diff --git a/tutorial/Pandas_tutorial_part1.ipynb b/tutorial/Pandas_tutorial_part1.ipynb new file mode 100644 index 0000000..e67d220 --- /dev/null +++ b/tutorial/Pandas_tutorial_part1.ipynb @@ -0,0 +1,3645 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "raw_mimetype": "-" + }, + "source": [ + "# Python for Data Analysis using Pandas (part 1 of 2)\n", + "\n", + "> The latest version of this notebook is always found at [github.com/tommyod/awesome-pandas](https://github.com/tommyod/awesome-pandas). \n", + " Improvements, corrections or suggestions? **Please submit a [Pull Request](https://github.com/tommyod/awesome-pandas/pulls).**\n", + " \n", + " ![](pandas_vs_excel_vs_sas.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Table of contents\n", + "\n", + "- **(1) Setup**\n", + " - (1.1) Installing Python and packages\n", + " - (1.2) Importing packages\n", + "- **(2) Importing data**\n", + " - (2.1) Importing .csv files\n", + " - (2.2) Other ways of creating DataFrames\n", + " - (2.3) Changing names and data types\n", + "- **(3) Summarizing data**\n", + " - (3.1) Peeking at the data\n", + " - (3.2) Null values and summary statistics\n", + " - (3.3) Unique values, value counts and sorting\n", + " - (3.4) Basic visualizations\n", + "- **(4) Selecting and computing new columns**\n", + " - (4.1) Accessing rows, columns and data\n", + " - (4.2) Selecting subsets of columns\n", + " - (4.3) Selecting subsets of rows\n", + " - (4.4) Selecting subsets of rows *and* columns\n", + " - (4.5) Creating new columns\n", + " - (4.6) Applying functions\n", + " \n", + " \n", + "**In the next video:** filtering and sorting, split-apply-combine, plotting, time series, machine learning, ..." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---------------------------------" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (1) Setup" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (1.1) Installing Python and packages" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Python and Anaconda\n", + "\n", + "If you haven't done it yet, you need to install Python.\n", + "I recommend the [Anaconda Distribution](https://www.anaconda.com/download/), and you should install version `3.X`.\n", + "- If you're on Windows, you will get a program called *Anaconda Prompt*. Open in and run `conda --version` to verify that everything works.\n", + "- If you're on Linux, open a terminal and run `conda --version`.\n", + "\n", + "Type `conda list` to see every installed package, and `conda update --all` to update every package. Type `python` to open an interactive Python terminal, and `exit()` to leave.\n", + "\n", + "### NumPy, matplotlib and Pandas\n", + "\n", + "![](https://indranilsinharoy.files.wordpress.com/2013/01/scientificpythonecosystemsi.png?w=584&h=442)\n", + "\n", + "*Image source: https://indranilsinharoy.com/2013/01/06/python-for-scientific-computing-a-collection-of-resources/*\n", + "\n", + "To install indiviual packages, run `conda install `. \n", + "The Anaconda distribution comes with 3 packages which this tutorial requires, namely [pandas](https://pandas.pydata.org/), [NumPy](http://www.numpy.org/) and [matplotlib](https://matplotlib.org/).\n", + "We'll also briefly use [sklearn](https://scikit-learn.org/stable/).\n", + "\n", + "- **NumPy** implements $n$-dimensional arrays in Python for efficient numerical computations. See the [arXiv](https://arxiv.org/pdf/1102.1523.pdf) paper for a nice introduction. To learn basic NumPy, consider doing these [100 NumPy exercises](https://github.com/rougier/numpy-100). For an in-depth look at NumPy and vectorization to speed up scientific computing, see [From Python to Numpy\n", + "](https://www.labri.fr/perso/nrougier/from-python-to-numpy/).\n", + "- **Matplotlib** is the most popular library for plotting in Python. See the beautiful [gallery](https://matplotlib.org/gallery.html) to get an overview of the capabilities of matplotlib. Read the [Matplotlib tutorial](http://www.labri.fr/perso/nrougier/teaching/matplotlib/matplotlib.html) by Nicolas P. Rougier for an introduction.\n", + "- **Pandas** is a library for data analysis based on two objects, the [Series](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.html) and the [DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html).\n", + "\n", + "### Jupyter\n", + "\n", + "A [Jupyter Notebook](https://jupyter-notebook.readthedocs.io/en/stable/) is an environment for running Python code interactively, displaying graphs and working with data. Think of it as a tool with capabilities somewhere between a simple terminal and a full fledged IDE. Move to a directory using the `cd` command in the terminal, then run `jupyter notebook` to start up a notebook. A video introduction to JupyterLab is [JupyterLab: Building Blocks for Interactive Computing](https://www.youtube.com/watch?v=Ejh0ftSjk6g). See also this list of [28 Jupyter Notebook tips](https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (1.2) Importing packages" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib\n", + "import KDEpy\n", + "import sklearn\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Package versions\n", + "\n", + "To make this Jupyter Notebook more easily reproducible, we list versions of the libraries we will be using." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Today is 2019-03-04 21:37:07.208603\n", + "----------------------------------------------------------------\n", + "pandas version 0.24.1\n", + "numpy version 1.15.4\n", + "matplotlib version 3.0.2\n", + "KDEpy version 0.6.11\n", + "sklearn version 0.20.1\n" + ] + } + ], + "source": [ + "import datetime\n", + "\n", + "print('Today is', datetime.datetime.utcnow())\n", + "print('-'*2**6)\n", + "\n", + "for lib in [pd, np, matplotlib, KDEpy, sklearn]:\n", + " print(f'{lib.__name__.ljust(12)} version {lib.__version__}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Jupyter Notebooks\n", + "\n", + "- Useful shortcuts: `SHIFT + TAB`, `SHIFT + ENTER`, `ESC`, `ENTER`, `E`, `A`, `D,D`, `I, I`. Type `H` to see all shortcuts.\n", + "- Executing terminal commands from within the notebook using `!`.\n", + "- Using markdown and $\\LaTeX{}$.\n", + "- Timing cells using `%%timeit` and other built-in magic commands.\n", + "- Pitfalls when using notebooks: state, order of execution, tidyness.\n", + "\n", + "Example of $\\LaTeX{}$ usage in notebooks:\n", + "\n", + "$$0 \\leq\n", + " \\left[\\operatorname{tr}(\\mathbf{A} \\mathbf{B})\\right]^2 \\leq\n", + " \\operatorname{tr}\\left(\\mathbf{A}^2\\right) \\operatorname{tr}\\left(\\mathbf{B}^2\\right) \\leq\n", + " \\left[\\operatorname{tr}(\\mathbf{A})\\right]^2 \\left[\\operatorname{tr}(\\mathbf{B})\\right]^2$$\n", + "$$\\varphi_X(t) = \\operatorname{E}\\left[\\exp \\left ({i\\int_\\mathbf{R} t(s)X(s)ds} \\right ) \\right]$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (2) Importing data\n", + "\n", + "Starting a cell with a `!` let's us use terminal commands. The UNIX `head` command shows the first rows of the file." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (2.1) Importing `.csv` files" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[01;34m.\u001b[00m\r\n", + "├── \u001b[01;34mdata\u001b[00m\r\n", + "│   ├── google_trends.csv\r\n", + "│   ├── movie_metadata.csv\r\n", + "│   ├── wine_data.csv\r\n", + "│   └── world_population_history.csv\r\n", + "├── Pandas_tutorial_part1.ipynb\r\n", + "├── Pandas_tutorial_part1.py\r\n", + "├── Pandas_tutorial_part2.ipynb\r\n", + "├── Pandas_tutorial_part2.py\r\n", + "├── \u001b[01;35mpandas_vs_excel_vs_sas.png\u001b[00m\r\n", + "└── Tutorial.py\r\n", + "\r\n", + "1 directory, 10 files\r\n" + ] + } + ], + "source": [ + "!tree . -L 2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "color,director_name,num_critic_for_reviews,duration,director_facebook_likes,actor_3_facebook_likes,actor_2_name,actor_1_facebook_likes,gross,genres,actor_1_name,movie_title,num_voted_users,cast_total_facebook_likes,actor_3_name,facenumber_in_poster,plot_keywords,movie_imdb_link,num_user_for_reviews,language,country,content_rating,budget,title_year,actor_2_facebook_likes,imdb_score,aspect_ratio,movie_facebook_likes\r", + "\r\n", + "Color,James Cameron,723,178,0,855,Joel David Moore,1000,760505847,Action|Adventure|Fantasy|Sci-Fi,CCH Pounder,Avatar ,886204,4834,Wes Studi,0,avatar|future|marine|native|paraplegic,http://www.imdb.com/title/tt0499549/?ref_=fn_tt_tt_1,3054,English,USA,PG-13,237000000,2009,936,7.9,1.78,33000\r", + "\r\n" + ] + } + ], + "source": [ + "!head data/movie_metadata.csv -n 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> **Interested in learning UNIX commands?** The book [The Linux Command Line](https://www.amazon.com/Linux-Command-Line-Complete-Introduction-ebook/dp/B006X2QEQS) gives a detailed introduction, and [Data Science at the Command Line](https://www.amazon.com/Data-Science-Command-Line-Time-Tested/dp/1491947853) shows how basic data manipulation may be done using the command line only." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The file has many columns, so we'll only load a couple into a pandas DataFrame.\n", + "To familiarize ourselves with with [magic commands](http://ipython.readthedocs.io/en/stable/interactive/magics.html), we'll use `%%time` to time the execution of the cell below." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded data of size (5043, 6) into memory.\n", + "CPU times: user 31.3 ms, sys: 3.91 ms, total: 35.2 ms\n", + "Wall time: 35.2 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "cols_to_use = ['movie_title', 'director_name', 'country', 'content_rating', 'imdb_score', 'gross']\n", + "df = pd.read_csv(r'data/movie_metadata.csv', sep=',', usecols=cols_to_use)\n", + "print(f'Loaded data of size {df.shape} into memory.')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " director_name gross movie_title \\\n", + "0 James Cameron 760505847.0 Avatar  \n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", + "\n", + " country content_rating imdb_score \n", + "0 USA PG-13 7.9 \n", + "1 USA PG-13 7.1 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head(2) # Show the top 2 rows" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `df.shape` attribute gives the rows and columns of the DataFrame." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(5043, 6)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape # Alternatively, use len(df) for row count" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (2.2) Other ways of creating DataFrames\n", + "\n", + "**The DataFrame**\n", + "\n", + "> Two-dimensional size-mutable, potentially heterogeneous tabular data\n", + "structure with **labeled axes** (rows and columns). Arithmetic operations\n", + "align on both row and column labels. Can be thought of as a **dict-like\n", + "container for Series objects**. The primary pandas data structure.\n", + "\n", + "**Creating a DataFrame from scratch**" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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World rankingNameCitizenshipNet worth (USD)Sources of wealth
021Georg SchaefflerGermany26.9 billionSchaeffler Group
137Beate Heister (b. Albrecht) & Karl Albrecht Jr.Germany21.3 billionAldi Süd
246Dieter SchwarzGermany19.4 billionSchwarz Gruppe
349Theo Albrecht Jr.Germany19 billionAldi Nord and Trader Joe's
450Michael OttoGermany18.1 billionOtto Group
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" + ], + "text/plain": [ + " World ranking Name Citizenship \\\n", + "0 21 Georg Schaeffler Germany \n", + "1 37 Beate Heister (b. Albrecht) & Karl Albrecht Jr. Germany \n", + "2 46 Dieter Schwarz Germany \n", + "3 49 Theo Albrecht Jr. Germany \n", + "4 50 Michael Otto Germany \n", + "\n", + " Net worth (USD) Sources of wealth \n", + "0 26.9 billion Schaeffler Group \n", + "1 21.3 billion Aldi Süd \n", + "2 19.4 billion Schwarz Gruppe \n", + "3 19 billion Aldi Nord and Trader Joe's \n", + "4 18.1 billion Otto Group " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Read HTML tables into a list of DataFrame objects.\n", + "url = r'https://en.wikipedia.org/wiki/List_of_Germans_by_net_worth'\n", + "tables = pd.read_html(url, header=0)\n", + "\n", + "df_net_worth = tables[0]\n", + "\n", + "# Asserts can be useful for sanity checks\n", + "assert len(df_net_worth) > 0 \n", + "assert df_net_worth.Name.is_unique\n", + "\n", + "\n", + "df_net_worth.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Reading from databases is also possible.**\n", + "\n", + "Reading from Microsoft SQL using `pyodbc` and `pd.read_sql(sql_code, connection)`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---------\n", + "\n", + "> **Gotcha.** Methods on DataFrames **return a new instance** by default. In other words, they behave like methods on *immutable* Python object, and not like methods on *mutable* objects." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1, 2, 4, 6, 9]\n", + "Tommy\n" + ] + } + ], + "source": [ + "# Lists are MUTABLE\n", + "scores = [6, 2, 4, 9, 1]\n", + "scores.sort() # Changes the object in-place, returns None\n", + "print(scores)\n", + "\n", + "# Strings are IMMUTABLE\n", + "my_name = 'tommy'\n", + "my_name = my_name.capitalize() # A new instance is returned\n", + "print(my_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (2.3) Changing names and data types" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Director_nameGrossMovie_titleCountryContent_ratingImdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.1
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" + ], + "text/plain": [ + " Director_name Gross Movie_title \\\n", + "0 James Cameron 760505847.0 Avatar  \n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", + "\n", + " Country Content_rating Imdb_score \n", + "0 USA PG-13 7.9 \n", + "1 USA PG-13 7.1 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Alter axes labels\n", + "df_net_worth = (df_net_worth\n", + " .rename(columns={'Net worth (USD)': 'net_worth',\n", + " 'World ranking': 'world_ranking',\n", + " 'Sources of wealth': 'wealth_source'}))\n", + "\n", + "df.rename(columns=str.capitalize).head(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The data type of each column may be listed using `df.dtypes`. Automatic conversion is possible via `pd.to_numeric` and `pd.to_datetime`." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "director_name object\n", + "gross float64\n", + "movie_title object\n", + "country object\n", + "content_rating object\n", + "imdb_score float64\n", + "dtype: object" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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world_rankingNameCitizenshipnet_worthwealth_sourcenet_worth_num
021Georg SchaefflerGermany26.9 billionSchaeffler Group26.9
137Beate Heister (b. Albrecht) & Karl Albrecht Jr.Germany21.3 billionAldi Süd21.3
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" + ], + "text/plain": [ + " world_ranking Name Citizenship \\\n", + "0 21 Georg Schaeffler Germany \n", + "1 37 Beate Heister (b. Albrecht) & Karl Albrecht Jr. Germany \n", + "\n", + " net_worth wealth_source net_worth_num \n", + "0 26.9 billion Schaeffler Group 26.9 \n", + "1 21.3 billion Aldi Süd 21.3 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_net_worth['net_worth_num'] = (df_net_worth['net_worth']\n", + " .str.replace(' billion', '')\n", + " .apply(float))\n", + "\n", + "df_net_worth.head(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Getting help\n", + "\n", + "There are many ways to help help on objects and methods.\n", + "\n", + "- Use `SHIFT TAB` in a notebook.\n", + "- Use question marks in the notebook, e.g. `?df.sum`.\n", + "- Use the built-in Python function `help`, e.g. `help(df.sum)`." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "# df.sum?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (3) Summarizing data\n", + "\n", + "This section shows some important methods related to summarizing data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (3.1) Peeking at the data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Three methods that are useful when peeking at the data are `df.head`, `df.tail` and `df.sample`.\n", + "Head and tail are $\\mathcal{O}(1)$ operations, while sample is $\\mathcal{O}(n)$, where $n$ is the number of rows.\n", + "For small datasets, this makes no difference in practice. We'll use `df.sample` here." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.1
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" + ], + "text/plain": [ + " director_name gross movie_title \\\n", + "0 James Cameron 760505847.0 Avatar  \n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", + "\n", + " country content_rating imdb_score \n", + "0 USA PG-13 7.9 \n", + "1 USA PG-13 7.1 " + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Return the first `n` rows.\n", + "df.head(n=2) # df.tail(n=2) returns the last rows" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
2699Mark Piznarski10494147.0Here on EarthUSAPG-135.1
1558David Cronenberg31493782.0A History of ViolenceUSAR7.5
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" + ], + "text/plain": [ + " director_name gross movie_title country \\\n", + "2699 Mark Piznarski 10494147.0 Here on Earth  USA \n", + "1558 David Cronenberg 31493782.0 A History of Violence  USA \n", + "\n", + " content_rating imdb_score \n", + "2699 PG-13 5.1 \n", + "1558 R 7.5 " + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.sample(n=2, replace=False, weights=None, random_state=None)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (3.2) Null values and summary statistics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We should make sure the data types are correct. To do so, we can use `df.dtypes`, or `df.info()` for some more information." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 5043 entries, 0 to 5042\n", + "Data columns (total 6 columns):\n", + "director_name 4939 non-null object\n", + "gross 4159 non-null float64\n", + "movie_title 5043 non-null object\n", + "country 5038 non-null object\n", + "content_rating 4740 non-null object\n", + "imdb_score 5043 non-null float64\n", + "dtypes: float64(2), object(4)\n", + "memory usage: 236.5+ KB\n" + ] + } + ], + "source": [ + "# Print a concise summary of a DataFrame\n", + "df.info(verbose=True, memory_usage=True, null_counts=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We have some null values. Let's count them by chaining `df.isnull()` and `df.sum()`." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "director_name 104\n", + "gross 884\n", + "movie_title 0\n", + "country 5\n", + "content_rating 303\n", + "imdb_score 0\n", + "dtype: int64" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Detect missing values -> sum over rows\n", + "null_values = df.isnull().sum(axis=0)\n", + "null_values # / len(df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The result of the above is not a DataFrame object, but a Series." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "pandas.core.series.Series" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(null_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![alt text](https://www.mathsisfun.com/algebra/images/scalar-vector-matrix.svg)\n", + "*Image source:* https://www.mathsisfun.com/algebra/scalar-vector-matrix.html\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can make the output prettier by converting the `null_values` Series to a DataFrame using the `to_frame()` method, then transposing using `.T`, and finally renaming the first index." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
Missing values104884053030
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" + ], + "text/plain": [ + " director_name gross movie_title country content_rating \\\n", + "Missing values 104 884 0 5 303 \n", + "\n", + " imdb_score \n", + "Missing values 0 " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "null_values.to_frame().T.rename(index={0: 'Missing values'})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The above is called *method chaining*, and can be written like so:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
Missing values104884053030
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" + ], + "text/plain": [ + " director_name gross movie_title country content_rating \\\n", + "Missing values 104 884 0 5 303 \n", + "\n", + " imdb_score \n", + "Missing values 0 " + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(df\n", + " .isnull() # Figure out whether every entry is null (missing), or not\n", + " .sum(axis=0) # Sum over each column, axis=0 is the default\n", + " .to_frame() # The result is a Series, convert to DataFrame\n", + " .T # Transpose (switch rows and columns)\n", + " .rename(index={0:'Missing values'}) # Rename the index and show it\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A tour of summarization would not be complete without `df.describe()`. \n", + "Calling `df.count()`, `df.nunique()`, `df.mean()`, `df.std()`, `df.min()`, `df.quantile()`, `df.max()` is also possible.\n", + "\n", + "> **Gotcha.** There are 200+ methods defined on a DataFrame. See the [API Reference](https://pandas.pydata.org/pandas-docs/stable/api.html) for an exhaustive list." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "# dir(pd.DataFrame)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
count493941595043503847405043
unique239849176518
topSteven SpielbergPanUSAR
freq26338072118
mean4.84684e+076.44214
std6.8453e+071.12512
min1621.6
50%2.55175e+076.6
max7.60506e+089.5
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" + ], + "text/plain": [ + " director_name gross movie_title country content_rating \\\n", + "count 4939 4159 5043 5038 4740 \n", + "unique 2398 4917 65 18 \n", + "top Steven Spielberg Pan  USA R \n", + "freq 26 3 3807 2118 \n", + "mean 4.84684e+07 \n", + "std 6.8453e+07 \n", + "min 162 \n", + "50% 2.55175e+07 \n", + "max 7.60506e+08 \n", + "\n", + " imdb_score \n", + "count 5043 \n", + "unique \n", + "top \n", + "freq \n", + "mean 6.44214 \n", + "std 1.12512 \n", + "min 1.6 \n", + "50% 6.6 \n", + "max 9.5 " + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe(percentiles=[0.5], include='all').fillna('')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(5043, 6)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(4092, 6)" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.dropna(axis=0, how='any').shape" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(4920, 6)" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.drop_duplicates(subset=None).shape # Use df[df.duplicated()] to see rows" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.dropna(axis=0, how='any').drop_duplicates(subset=None)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (3.3) Unique values, value counts and sorting" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['PG-13', 'PG', 'G', 'R', 'Unrated', 'Approved', 'NC-17', 'X',\n", + " 'Not Rated', 'M', 'GP', 'Passed'], dtype=object)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.content_rating.unique() # Not the same as: df.content_rating.is_unique" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['PG-13', 'PG', 'G', 'R', 'Unrated', 'Approved', 'NC-17', 'X', 'Not Rated', 'M', 'GP', 'Passed']\n" + ] + } + ], + "source": [ + "print(df.content_rating.drop_duplicates().tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "R 1818\n", + "PG-13 1352\n", + "PG 596\n", + "G 95\n", + "Not Rated 56\n", + "Unrated 34\n", + "Approved 18\n", + "X 9\n", + "NC-17 6\n", + "Passed 3\n", + "M 2\n", + "GP 1\n", + "Name: content_rating, dtype: int64" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.content_rating.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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movie_titlegross
0Avatar760505847.0
26Titanic658672302.0
29Jurassic World652177271.0
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" + ], + "text/plain": [ + " movie_title gross\n", + "0 Avatar  760505847.0\n", + "26 Titanic  658672302.0\n", + "29 Jurassic World  652177271.0" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[['movie_title', 'gross']].nlargest(3, 'gross')" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4735Siddiq Barmak1127331.0OsamaAfghanistanPG-137.4
4000Juan José Campanella20167424.0The Secret in Their EyesArgentinaR8.2
4415Fabián Bielinsky1221261.0Nine QueensArgentinaR7.9
4450Lucrecia Martel304124.0The Holy GirlArgentinaR6.7
1491Hark Tsui10076136.0Knock OffArubaR4.8
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" + ], + "text/plain": [ + " director_name gross movie_title \\\n", + "4735 Siddiq Barmak 1127331.0 Osama  \n", + "4000 Juan José Campanella 20167424.0 The Secret in Their Eyes  \n", + "4415 Fabián Bielinsky 1221261.0 Nine Queens  \n", + "4450 Lucrecia Martel 304124.0 The Holy Girl  \n", + "1491 Hark Tsui 10076136.0 Knock Off  \n", + "\n", + " country content_rating imdb_score \n", + "4735 Afghanistan PG-13 7.4 \n", + "4000 Argentina R 8.2 \n", + "4415 Argentina R 7.9 \n", + "4450 Argentina R 6.7 \n", + "1491 Aruba R 4.8 " + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Sort by country, then by IMDB_score. Put NA values last\n", + "df.sort_values(by=['country', 'imdb_score'], \n", + " ascending=[True, False], \n", + " na_position='last').head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (3.4) Basic visualizations\n", + "\n", + "Some quick visualizations." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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grossimdb_score
gross1.000000.20497
imdb_score0.204971.00000
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" + ], + "text/plain": [ + " gross imdb_score\n", + "gross 1.00000 0.20497\n", + "imdb_score 0.20497 1.00000" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.corr(method='pearson')" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "(df.content_rating\n", + " .value_counts()\n", + " .to_frame() # Below are the default values, except `figsize`\n", + " .plot.barh(subplots=False, sharex=None, sharey=False, layout=None, \n", + " figsize=(10, 5), use_index=True, title=None, grid=None, legend=True, \n", + " style=None, logx=False, logy=False, loglog=False, xticks=None, \n", + " yticks=None, xlim=None, ylim=None, rot=None, fontsize=None, \n", + " colormap=None, table=False, yerr=None, xerr=None, \n", + " secondary_y=False, sort_columns=False));" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot = pd.plotting.scatter_matrix(df, alpha=0.5, figsize=(10, 5))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (4) Selecting and computing new columns\n", + "\n", + "This section is about selecting subsets of a datset, or creating new data from existing data, i.e.:\n", + "\n", + "- Selecting a **single column**, or a **subset of columns**.\n", + "- Selecting a **subset of rows**, i.e. filtering.\n", + "- Chaining and/or combining the above operations to accomplish both.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (4.1) Accessing index, columns and data" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Int64Index([ 0, 1, 2, 3, 5, 6, 7, 8, 9, 10,\n", + " ...\n", + " 5021, 5025, 5026, 5027, 5033, 5034, 5035, 5037, 5041, 5042],\n", + " dtype='int64', length=3990)" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.index" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['director_name', 'gross', 'movie_title', 'country', 'content_rating',\n", + " 'imdb_score'],\n", + " dtype='object')" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([['James Cameron', 760505847.0, 'Avatar\\xa0', 'USA', 'PG-13', 7.9],\n", + " ['Gore Verbinski', 309404152.0,\n", + " \"Pirates of the Caribbean: At World's End\\xa0\", 'USA', 'PG-13',\n", + " 7.1],\n", + " ['Sam Mendes', 200074175.0, 'Spectre\\xa0', 'UK', 'PG-13', 6.8],\n", + " ...,\n", + " ['Edward Burns', 4584.0, 'Newlyweds\\xa0', 'USA', 'Not Rated', 6.4],\n", + " ['Daniel Hsia', 10443.0, 'Shanghai Calling\\xa0', 'USA', 'PG-13',\n", + " 6.3],\n", + " ['Jon Gunn', 85222.0, 'My Date with Drew\\xa0', 'USA', 'PG', 6.6]],\n", + " dtype=object)" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# This is very useful when using data with libraries\n", + "df.to_numpy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([7.60505847e+08, 3.09404152e+08, 2.00074175e+08, ...,\n", + " 4.58400000e+03, 1.04430000e+04, 8.52220000e+04])" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.gross.dropna().to_numpy()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (4.2) Selecting subsets of columns" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['director_name', 'gross', 'movie_title', 'country', 'content_rating', 'imdb_score']\n" + ] + } + ], + "source": [ + "print(df.columns.tolist()) # Get the columns" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 James Cameron\n", + "1 Gore Verbinski\n", + "2 Sam Mendes\n", + "Name: director_name, dtype: object" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.director_name.head(3) # Alternatively, use df['director_name'].head(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Selecting two or more columns." + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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movie_titlecountry
0AvatarUSA
1Pirates of the Caribbean: At World's EndUSA
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" + ], + "text/plain": [ + " movie_title country\n", + "0 Avatar  USA\n", + "1 Pirates of the Caribbean: At World's End  USA" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[['movie_title', 'country']].head(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The most useful selection function is `df.loc[[row1, row2, ...], [col1, col2, ...]]`.\n", + "\n", + "- `df.loc[:, [col1, col2]]` selects every row, and columns `[col1, col2]`\n", + "- `df.loc[[row1, row2], :]` selects rows `[row1, row2]`, and every column" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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movie_titlecountry
0AvatarUSA
1Pirates of the Caribbean: At World's EndUSA
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" + ], + "text/plain": [ + " movie_title country\n", + "0 Avatar  USA\n", + "1 Pirates of the Caribbean: At World's End  USA" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[:, ['movie_title', 'country']].head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + } + ], + "source": [ + "a = df.loc[:, 'gross'] # Returns a Series\n", + "b = df.loc[:, ['gross']] # Returns a DataFrame\n", + "\n", + "print(type(a))\n", + "print(type(b))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead of selecting a subset of columns to *keep*, we can select a subset to *drop*." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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countrycontent_ratingimdb_score
0USAPG-137.9
1USAPG-137.1
2UKPG-136.8
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director_namegrossmovie_title
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's End
2Sam Mendes200074175.0Spectre
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" + ], + "text/plain": [ + " director_name gross movie_title\n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End \n", + "2 Sam Mendes 200074175.0 Spectre " + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Integer-location based indexing\n", + "df.iloc[1:3, [0, 1, 2]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (4.3) Selecting subsets of rows" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
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" + ], + "text/plain": [ + " director_name gross movie_title country content_rating imdb_score\n", + "0 James Cameron 760505847.0 Avatar  USA PG-13 7.9" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Return the first `n` rows\n", + "df.head(n=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4498Sergio Leone6100000.0The Good, the Bad and the UglyItalyApproved8.9
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
4029Fernando Meirelles7563397.0City of GodBrazilR8.7
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" + ], + "text/plain": [ + " director_name gross \\\n", + "4498 Sergio Leone 6100000.0 \n", + "270 Peter Jackson 313837577.0 \n", + "4029 Fernando Meirelles 7563397.0 \n", + "\n", + " movie_title country \\\n", + "4498 The Good, the Bad and the Ugly  Italy \n", + "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", + "4029 City of God  Brazil \n", + "\n", + " content_rating imdb_score \n", + "4498 Approved 8.9 \n", + "270 PG-13 8.8 \n", + "4029 R 8.7 " + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Top three movies / TV-series not from the USA\n", + "df[df.country != 'USA'].nlargest(3, 'imdb_score')" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
2323Hayao Miyazaki2298191.0Princess MononokeJapanPG-138.4
4659Asghar Farhadi7098492.0A SeparationIranPG-138.4
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" + ], + "text/plain": [ + " director_name gross \\\n", + "270 Peter Jackson 313837577.0 \n", + "2323 Hayao Miyazaki 2298191.0 \n", + "4659 Asghar Farhadi 7098492.0 \n", + "\n", + " movie_title country \\\n", + "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", + "2323 Princess Mononoke  Japan \n", + "4659 A Separation  Iran \n", + "\n", + " content_rating imdb_score \n", + "270 PG-13 8.8 \n", + "2323 PG-13 8.4 \n", + "4659 PG-13 8.4 " + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Best non-American films, with content rating PG-13\n", + "mask = (df.country != 'USA') & (df.content_rating == 'PG-13')\n", + "df[mask].nlargest(3, 'imdb_score')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (4.4) Selecting subsets of rows *and* columns" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namemovie_titlecountry
1196James WanThe Conjuring 2USA
1562Martin ScorseseBringing Out the DeadUSA
2163James WanThe ConjuringUSA
2969Peter WebberGirl with a Pearl EarringUK
3858Todd SolondzLife During WartimeUSA
4298Lance MungiaSix-String SamuraiUSA
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" + ], + "text/plain": [ + " director_name movie_title country\n", + "1196 James Wan The Conjuring 2  USA\n", + "1562 Martin Scorsese Bringing Out the Dead  USA\n", + "2163 James Wan The Conjuring  USA\n", + "2969 Peter Webber Girl with a Pearl Earring  UK\n", + "3858 Todd Solondz Life During Wartime  USA\n", + "4298 Lance Mungia Six-String Samurai  USA" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Above average movies, with the title containing 'ring'\n", + "row_mask = ((df.imdb_score > df.imdb_score.mean()) & \n", + " df.movie_title.str.contains('ring'))\n", + "df.loc[row_mask, ['director_name', 'movie_title', 'country']]" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namemovie_titlecontent_ratingimdb_score
0James CameronAvatarPG-137.9
1Gore VerbinskiPirates of the Caribbean: At World's EndPG-137.1
2Sam MendesSpectrePG-136.8
3Christopher NolanThe Dark Knight RisesPG-138.5
5Andrew StantonJohn CarterPG-136.6
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" + ], + "text/plain": [ + " director_name movie_title \\\n", + "0 James Cameron Avatar  \n", + "1 Gore Verbinski Pirates of the Caribbean: At World's End  \n", + "2 Sam Mendes Spectre  \n", + "3 Christopher Nolan The Dark Knight Rises  \n", + "5 Andrew Stanton John Carter  \n", + "\n", + " content_rating imdb_score \n", + "0 PG-13 7.9 \n", + "1 PG-13 7.1 \n", + "2 PG-13 6.8 \n", + "3 PG-13 8.5 \n", + "5 PG-13 6.6 " + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Columns containing and underscore\n", + "cols = [c for c in df.columns if '_' in c]\n", + "df.loc[:, cols].head()" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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grossimdb_score
0760505847.07.9
1309404152.07.1
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" + ], + "text/plain": [ + " gross imdb_score\n", + "0 760505847.0 7.9\n", + "1 309404152.0 7.1" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Numerical columns\n", + "numeric_cols = df.dtypes[df.dtypes == np.float].index.tolist()\n", + "df.loc[:, numeric_cols].head(n=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (4.5) Creating new columns" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_scorelog_gross
0James Cameron760505847.0AvatarUSAPG-137.98.881103
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.18.490526
\n", + "
" + ], + "text/plain": [ + " director_name gross movie_title \\\n", + "0 James Cameron 760505847.0 Avatar  \n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", + "\n", + " country content_rating imdb_score log_gross \n", + "0 USA PG-13 7.9 8.881103 \n", + "1 USA PG-13 7.1 8.490526 " + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "temp = df.copy() # Copy the DataFrame\n", + "\n", + "# Create a new column - based on the gross income\n", + "temp['log_gross'] = temp['gross'].apply(np.log10)\n", + "\n", + "temp.head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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grossimdb_score
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grossimdb_score
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" + ], + "text/plain": [ + " gross imdb_score\n", + "0 760505847 7\n", + "1 309404152 7" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[:, ['gross', 'imdb_score']].applymap(int).head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "gross 4.839239e+07\n", + "imdb_score 6.463283e+00\n", + "dtype: float64" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[:, ['gross', 'imdb_score']].mean().head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "gross 760505685.0\n", + "imdb_score 7.7\n", + "dtype: float64" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Or specify your own aggregation function\n", + "def spread(array):\n", + " return np.max(array) - np.min(array)\n", + "\n", + "df.loc[:, ['gross', 'imdb_score']].aggregate(spread, axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Next up ...\n", + "\n", + "**In the next video:** filtering and sorting, split-apply-combine, plotting, time series, machine learning, ..." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tutorial/Pandas_tutorial_part2.ipynb b/tutorial/Pandas_tutorial_part2.ipynb new file mode 100644 index 0000000..7fdea6a --- /dev/null +++ b/tutorial/Pandas_tutorial_part2.ipynb @@ -0,0 +1,4665 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "raw_mimetype": "-" + }, + "source": [ + "# Python for Data Analysis using Pandas (part 2 of 2)\n", + "\n", + "> The latest version of this notebook is always found at [github.com/tommyod/awesome-pandas](https://github.com/tommyod/awesome-pandas). \n", + " Improvements, corrections or suggestions? **Please submit a [Pull Request](https://github.com/tommyod/awesome-pandas/pulls).**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Table of contents\n", + "\n", + "- **(5) Filtering and sorting**\n", + " - (5.1) Equality, non-equality and logical operators\n", + " - (5.2) Group membership and string filtering\n", + "- **(6) Split-apply-combine and pivots**\n", + " - (6.1) The groupby operation\n", + " - (6.2) Several groups and aggregations\n", + " - (6.3) Unstacking and stacking\n", + " - (6.4) Pivoting and melting\n", + " - (6.4) Merging\n", + "- **(7) Plotting**\n", + " - (7.1) Built-in `plot()` methods\n", + " - (7.2) Using matplotlib\n", + "- **(8) Time series manipulations**\n", + " - (8.1) `.dt` accessor\n", + " - (8.2) Rolling window functions\n", + " - (8.3) Resampling\n", + "- **(9) Modeling and Machine Learning**\n", + " - (9.1) Dummy variables for categorical data\n", + " - (9.2) Training a model\n", + "- **(10) Misc tips and tricks**\n", + " - (10.1) Performance\n", + "- **(11) Problems and answers**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---------------------------------" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (1) Setup" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (1.1) Installing Python and packages" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Python and Anaconda\n", + "\n", + "If you haven't done it yet, you need to install Python.\n", + "I recommend the [Anaconda Distribution](https://www.anaconda.com/download/), and you should install version `3.X`.\n", + "- If you're on Windows, you will get a program called *Anaconda Prompt*. Open in and run `conda --version` to verify that everything works.\n", + "- If you're on Linux, open a terminal and run `conda --version`.\n", + "\n", + "Type `conda list` to see every installed package, and `conda update --all` to update every package. Type `python` to open an interactive Python terminal, and `exit()` to leave." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (1.2) Importing packages" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib\n", + "import KDEpy\n", + "import sklearn\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Package versions\n", + "\n", + "To make this Jupyter Notebook reproducible, we list versions of the libraries we will be using." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Today is 2019-03-04 21:37:06.735457\n", + "----------------------------------------------------------------\n", + "pandas version 0.24.1\n", + "numpy version 1.15.4\n", + "matplotlib version 3.0.2\n", + "KDEpy version 0.6.11\n", + "sklearn version 0.20.1\n" + ] + } + ], + "source": [ + "import datetime\n", + "\n", + "print('Today is', datetime.datetime.utcnow())\n", + "print('-'*2**6)\n", + "\n", + "for lib in [pd, np, matplotlib, KDEpy, sklearn]:\n", + " print(f'{lib.__name__.ljust(12)} version {lib.__version__}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (2) Importing data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (2.1) Importing `.csv` files" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded data of size (5043, 6) into memory.\n", + "CPU times: user 31.8 ms, sys: 0 ns, total: 31.8 ms\n", + "Wall time: 32.5 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "cols_to_use = ['movie_title', 'director_name', 'country', 'content_rating', 'imdb_score', 'gross']\n", + "df = pd.read_csv(r'data/movie_metadata.csv', sep=',', usecols=cols_to_use)\n", + "print(f'Loaded data of size {df.shape} into memory.')\n", + "\n", + "df = df.dropna(axis=0, how='any').drop_duplicates(subset=None)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Reading a HTML table from the web**" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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World rankingNameCitizenshipNet worth (USD)Sources of wealth
021Georg SchaefflerGermany26.9 billionSchaeffler Group
137Beate Heister (b. Albrecht) & Karl Albrecht Jr.Germany21.3 billionAldi Süd
246Dieter SchwarzGermany19.4 billionSchwarz Gruppe
349Theo Albrecht Jr.Germany19 billionAldi Nord and Trader Joe's
450Michael OttoGermany18.1 billionOtto Group
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" + ], + "text/plain": [ + " World ranking Name Citizenship \\\n", + "0 21 Georg Schaeffler Germany \n", + "1 37 Beate Heister (b. Albrecht) & Karl Albrecht Jr. Germany \n", + "2 46 Dieter Schwarz Germany \n", + "3 49 Theo Albrecht Jr. Germany \n", + "4 50 Michael Otto Germany \n", + "\n", + " Net worth (USD) Sources of wealth \n", + "0 26.9 billion Schaeffler Group \n", + "1 21.3 billion Aldi Süd \n", + "2 19.4 billion Schwarz Gruppe \n", + "3 19 billion Aldi Nord and Trader Joe's \n", + "4 18.1 billion Otto Group " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Read HTML tables into a list of DataFrame objects.\n", + "url = r'https://en.wikipedia.org/wiki/List_of_Germans_by_net_worth'\n", + "tables = pd.read_html(url, header=0)\n", + "\n", + "df_net_worth = tables[0]\n", + "\n", + "# Asserts can be useful for sanity checks\n", + "assert len(df_net_worth) > 0 \n", + "assert df_net_worth.Name.is_unique\n", + "\n", + "\n", + "df_net_worth.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (2.3) Changing names and data types" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# Alter axes labels\n", + "df_net_worth = (df_net_worth\n", + " .rename(columns={'Net worth (USD)': 'net_worth',\n", + " 'World ranking': 'world_ranking',\n", + " 'Sources of wealth': 'wealth_source'}))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "df_net_worth['net_worth_num'] = (df_net_worth['net_worth']\n", + " .str.replace(' billion', '')\n", + " .apply(float))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (5) Filtering and sorting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We've already seen basic filtering. \n", + "\n", + "- `==` defines equality\n", + "- `!=` defines inquality equality\n", + "- `~` negates logic, e.g. `True` -> `False`\n", + "- `&` represents elementwise `and`\n", + "- `|` represents elementwise `or`\n", + "\n", + "Remember to parenthesize expressions, write:\n", + "\n", + "> `(df.col_A > 5) & (df.col_B <= 5)`\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (5.1) Equality, non-equality and logical operators" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
3690Morten Tyldum1196752.0HeadhuntersNorwayR7.6
4007André Øvredal252652.0TrollhunterNorwayPG-137.0
4240Petter Næss313436.0EllingNorwayR7.6
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" + ], + "text/plain": [ + " director_name gross movie_title country content_rating \\\n", + "3690 Morten Tyldum 1196752.0 Headhunters  Norway R \n", + "4007 André Øvredal 252652.0 Trollhunter  Norway PG-13 \n", + "4240 Petter Næss 313436.0 Elling  Norway R \n", + "\n", + " imdb_score \n", + "3690 7.6 \n", + "4007 7.0 \n", + "4240 7.6 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Movies and TV shows from Norway\n", + "df[df.country == 'Norway'].head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4498Sergio Leone6100000.0The Good, the Bad and the UglyItalyApproved8.9
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
4029Fernando Meirelles7563397.0City of GodBrazilR8.7
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" + ], + "text/plain": [ + " director_name gross \\\n", + "4498 Sergio Leone 6100000.0 \n", + "270 Peter Jackson 313837577.0 \n", + "4029 Fernando Meirelles 7563397.0 \n", + "\n", + " movie_title country \\\n", + "4498 The Good, the Bad and the Ugly  Italy \n", + "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", + "4029 City of God  Brazil \n", + "\n", + " content_rating imdb_score \n", + "4498 Approved 8.9 \n", + "270 PG-13 8.8 \n", + "4029 R 8.7 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mask = ((df.imdb_score > 8) & (df.country != 'USA') & (df.gross > 10**6))\n", + "df[mask].nlargest(3, columns=['imdb_score'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (5.2) Group membership and string filtering" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4747Akira Kurosawa269061.0Seven SamuraiJapanUnrated8.7
2373Hayao Miyazaki10049886.0Spirited AwayJapanPG8.6
2323Hayao Miyazaki2298191.0Princess MononokeJapanPG-138.4
2047Hayao Miyazaki4710455.0Howl's Moving CastleJapanPG8.2
3423Katsuhiro Ôtomo439162.0AkiraJapanR8.1
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" + ], + "text/plain": [ + " director_name gross movie_title country \\\n", + "4747 Akira Kurosawa 269061.0 Seven Samurai  Japan \n", + "2373 Hayao Miyazaki 10049886.0 Spirited Away  Japan \n", + "2323 Hayao Miyazaki 2298191.0 Princess Mononoke  Japan \n", + "2047 Hayao Miyazaki 4710455.0 Howl's Moving Castle  Japan \n", + "3423 Katsuhiro Ôtomo 439162.0 Akira  Japan \n", + "\n", + " content_rating imdb_score \n", + "4747 Unrated 8.7 \n", + "2373 PG 8.6 \n", + "2323 PG-13 8.4 \n", + "2047 PG 8.2 \n", + "3423 R 8.1 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Top three movies from Japan or Hong Kong\n", + "df[df.country.isin(['Japan', 'Hong Kong'])].nlargest(5, 'imdb_score')" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.1
2Sam Mendes200074175.0SpectreUKPG-136.8
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" + ], + "text/plain": [ + " director_name gross movie_title \\\n", + "0 James Cameron 760505847.0 Avatar  \n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", + "2 Sam Mendes 200074175.0 Spectre  \n", + "\n", + " country content_rating imdb_score \n", + "0 USA PG-13 7.9 \n", + "1 USA PG-13 7.1 \n", + "2 UK PG-13 6.8 " + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Movies and TV shows NOT from scandinavia\n", + "df[~df.country.isin(['Norway, Sweden', 'Denmark'])].head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
339Peter Jackson377019252.0The Lord of the Rings: The Return of the KingUSAPG-138.9
340Peter Jackson340478898.0The Lord of the Rings: The Two TowersUSAPG-138.7
1170Andrew Niccol24127895.0Lord of WarUSAR7.6
1974Catherine Hardwicke11008432.0Lords of DogtownUSAPG-137.1
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" + ], + "text/plain": [ + " director_name gross \\\n", + "270 Peter Jackson 313837577.0 \n", + "339 Peter Jackson 377019252.0 \n", + "340 Peter Jackson 340478898.0 \n", + "1170 Andrew Niccol 24127895.0 \n", + "1974 Catherine Hardwicke 11008432.0 \n", + "\n", + " movie_title country \\\n", + "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", + "339 The Lord of the Rings: The Return of the King  USA \n", + "340 The Lord of the Rings: The Two Towers  USA \n", + "1170 Lord of War  USA \n", + "1974 Lords of Dogtown  USA \n", + "\n", + " content_rating imdb_score \n", + "270 PG-13 8.8 \n", + "339 PG-13 8.9 \n", + "340 PG-13 8.7 \n", + "1170 R 7.6 \n", + "1974 PG-13 7.1 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Contains the word 'lord'\n", + "mask = df.movie_title.str.lower().str.contains(\"lord\")\n", + "\n", + " # Gross better than 25 % of the movies\n", + "mask = mask & (df.gross > df.gross.quantile(q=0.25))\n", + "\n", + "df[mask]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (6) Split-apply-combine and pivots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (6.1) The groupby operation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](https://data36.com/wp-content/uploads/2017/06/SQL-GROUP-BY-clause-768x540.png)\n", + "\n", + "*Image source is https://data36.com/sql-functions-beginners-tutorial-ep3/*" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Aruba1.007614e+074.8
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" + ], + "text/plain": [ + " gross imdb_score\n", + "country \n", + "Afghanistan 1.127331e+06 7.4\n", + "Argentina 7.230936e+06 7.6\n", + "Aruba 1.007614e+07 4.8" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.groupby(df.country).mean().head(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Directors with the most movies." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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movie_title
director_name
Steven Spielberg25
Clint Eastwood19
Woody Allen19
Martin Scorsese18
Ridley Scott16
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" + ], + "text/plain": [ + " movie_title\n", + "director_name \n", + "Steven Spielberg 25\n", + "Clint Eastwood 19\n", + "Woody Allen 19\n", + "Martin Scorsese 18\n", + "Ridley Scott 16" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(df\n", + " .groupby(df.director_name)\n", + " .nunique()\n", + " .movie_title\n", + " .nlargest(5)\n", + " .to_frame()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (6.2) Several groups and aggregations\n", + "\n", + "A group can be a combination of columns, e.g. [`country`, `content_rating`]." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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imdb_score
countrycontent_rating
AfghanistanPG-137.40
ArgentinaR7.60
ArubaR4.80
AustraliaG6.30
PG6.20
PG-136.51
R6.60
Unrated6.30
BelgiumR7.10
BrazilR8.17
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" + ], + "text/plain": [ + " imdb_score\n", + "country content_rating \n", + "Afghanistan PG-13 7.40\n", + "Argentina R 7.60\n", + "Aruba R 4.80\n", + "Australia G 6.30\n", + " PG 6.20\n", + " PG-13 6.51\n", + " R 6.60\n", + " Unrated 6.30\n", + "Belgium R 7.10\n", + "Brazil R 8.17" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.groupby(['country', 'content_rating']).mean().imdb_score.round(2).to_frame().head(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Serveral aggregation functions may be used. \n", + "Below we see directors and their `average`, `max` and `min` imdb_scores." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meanminmax
director_name
Aaron Schneider7.17.17.1
Aaron Seltzer2.72.72.7
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" + ], + "text/plain": [ + " mean min max\n", + "director_name \n", + "Aaron Schneider 7.1 7.1 7.1\n", + "Aaron Seltzer 2.7 2.7 2.7" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(df\n", + " .groupby(df.director_name)\n", + " .agg(['mean', 'min', 'max'])\n", + " .imdb_score\n", + " .head(2)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meanspreadnunique
director_name
Adam McKay6.9166671.56
Adam Shankman5.9625002.27
\n", + "
" + ], + "text/plain": [ + " mean spread nunique\n", + "director_name \n", + "Adam McKay 6.916667 1.5 6\n", + "Adam Shankman 5.962500 2.2 7" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def spread(series):\n", + " \"\"\"Custom aggregation function.\"\"\"\n", + " return series.max() - series.min()\n", + "\n", + "\n", + "(df\n", + " .groupby(df.director_name)\n", + " .agg(['mean', spread, 'nunique'])\n", + " .imdb_score\n", + " .loc[lambda df:df['nunique'] > 1, :]\n", + " .head(2)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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imdb_scoregross
meanstdmeanmax
countrycontent_rating
AfghanistanPG-137.400000NaN1.127331e+061127331.0
ArgentinaR7.6000000.7937257.230936e+0620167424.0
ArubaR4.800000NaN1.007614e+0710076136.0
AustraliaG6.3000000.7071074.245900e+0766600000.0
PG6.2000001.1575845.703676e+07257756197.0
PG-136.5111110.7440505.468192e+07174635000.0
R6.6000000.8246212.336834e+07153629485.0
Unrated6.300000NaN2.651070e+05265107.0
BelgiumR7.100000NaN1.357042e+061357042.0
BrazilR8.1750000.3593983.385652e+067563397.0
Unrated6.100000NaN2.026200e+0420262.0
CameroonNot Rated7.500000NaN3.263100e+0432631.0
CanadaG2.800000NaN1.114452e+0711144518.0
Not Rated6.4750000.7410581.831962e+05703002.0
PG5.5200001.0232305.192535e+07113006880.0
\n", + "
" + ], + "text/plain": [ + " imdb_score gross \n", + " mean std mean max\n", + "country content_rating \n", + "Afghanistan PG-13 7.400000 NaN 1.127331e+06 1127331.0\n", + "Argentina R 7.600000 0.793725 7.230936e+06 20167424.0\n", + "Aruba R 4.800000 NaN 1.007614e+07 10076136.0\n", + "Australia G 6.300000 0.707107 4.245900e+07 66600000.0\n", + " PG 6.200000 1.157584 5.703676e+07 257756197.0\n", + " PG-13 6.511111 0.744050 5.468192e+07 174635000.0\n", + " R 6.600000 0.824621 2.336834e+07 153629485.0\n", + " Unrated 6.300000 NaN 2.651070e+05 265107.0\n", + "Belgium R 7.100000 NaN 1.357042e+06 1357042.0\n", + "Brazil R 8.175000 0.359398 3.385652e+06 7563397.0\n", + " Unrated 6.100000 NaN 2.026200e+04 20262.0\n", + "Cameroon Not Rated 7.500000 NaN 3.263100e+04 32631.0\n", + "Canada G 2.800000 NaN 1.114452e+07 11144518.0\n", + " Not Rated 6.475000 0.741058 1.831962e+05 703002.0\n", + " PG 5.520000 1.023230 5.192535e+07 113006880.0" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "funcs = {'imdb_score': [pd.Series.mean, pd.Series.std], 'gross': [pd.Series.mean, pd.Series.max]}\n", + "\n", + "df.groupby(['country', 'content_rating']).agg(funcs).head(15)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Data source: https://github.com/highcharts/highcharts/blob/master/samples/data/world-population-history.csv" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "df_world = pd.read_csv(f'data/world_population_history.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "df_world = (df_world\n", + " .drop(columns=['Country Name', 'Country Code', 'Indicator Name', 'Indicator Code'])\n", + " .dropna(axis=1, how='all'))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Data SourceWorld Development Indicators19601961196219631964196519661967...2006200720082009201020112012201320142015
0ArubaABW56225.056695.057032.057360.057715.058055.058386.058726.0...101353.0101453.0101669.0102053.0102577.0103187.0103795.0104341.0104822.0105000.0
1AfghanistanAFG9345868.09533954.09731361.09938414.010152331.010372630.010604346.010854428.0...27294031.028004331.028803167.029708599.030696958.031731688.032758020.033736494.034656032.035530000.0
2AngolaAGO5866061.05980417.06093321.06203299.06309770.06414995.06523791.06642632.0...21759420.022549547.023369131.024218565.025096150.025998340.026920466.027859305.028813463.029784000.0
3AlbaniaALB1711319.01762621.01814135.01864791.01914573.01965598.02022272.02081695.0...2947314.02927519.02913021.02905195.02900401.02895092.02889104.02880703.02876101.02879000.0
4AndorraAND15370.016412.017469.018549.019647.020758.021890.023058.0...83861.084462.084449.083751.082431.080788.079223.078014.077281.077000.0
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5 rows × 58 columns

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Data Source1960196119621963
0Aruba56225.056695.057032.057360.0
1Afghanistan9345868.09533954.09731361.09938414.0
2Angola5866061.05980417.06093321.06203299.0
3Albania1711319.01762621.01814135.01864791.0
4Andorra15370.016412.017469.018549.0
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" + ], + "text/plain": [ + " Data Source 1960 1961 1962 1963\n", + "0 Aruba 56225.0 56695.0 57032.0 57360.0\n", + "1 Afghanistan 9345868.0 9533954.0 9731361.0 9938414.0\n", + "2 Angola 5866061.0 5980417.0 6093321.0 6203299.0\n", + "3 Albania 1711319.0 1762621.0 1814135.0 1864791.0\n", + "4 Andorra 15370.0 16412.0 17469.0 18549.0" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_world.iloc[:5, :5]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CountryYearPopulation
0Aruba1960-01-0156225.0
1Aruba1961-01-0156695.0
2Aruba1962-01-0157032.0
3Aruba1963-01-0157360.0
4Aruba1964-01-0157715.0
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" + ], + "text/plain": [ + " Country Year Population\n", + "0 Aruba 1960-01-01 56225.0\n", + "1 Aruba 1961-01-01 56695.0\n", + "2 Aruba 1962-01-01 57032.0\n", + "3 Aruba 1963-01-01 57360.0\n", + "4 Aruba 1964-01-01 57715.0" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_world_tidy = (df_world\n", + " .set_index(['Data Source'])\n", + " .stack(0)\n", + " .rename('Population')\n", + " .to_frame()\n", + " .reset_index()\n", + " .rename(columns={'level_1':'Year', 'Data Source':'Country'})\n", + " .assign(Year=lambda df:pd.to_datetime(df.Year)))\n", + "\n", + "df_world_tidy.iloc[:5,:5]" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "to_plot = (df_world_tidy\n", + " .set_index(['Country', 'Year'])\n", + " .unstack(level=0)\n", + " .loc[:, (slice(None), ['Norway', 'Sweden'])])" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Return Index with requested level removed\n", + "to_plot.columns = to_plot.columns.droplevel(0)\n", + "\n", + "(to_plot / 10**6).plot(grid=True, figsize=(10, 5));\n", + "plt.ylabel('Population (millions)'); \n", + "plt.ylim([0, 11]); plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (6.4) Pivoting and melting\n", + "\n", + "We'll show how pivoting and meling can help us create data for plotting." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
CountryYearPopulation
0Aruba1960-01-0156225.0
1Aruba1961-01-0156695.0
2Aruba1962-01-0157032.0
\n", + "
" + ], + "text/plain": [ + " Country Year Population\n", + "0 Aruba 1960-01-01 56225.0\n", + "1 Aruba 1961-01-01 56695.0\n", + "2 Aruba 1962-01-01 57032.0" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The tidy data set\n", + "df_world_tidy.head(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `.pivot()` method is more powerful than unstack. Both move rows up to the columns." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CountryAfghanistanAlbaniaAlgeriaAmerican SamoaAndorra
Year
1960-01-019345868.01711319.011690153.021117.015370.0
1961-01-019533954.01762621.011985136.021882.016412.0
1962-01-019731361.01814135.012295970.022698.017469.0
1963-01-019938414.01864791.012626952.023520.018549.0
1964-01-0110152331.01914573.012980267.024321.019647.0
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" + ], + "text/plain": [ + "Country Afghanistan Albania Algeria American Samoa Andorra\n", + "Year \n", + "1960-01-01 9345868.0 1711319.0 11690153.0 21117.0 15370.0\n", + "1961-01-01 9533954.0 1762621.0 11985136.0 21882.0 16412.0\n", + "1962-01-01 9731361.0 1814135.0 12295970.0 22698.0 17469.0\n", + "1963-01-01 9938414.0 1864791.0 12626952.0 23520.0 18549.0\n", + "1964-01-01 10152331.0 1914573.0 12980267.0 24321.0 19647.0" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Demonstrating the pivot method\n", + "# Return reshaped DataFrame organized by given index / column values.\n", + "df_world_pivot = df_world_tidy.pivot(index='Year', columns='Country', values='Population')\n", + "df_world_pivot.iloc[:5, :5]" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "# Drop every country where there are any missing values\n", + "df_world_pivot = df_world_pivot.dropna(how='any', axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CountryAfghanistanAlbaniaAlgeriaAmerican SamoaAndorra
Year
1960-01-019345868.01711319.011690153.021117.015370.0
1961-01-019533954.01762621.011985136.021882.016412.0
1962-01-019731361.01814135.012295970.022698.017469.0
1963-01-019938414.01864791.012626952.023520.018549.0
1964-01-0110152331.01914573.012980267.024321.019647.0
\n", + "
" + ], + "text/plain": [ + "Country Afghanistan Albania Algeria American Samoa Andorra\n", + "Year \n", + "1960-01-01 9345868.0 1711319.0 11690153.0 21117.0 15370.0\n", + "1961-01-01 9533954.0 1762621.0 11985136.0 21882.0 16412.0\n", + "1962-01-01 9731361.0 1814135.0 12295970.0 22698.0 17469.0\n", + "1963-01-01 9938414.0 1864791.0 12626952.0 23520.0 18549.0\n", + "1964-01-01 10152331.0 1914573.0 12980267.0 24321.0 19647.0" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Compute the relative change since 1960\n", + "df_world_rel = (df_world_pivot / df_world_pivot.iloc[0, :])\n", + "df_world_pivot.iloc[:5, :5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `.melt()` method is more powerful than stack. Both move columns up to the index.\n", + "\n", + "> `unstack` and `stack` are inverses. \n", + " `pivot` and `melt` are inverses." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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YearCountryPopulation
01960-01-01Afghanistan1.000000
11961-01-01Afghanistan1.020125
21962-01-01Afghanistan1.041247
31963-01-01Afghanistan1.063402
41964-01-01Afghanistan1.086291
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" + ], + "text/plain": [ + " Year Country Population\n", + "0 1960-01-01 Afghanistan 1.000000\n", + "1 1961-01-01 Afghanistan 1.020125\n", + "2 1962-01-01 Afghanistan 1.041247\n", + "3 1963-01-01 Afghanistan 1.063402\n", + "4 1964-01-01 Afghanistan 1.086291" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_world_rel = df_world_rel.reset_index().melt(id_vars='Year', value_name='Population')\n", + "df_world_rel.iloc[:5, :5]" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "top_n = 5\n", + "countries = (df_world_rel\n", + " .groupby('Country')\n", + " .max()\n", + " .Population\n", + " .nlargest(top_n)\n", + " .index)\n", + "\n", + "(df_world_rel\n", + " .pivot(index='Year', columns='Country', values='Population')\n", + " .loc[:, countries].plot(figsize=(10, 5)))\n", + "plt.legend(bbox_to_anchor=(1,1));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (6.5) Merging" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](https://www.dofactory.com/Images/sql-joins.png)\n", + "\n", + "*Image source is https://www.dofactory.com/sql/join*\n", + "\n", + "> **Tip.** Learning SQL is likely worth your time, see for instance [w3schools.com](https://www.w3schools.com/sql/default.asp) and [sqlzoo.net](https://sqlzoo.net/wiki/SELECT_names)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add a column showing every directors average imdb score." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_imdb_score
director_name
Aaron Schneider7.1
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" + ], + "text/plain": [ + " director_imdb_score\n", + "director_name \n", + "Aaron Schneider 7.1" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "director_means = (df.groupby(df.director_name).mean().round(1)\n", + " .loc[:, ['imdb_score']]\n", + " .rename(columns={'imdb_score':'director_imdb_score'}))\n", + "director_means.head(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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director_namegrossmovie_titlecountrycontent_ratingimdb_scoredirector_imdb_score
0James Cameron760505847.0AvatarUSAPG-137.97.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.17.0
2Sam Mendes200074175.0SpectreUKPG-136.87.5
3Christopher Nolan448130642.0The Dark Knight RisesUSAPG-138.58.4
5Andrew Stanton73058679.0John CarterUSAPG-136.67.7
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" + ], + "text/plain": [ + " director_name gross movie_title \\\n", + "0 James Cameron 760505847.0 Avatar  \n", + "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", + "2 Sam Mendes 200074175.0 Spectre  \n", + "3 Christopher Nolan 448130642.0 The Dark Knight Rises  \n", + "5 Andrew Stanton 73058679.0 John Carter  \n", + "\n", + " country content_rating imdb_score director_imdb_score \n", + "0 USA PG-13 7.9 7.9 \n", + "1 USA PG-13 7.1 7.0 \n", + "2 UK PG-13 6.8 7.5 \n", + "3 USA PG-13 8.5 8.4 \n", + "5 USA PG-13 6.6 7.7 " + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.merge(director_means, how='left', left_on='director_name', right_index=True).head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The inner join, or `merge(how='inner')` can be used if you want the intersection." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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imdb_score_USAimdb_score_Canada
director_name
Adam Shankman6.25.5
Andrzej Bartkowiak5.83.7
Atom Egoyan6.37.0
Bennett Miller7.67.4
Bob Clark2.56.2
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" + ], + "text/plain": [ + " imdb_score_USA imdb_score_Canada\n", + "director_name \n", + "Adam Shankman 6.2 5.5\n", + "Andrzej Bartkowiak 5.8 3.7\n", + "Atom Egoyan 6.3 7.0\n", + "Bennett Miller 7.6 7.4\n", + "Bob Clark 2.5 6.2" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# For every director which has made movies in the USA and Cananda\n", + "# get average imdb scores for both locations\n", + "\n", + "american_directors = (df[df.country == 'USA'].groupby('director_name')\n", + " .mean().imdb_score.to_frame())\n", + "canadian_directors = (df[df.country == 'Canada'].groupby('director_name')\n", + " .mean().imdb_score.to_frame())\n", + "\n", + "(american_directors.merge(canadian_directors, how='inner', \n", + " left_index=True, right_index=True, \n", + " suffixes=('_USA', '_Canada'))\n", + " .round(1)\n", + " .head())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For more information about mergning, see the [Pandas Merging 101](https://stackoverflow.com/questions/53645882/pandas-merging-101/53645883#53645883) question on stackoverflow." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (7) Plotting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (7.1) Built-in `plot()` methods\n", + "\n", + "\n", + "Excellent for creating plots quickly. The downside is less control.\n", + "\n", + "The built in plot options are:\n", + "\n", + "- `line` : line plot (default)\n", + "- `bar` : vertical bar plot\n", + "- `barh` : horizontal bar plot\n", + "- `hist` : histogram\n", + "- `box` : boxplot\n", + "- `kde` : Kernel Density Estimation plot\n", + "- `density` : same as ‘kde’\n", + "- `area` : area plot\n", + "- `pie` : pie plot\n", + "- `scatter` : scatter plot\n", + "- `hexbin` : hexbin plot\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot countries by number of occurences\n", + "(df.country\n", + " .value_counts()\n", + " .head(n=10)\n", + " .sort_values(ascending=True)\n", + " .to_frame()\n", + " .plot.barh(figsize=(10, 5)));" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Ys8S2e4D7I2JiOsv840AAQ4BtIuKpXvqeBEwCaGlpGXv06UfnHH3jah3Syuwls6sdRt1wvsrjfJXH+SpPd/kau+7YKkRT+zo7Oxk+fHi1w6gbA5Wv9vb2eyNi897aeSSzZ68Dg7rZNijd3uVl4AvA7cCNkj4WES9113FEnAOcAzBqo1Ex+ZHJ+UTcBDrGdOB89Z3zVR7nqzzOV3m6y1eM84BPKYVCgba2tmqHUTdqLV9+T2bP5gDrdLNtXeCF7IqIeAzYEVgP+L2kYZUNz8zMzKw2ucjs2Z+AsZLekV0paStg7XT7W6TvxNyV5PnMyyR5tNjMzMyajovMnl0APAnMlHSApE9KOgS4Bvgz8IdSO0VEAdgX2AE4T5L/ZqSZmZk1FReZPYiITuATJCOWPyApKo8BfgPsGBFv9rDv5cAhwHjg5MpHa2ZmZlY7fCu3FxHxDDCxlzYlt0fE/wH/l39UZmZmZrXNRWYNGDZ4GDHFMwv7qlAoeCZmGZyv8jhf5XG+yuN8WTPx7XIzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8vditUOwGDh0oVomqodRt3oGNNB+7T2aodRN5yv8jhf5elLvmJKDFA0ZlZLan4kU9JUSVHi66Zqx2ZmZmZmpdXLSOYrwGdKrDMzMzOzGlQvRebrEXFnXxpKWjkiFlU6IDMzMzPrXs3fLu+JpBXTW+dfl3S6pDnAX9Ntu0i6SdIcSa9KukPSp4r2P1HSc5I2l3SXpIWS7pO0TYljfVnS/ZIWS3pe0m8ljchs31bSzLSPlySdLWl4xZNgZmZmVoPqpshMC8rsV3amzNFACzAe+Ea6bkPgKmBfYA/gLuAPkrYq6no4cD5wVtrudeAKSUMzx56abr8Z+DzwVWABMCzd/glgBvB02seRwOeAn+dy8mZmZmZ1pl5ul48Elhat2x4opN/Pjoh9shsj4vSu7yWtANwCvB84kKTg7LIKcEhEzEzbzgHuBj4G3CRpJEkR2xER38rs97vM9z8Ebo2IcZljPgvcIGlqRPyrvNM1MzMzq2/1UmS+AnyqaN3Dme+vLd5B0ijge8AngXWBrpHPQUVNFwN/yiw/mH62pp/bAENIRjvfJr0lvhXwZUnZfM4E3gTGAm8rMiVNAiYBtLS00DGmo1T3VkLrkFbnqwzOV3mcr/L0JV+FQmFggqkDnZ2dzkcZnK/y1Fq+6qXIfD0i7ilemSnqni9aPwj4PTAUOA54jOT29veAVYu6eSUisi9xey397LpdPjL9fLab2EaSFLDnpF/FRpXaKSKWtR+10aiY/Mjkbrq3Yh1jOnC++s75Ko/zVZ6+5CvG+T2ZXQqFAm1tbdUOo244X+WptXzVS5HZm+LfYO8GNgO2j4hl79OUtHI/+n4p/VwXmFdi+8vp53HAH0psf7ofxzQzMzOra41SZBbrKiaXdK2QtBHwEeDeMvu6neSW+gSSZzPfIiJelXQ3MCYiTupfuGZmZmaNpVGLzAeAZ4AfSzoeWA04AZhdbkcRMVfS94Bp6Yzz60mK2J2BYyPieeBbwI3phPfLgU5gA2An4NsR8Z/lPyUzMzOz+tGQRWZELJa0O3AmSdH3FEmRuQOwcT/6+66kF4HDSV5f9DJwK8lznkREQdK2wFTg1ySTi54gKUjnLO/5mJmZmdWbmi8yI2IqSfFWatvr/HfWePG2u4DNi1b/qqjNcSTPUvbaZ0ScRfKuzO7ivIOkiDUzMzNrejVfZDaDYYOHEVM8+7KvCoWCZ6uWwfkqj/NVHufLzLpTN3/xx8zMzMzqh4tMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy92K1Q7AYOHShWiaqh1G3egY00H7tPZqh1E3nK/yNHO+YkpUOwQzayAVH8mU9HlJN0p6SdJrkp6WdImkj1b62GZmZmZWHRUtMiX9GLgceBo4CPgUcDQwArhN0jsreXwzMzMzq46K3S6XtCtwBHBAREwv2vwrSbsAi5aj/8HAmxHxRv+jNDMzM7NKqORI5hHA3SUKTAAi4pqIeAZA0gqSjpb0qKQlkh6RNCHbXlJB0mWSJkn6D7AYWE/SVEkvStpK0j2SFkm6TdKGktaSdKWkTkkPSfpkUZ/7p23nSnpZ0i2SNi9qMz3td3tJ/5C0IN1n00ybSyXdUnyOkqZJej4tiM3MzMyaRkWKTEkrAlsDN/Zxl58CxwHnADsBVwDnSdq5qN1Hga8C3wZ2AV5J1w9L9/0xMA5YH/gVcDFwG7A7yS37SyUNy/Q3GrgA2AvYB5gNzJS0UdFx1wd+BJyU9r8W8FtJXbN1fg5sK2nDTA4E7A/8OiKW9jEPZmZmZg2hUrfLRwJDgKeyK9PCa1Bm1RvAO0kKxwMi4pfp+pskrQtMAX6fab868KGIeC7TJ8DKwOERcWu6bj3gTGBKRHSk62YDDwDbAtcDRMQJmX5WAGYAWwD7Acu2AWsAH42If2faXgG8G/hXut9TwMQ0ZoB2kiL2/J5TZWZmZtZ4KlVkdo3wFb8P4yiSEcEuhwFLgTeBK9IR0C5/BMZJGpR57vLebIGZ8Rrwp8zyo+nnzSXWvWNZkNJ7gO8B25CMTnYZU9T/rK4CM/Vg+tkK/Csi3pQ0Hdhf0tSICJKC856IuL9EvEiaBEwCaGlpoWNMR6lmVkLrkFbnqwzOV3maOV+FQqHsfTo7O/u1X7NyvsrjfJWn1vJVqSLzRWAJSRGW9SugkH5/d/rZQjK6+QqlrUtyGxvg+W7azI+INzPLr6Wf87pWRMRr6ajnUABJI0hu5z8PHAk8QfKc58+72mTMK1ru6j/b7nzgO0C7pLuBPYDJ3cRLRJxDcoufURuNismPdNvUinSM6cD56jvnqzzNnK8YV/57MguFAm1tbfkH06Ccr/I4X+WptXxVpMiMiNcl3QF8Gjg+s/550kLxv48zMhd4neR5yzd5uxeyXecY5tYkRfD2EfGvrpWSVutPZxExS9JNJCOYG5I873pxDnGamZmZ1Z1K/sWf04ArJY2PiF/10O5mkpHM1SJiRgXjKbZy+rmka4WkbUieo7y3n33+AjgP2BS4MiKKR0DNzMzMmkLFisyIuErSacB0Se3ANSS30UcC26fNOiPiYUn/B1wi6WTgHpLb0JsCYyLioAqFeCfQCZybHrcVmEoyC72/rgR+BnwYOGZ5AzQzMzOrVxX92+UR8Q1JM4GvkYzyjQDmAHcAn42I69OmhwCPAAeTzOp+lWRyzS8qGNvzkvYCOoCrgH8DXwG+tRx9LpF0PfAJ4KZcAjUzMzOrQxUtMgEi4gqS1/301CZIbq+f1kObtm7WTyUZgcyuK/DfGe7Z9SpavgG4oajZdUVtJpboZ1ap/tPZ8e3AeUUTkczMzMyaSsWLzGYgaSXgAyQvdB8JnF3O/sMGDyOm5DmnqbEVCoV+zYJtVs5XeZwvM7N8uMjMx3rAX0hmwn85Imb30t7MzMysobnIzEF3t8/NzMzMmlVF/na5mZmZmTU3F5lmZmZmljsXmWZmZmaWOxeZZmZmZpY7F5lmZmZmljsXmWZmZmaWOxeZZmZmZpY7F5lmZmZmljsXmWZmZmaWOxeZZmZmZpY7F5lmZmZmljv/7fIasHDpQjTNf/q8rzrGdNA+rb3aYdQN56s8jZivmBLVDsHMmlDNjWRK2l3SzZLmSVoi6RFJJ0pqqXZsXSR1SJpV7TjMzMzMalVNFZmSTgEuBR4DxgOfBn4M7AKcW8XQzMzMzKwMNXO7XNIuwJHAgRFxXmbTrZLOISk4zczMzKwO1NJI5jeA+4oKTAAi4o2IuB5A0g8k/VNSp6TZki6UtE62vaRZ6S3tb6RtXpZ0iaTVM21WkXSGpIclLZT0uKQzJa1a1Nfqki6StEDSs5KOLY5P0rqSzpP0mKRFmVv8K+WWHTMzM7M6UhMjmZIGA9sAp/Sh+VrA94BngDWBo4CbJb0/It7ItPsC8A9gEtAKnJru97V0+zBgEHAsMAcYlX5/KbBDpp/zgTbgCOA5YDLwTuD1TJsWYC7JSOzLwBhgahrfl/twTmZmZmYNRRHVn3WYjkQ+C3wlIs4uY79BwDrAbGDbiJiZrp8FvAG8OyJeT9edBnwxItbppq8Vga2A24ANIuJJSZsC96f7/SZtNxx4Eng1Ikb30NcXgPOAVSPitRJtJpEUwLS0tIw9+vSj+3raTa91SCuzl8yudhh1w/kqTyPma+y6YyvWd2dnJ8OHD69Y/43G+SqP81WegcpXe3v7vRGxeW/tamIkM6PXilfSjsB3gE2B7K3tMcDMzPItXQVm6kFgLUkrdRV9ksaTjD6+C1ilqK8ngS3S5auXBRjRKWkGSUHaFZOAr5MUjRsCQzN9rQ88+rYTjTgHOAdg1EajYvIjk3s7dUt1jOnA+eo756s8jZivGFe5wYRCoUBbW1vF+m80zld5nK/y1Fq+auWZzJeAJSQFWbckbUFS8M0mmX2+NfCRdPPQoubzipZfAwSslPa1G3ABcAewV9rPbkV9rQPMj4hFRX29ULR8BMmt/iuAXYEtgUO6icvMzMys4dXESGZELJV0O8mzkMf10HQ3kucn9470Pr+kDfp52L2AuyKi6xlNJG1b1OY5YISklYsKzbVK9HVpRCybFCTpvf2My8zMzKzu1cpIJsBpwOaSJhRvkLSCpM8AKwNL460Pku7bz+OtTDJ6mlXc193p5+cysQwHtu9HX2ZmZmZNoyZGMgEi4hpJpwK/kPRR4CqgE9gE+Aowi+SF7Eekk3iuIZmRvl8/DzkDODN9JdFdwGeB7YpiekDS1cBZ6auNngW+CSws0dfhku4C/kNSYG7cz7jMzMzM6l7NFJkAEXGUpD8DhwIXkYwQziJ5DrMjIp6T9G3gMOBgkucpdwYe6cfhzgY2IpmwM5SkUNwHuLOo3UTgLJKR1k7gTJIRzj0zbU4geV3Rieny74DDSQphMzMzs6ZTU0UmQERcDlzew/aTgZOLVquozegS+00HpmeW3yB552XxNNLivl4GvlgilMmZNp3AASXaqMS6txk2eBgxpfqvkqoXhUKhorNlG43zVR7ny8wsH7X0TKaZmZmZNQgXmWZmZmaWOxeZZmZmZpY7F5lmZmZmljsXmWZmZmaWOxeZZmZmZpY7F5lmZmZmljsXmWZmZmaWOxeZZmZmZpY7F5lmZmZmljsXmWZmZmaWOxeZZmZmZpY7F5lmZmZmlrsVqx2AwcKlC9E0VTuMutExpoP2ae3VDqNuOF/l6W++YkpUIBozs/o1YCOZSjwuKSRtXIH+V5I0VdIHc+53uqR7MssT03MYnudxzMzMzBrJQN4u3xoYnX7/xQr0vxIwBci1yCzhWpJzWVjh45iZmZnVrYEsMscBC4C70u+rRtLK/d03IuZExJ0R8WaeMZmZmZk1kgEpMiUNAvYCrgbOA94rabPM9qmSXiyxX0g6NLP8OUn3Slog6WVJd0naNt08P/08P90vJI1Ov0LSvpIukDQPuCbtb39Jt0mam/Z3i6TNezmXt90ul/QDSf+U1ClptqQLJa3Tz3SZmZmZ1b2BGsn8JLA2cAlwGbCUMkczJb0z3fdmYBdgX+D3wBqZYwCcSHI7e2vg2UwXHSSF6F7A99J1o4EL0nX7ALOBmZI2Kic2YK20z52AI4CNgJvT4trMzMys6Sii8jMiJZ0H7AasHRGvSboWeC+wUUSEpKnAoRHRUrRfAIdFxBmS9gTOjoiR3RxjOEkReUBETM+sHw08DlwZEbv1EOMKJEX3/cBFEXFCun468L6I2DxdngicD4yIiM4S/QwC1iEpWLeNiJndHG8SMAmgpaVl7NGnH91daFakdUgrs5fMrnYYdcP5Kk9/8zV23bEViKb2dXZ2Mny450H2lfNVHuerPAOVr/b29nu76qKeVPwVRpKGkBSYV0TEa+nqi4FfAR8B7uhjV/8EVpP0S+BC4PaIWFBGKNeWiO09JCOQ25CMRnYZU0a/SNqV8xcmAAAcEklEQVQR+A6wKbBqUT8li8yIOAc4B2DURqNi8iOTyzlkU+sY04Hz1XfOV3n6m68Y15yvMCoUCrS1tVU7jLrhfJXH+SpPreVrIG6X7wisDlwnaXVJqwMFYAll3DKPiIeBXUluRV8HvCjpIklr9rGL57MLkkYANwKjgCOBjwNbAH8HhvY1LklbkDxrOhsYT3Kb/iPp5j73Y2ZmZtZIBuJl7F2F5KUltn1B0jeAxSSvIFpG0v8UN46Ia4FrJa1G8vzjacBP6dsrkYqHGbYGWoHtI+JfmeOu1oe+snYD5gB7R/rsgaQNyuzDzMzMrKFUtMhMn5PcmeT2+DlFmz8EnAq0k4wCjpD0joh4Ot3+6e76jYhXgIvSmeVbp6u7bsX3dfSw6zVGSzLxbkMyGejePvbR1c/SeOvDrfuWsb+ZmZlZw6n0SOauwDDgJxFxV3aDpNuBY0lGOr8NLALOk3QKsCHwlaL2XyYpKG8AngHeRTIr/AKAdELR4ySjo/eTjI7+o4fY7gQ6gXMlnUwyqjkVeLqHfUqZARwh6TSSVyNtA+xXZh9mZmZmDaXSz2SOA/5dXGACRMRS4LfA7iSzwvcgKfSuJCnS9ina5R/AmiSjnzcCxwHnkhSoXb4CtAA3AXcD63UXWEQ8T1KkrgNcRfLqoa8Aj5ZzghFxXRrDHiTPZm5LMnprZmZm1rQqOpIZET0WWxHxNeBr6eL16VeWMm3vIHkOs6f+bgQ2K7FJJdYRETeQjIxmXVfUZmLR8nRgetG6k4GT+3LMUoYNHkZMac6Zqf1RKBSadiZvfzhf5XG+zMzyMZB/VtLMzMzMmoSLTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy52LTDMzMzPLnYtMMzMzM8udi0wzMzMzy92K1Q7AYOHShWiaqh1G3egY00H7tPZqh1E3mjlfMSWqHYKZWdNqmJFMSRMl3StpvqSXJf1V0qkVOlabpJD0vkr0b2ZmZlbvGqLIlHQM8HPgD8DuwP7AVcDnKnTI+4Ctgf9UqH8zMzOzutYot8sPBc6OiP/NrLtG0rRKHCwiXgXurETfZmZmZo2gIUYygdWB54pXRsSyB7IkjU5vce8j6VfpbfUXJE3J7iNpE0mXSHpK0kJJD0g6QtIKmTZvu12eLn9d0vckzUn7PlPSkAqds5mZmVnNapSRzPuAwyQ9Cfw+Il7qoe2PgN8DewKfAKZIejEizky3vwN4GLgQmA98EJgGrAx8v5c4jgJuBvYDNkvbPwGc3J+TMjMzM6tXjVJkHgJcCUwHQtJDwOVAR3prO+uBiPhy+v0fJK0F/K+ksyLizYj4I/BHAEkCbgOGAQfTe5E5KyImZvr+KMkzoi4yzczMrKkoc0e5rqW3pT8N7AB8EngP8G/gwxHRKWk08DjwtYg4K7PfjsB1wAYR8aSkocAxwL7A+sDgzGEGR8TrktqAW4D3R8T9aT8BfCciTsz0/T1g/4hoLRHvJGASQEtLy9ijTz86lzw0g9YhrcxeMrvaYdSNZs7X2HXHlr1PZ2cnw4cPr0A0jcn5Ko/zVR7nqzwDla/29vZ7I2Lz3to1ykgmEbEEuCb9QtKBJDPODwR+kmn6QtGuXcvrAk8CPwQOIrlFfh8wD9gVOA4YCnT2EMa8ouXX0n1KxXsOcA7AqI1GxeRHJvfQrWV1jOnA+eq7Zs5XjCv/H9GFQoG2trb8g2lQzld5nK/yOF/lqbV8NcrEn7eJiF8Ac4FNijat1c3ys+nnXsBPI+LkiLgpIu4BXq9cpGZmZmaNpyGKzPS5yuJ1awKrAc8XbdqtaHl3kgKz637iysCSTD+DgC/mFqyZmZlZE2iU2+X/lHQVcCPJ7e8NgMnAQuCXRW03lXQ2ycSgT5DcTv96RLyZbp8BHCLpUZKR0EMAv4bIzMzMrAyNUmSeQPLc5OnAGiTvzPwzsHdEPF7U9lvAziRF5mLgu8AZme2HAf8HnAksIilSryB9ftLMzMzMetcQRWb6jssze22YeCUixvXQ1/O8/ZY6wLmZNgVARfupeIeImApM7S2gYYOHEVMaY5b/QCgUCv2a0NGsnC8zM6uGhngm08zMzMxqi4tMMzMzM8tdQ9wu74uImEXRLW4zMzMzqwyPZJqZmZlZ7lxkmpmZmVnuXGSamZmZWe5cZJqZmZlZ7lxkmpmZmVnuXGSamZmZWe5cZJqZmZlZ7lxkmpmZmVnuXGSamZmZWe5cZJqZmZlZ7prmz0rWsoVLF6Jp/ouXfdUxpoP2ae3VDqNuDGS+YkoMyHHMzKz29TqSKWmqpBe72TZd0j35h7V8JIWkQ4vWbSnpFUk3SBpSrdjMzMzMmkFT3C6X9EHgBuBeYLeIWFLlkMzMzMwaWsMXmZI2BWYADwK7RMSiKodkZmZm1vByLzIlfVDSHyUtlPSypAslrZ3ZPjq9nf0FSWent7BnS5omaYWivvaS9G9JiyTdIulD6b4T+xjLGOAm4DHgsxGxoFZjNTMzM2skfS4yJa1Y/AWoqM2aQAEYBuwDHAZsC8yQtFJRlycDncCewK+B49Pvu/raHLgEuA/YDbga+E0Z57Yh8EfgWWCHiHi1hmM1MzMzayh9nV0+EljazbZ7M98flX4uK+okPQLcBewBXJxpOzMiutrPkPQZYHfgt+m6bwMPAV+MiABukDQY+GEfYz4SWARsERHzSmyvpVjNzMzMGkpfi8xXgE+VWD8FWDezvCVwY3bUMCL+ImkW8DHeWrjdWNTXg8D6meUtgIvToq3L1fS9cLsJ+CTwA0kHFPVT9VglTQImAbS0tNAxpqNPJ2XQOqTV+SrDQOarUCgMyHEqqbOzsyHOY6A4X+VxvsrjfJWn1vLV1yLz9Yh426uKJL3EW4vMdYEHSuz/PLBG0bri0cXXgKGZ5XWAOUVtipd7chVwBXAm8ALwraLtVY01Is4BzgEYtdGomPzI5J6aW0bHmA6cr74byHzFuPp/T2ahUKCtra3aYdQN56s8zld5nK/y1Fq+8p748yywVon1awNzy+zrOWDNonXFyz2KiJ8B3wW+KenIos01FauZmZlZI8m7yLwL2EHSiK4VkrYARgO3ldnX3cAukrKTiz5XbkARcTxwNtAhab9ajtXMzMysUeRdZJ6afv5B0q6S9gV+B/wTuLzMvn4IvAe4RNJnJH0DODjd9maZfX0NuBI4L520U8uxmpmZmdW9XIvMiJgDtAOLSSbOnAn8Cdg+Il4rs697gHHAWJICcQ/gq+nmV7vbr5u+3kz7+jNwmaStajVWMzMzs0bQ68SfiJgKTO1m28QS6/5KMqu7u/5mUfR+zR76+i3/fU0Qmdvdf+8l5lL9LwHaai1WMzMzs0bU19nlVSHpLJI/Cfky8GHgOODaiHi8qoGVsDyxDhs8jJhS/7NyB0qhUGiIWcwDxfkyM7NqqOkik+Ql8D9LP18i+Ss6xa8iqhX1FKuZmZlZRdV0kRkRX6h2DH1VT7GamZmZVVres8vNzMzMzFxkmpmZmVn+XGSamZmZWe5cZJqZmZlZ7lxkmpmZmVnuXGSamZmZWe5cZJqZmZlZ7lxkmpmZmVnuXGSamZmZWe5cZJqZmZlZ7mr6z0o2i4VLF6JpqnYYdaNjTAft09qrHUbdGMh8xZQYkOOYmVnta6iRTEm7S7pZ0jxJSyQ9IulESS2SRksKSTv30sdUSS8OVMxmZmZmjahhikxJpwCXAo8B44FPAz8GdgHOLaOrnwM75B6gmZmZWRNpiNvlknYBjgQOjIjzMptulXQOScHZJxExG5idc4hmZmZmTaVRRjK/AdxXVGACEBFvRMT1mVXDJJ0t6RVJsyVNk7QsD8W3yyW1pbfZ2yRdKqlT0mOSvpY9jqStJV0t6RlJCyT9TdK+lThZMzMzs1pX90WmpMHANsANfdzlZKAT2BP4NXB8+n1vzgX+DuwGFIAzJW2Z2b4BcDtwEMkt+suB8yWN62NcZmZmZg2jEW6XjwSGAE/2sf3MiDgq/X6GpM8AuwO/7WW/iyPiRABJBZJCcnfgLwARcUlXQ0kCZgKtwMHAxX2MzczMzKwhNEKR2aWv7065sWj5QWD9cvaLiKWS/k1SRAIg6X+AacCuwDuAQemmp0t1JmkSMAmgpaWFjjEdfQzfWoe0Ol9lGMh8FQqFATlOJXV2djbEeQwU56s8zld5nK/y1Fq+GqHIfAlYQt8KRYB5RcuvAUNz2G868BHguySF66vAV0mKzreJiHOAcwBGbTQqJj8yuQ8hGCTvfXS++m4g8xXj6v89mYVCgba2tmqHUTecr/I4X+VxvspTa/mq+yIzHVW8neS1Q8dVIwZJQ4GdgEMj4v8y6+v+mVczMzOz/miUIug0YHNJE4o3SFohfe6ykoaQ3B5fkjnuCOBzFT6umZmZWU2q+5FMgIi4RtKpwC8kfRS4imQG+SbAV4BZJK85qtTxX5F0N3C8pFeBN4GjgVeAVSt1XDMzM7Na1RBFJkBEHCXpz8ChwEXAyiTF5dVAB3177nJ57EPyjOUFJM+JngEMS+MxMzMzayoNU2QCRMTlJO+n7I5K7DOxaHkqMDWzXOhmv7ai5UeBT5Y45tQS68zMzMwaWkMVmfVq2OBhxJT6n5U7UAqFQkPMYh4ozpeZmVVDo0z8MTMzM7Ma4iLTzMzMzHLnItPMzMzMcuci08zMzMxy5yLTzMzMzHLnItPMzMzMcuci08zMzMxy5yLTzMzMzHLnItPMzMzMcuci08zMzMxy5z8raWZmZk1n6dKlzJ49m8WLF1c7lNysttpqPPTQQ7n1N3ToUFpbWxk8eHC/9neRaWZmZk1n9uzZjBgxgtGjRyOp2uHkYv78+YwYMSKXviKCl156idmzZ7Phhhv2qw8XmTVg4dKFaFpjXOADoWNMB+3T2qsdRt0YyHzFlBiQ45iZLa/Fixc3VIGZN0mMHDmSOXPm9LuPhngmU9JUSS9WOw4zMzOrHy4we7a8+WmIItPMzMzM/uu0005j4cKFVY3Bt8vNzMys6eX92Fq1Hx867bTT2G+//Rg2bNjbtr3xxhsMGjSo4jE03EimpFUknSHpYUkLJT0u6UxJqxa1C0lHSvqJpLmS5kn6qaSVMm3WlXSepMckLZL0iKQTi9qMTvv6gqSzJb0iabakaZIaLr9mZmaWjwsuuIDNNtuMD3zgA4wfP54nnniC7bbbjs0224ztttuOJ598EoCJEydy2WWXLdtv+PDhABQKBdra2thzzz3ZZJNNOPDAA4kITj/9dJ555hna29tpb29fts/xxx/PVlttxYknnshuu+22rL8ZM2aw++67535+jTiSOQwYBBwLzAFGpd9fCuxQ1PYo4E5gX2BT4CRgMfDNdHsLMBc4EngZGANMBdYEvlzU18nA5cCewHbA8cADwG/zOjEzMzNrDA888AAnnXQSt99+Oy0tLcydO5cJEyaw//77M2HCBM477zwOP/xwrrzyyh77+etf/8oDDzzAeuutx0c+8hFuv/12Dj/8cE499VRuueUWWlpaAFiwYAHve9/7OOGEE4gI3vOe9zBnzhzWXHNNzj//fA444IDcz7HhRtoiYk5EfDUiLouIW4FLgIOAT0tav6j5fGCviLg+IjqAE4BDJK2R9vXPiJgcEVemfZ1PUoBOyI5mpmZGxFERMSMijgb+DuT/zwIzMzOrezfffDN77rnnsiJwjTXW4I477mCfffYBYPz48dx222299rPlllvS2trKCiuswGabbcasWbNKths0aBB77LEHkEzoGT9+PL/+9a+ZN28ed9xxBzvuuGM+J5bRiCOZSBpPMvr4LmCVzKYxwJOZ5asi4s3M8u+AE4H3ATOVTKv6OjAJ2BAYmmm7PvBoZvnGojAeTNt0F+OktF9aWlroGNPR+4kZAK1DWp2vMgxkvgqFwoAcp5I6Ozsb4jwGivNVHuerPJXM12qrrcb8+fMr0jfQa9+LFi3itddee0u7iGD+/PkMHjyYpUuXLusnIliwYMGy77v2W7hwIYMGDVrWhyQ6OzuXtevs7GTIkCFA8mL17ESgvfbai7333huAXXfdlUWLFpWMc/Hixf3+GTRckSlpN+AC4Czgf0lud68LXMFbi0SAF7pZXjf9PALoAH4A3Epyy3wL4MwSfc0rWn6tRJtlIuIc4ByAURuNismPTO7ptCyjY0wHzlffDWS+Ylz9vyez6xkn6xvnqzzOV3kqma+HHnootxeXl9Jb3zvttBO77bYbRx99NCNHjmTu3Ll89KMf5dprr2X8+PFMnz6dj3/844wYMYJ3vetdPPjgg0yYMIErr7ySpUuXMmLECIYNG8aKK6647FiSGDp0KCNGjGDVVVclIt4SR/H3ra2tdHR0MGPGjG7jHTp0KB/60If6lYOGKzKBvYC7IuJrXSskbdtN27W6WX4209elEXFspq/35hWomZmZNadNN92UY489lm233ZZBgwbxoQ99iNNPP50vfelL/OhHP1r2rCTAwQcfzK677sqWW27JdtttxyqrrNJL7zBp0iR23HFH1l13XW655ZaSbfbdd1/mzJnDe99bmdKmEYvMlYElRev27abtrpKOydwy3x1YBNzfj77MzMysTlXjlUMTJkxgwoQJb1l38803v63d2muvzZ133rls+fvf/z4AbW1tbxnpPeWUU5aNSB522GEcdthhy7Z1dna+rd/bbruNgw8+eLnOoSeNVGR2XR0zgDMlHQvcBXyWZLZ3KSOASyWdSzK7/HjgjIiYm+nrcEl3Af8hKTA3rlD8ZmZmZgNi7NixrLLKKpxyyikVO0ajFJkrkzwDCXA2sBHJhJ2hJIXiPiSvKip2Str2YpKZ9j8neY6zywkkrys6MV3+HXA4cE2+4ZuZmZkNnHvvvbfix2iUIvOdpLPGI+INYHL6lVXqVf6vRcShwKGlOo2ITqDUi6OUaTOrVN8RMbEPcZuZmZk1pLouMiVtCrQDOwNTqhxOvw0bPKzqf36qnhQKhYaYxTxQnC8zs9IiguRthVZKxPL9v6Oui0zgDJJRzJ8Ap1Y5FjMzM6sTQ4cO5aWXXmLkyJEuNEuICF566SWGDu32bYy9qusiMyLal2NfX1FmZmZNqrW1ldmzZzNnzpxqh5KbxYsXL1dRWGzo0KG0trb2e/+6LjLNzMzM+mPw4MFsuOGG1Q4jV4VCod8vTq+Ehvvb5WZmZmZWfS4yzczMzCx3LjLNzMzMLHda3unptvwkzQcernYcdaQFeLHaQdQR56s8zld5nK/yOF/lcb7KM1D52iAi1uytkSf+1IaHI2LzagdRLyTd43z1nfNVHuerPM5XeZyv8jhf5am1fPl2uZmZmZnlzkWmmZmZmeXORWZtOKfaAdQZ56s8zld5nK/yOF/lcb7K43yVp6by5Yk/ZmZmZpY7j2SamZmZWe5cZFaQpPdK+qOkhZKekXSCpEF92G81SedLelnSK5IulDRyIGKupv7kS9JoSVHi65KBirtaJG0s6WxJf5f0hqRCH/dr1uur7Hw16/UlaS9JV0t6WlKnpHsljevDfkMknSLpBUkLJF0raXTlI66u5chXqWvrzoGIuZok7Snpz5JekrRY0sOSjpO0Ui/7NevvrrLzVSu/u/wKowqR9D/ATcCDwK7AO4FTSAr743rZ/TfAu4GDgDeBHwJXAh+vVLzVtpz5ApgM3J5Zbob3qm0KfBa4E+jxl3ORpru+Uv3NFzTf9XUk8DjwDZJz/SxwkaSWiPhpD/udDuyZ7jcHmArMkPT+iFhc2ZCrqr/5guT33GWZ5fmVCbGmjARuAX4EzAO2JLlW1gEO7WG/Zv3d1d98QbV/d0WEvyrwBRwDvAysmln3LWBhdl2J/bYGAvhEZt2W6bpPVfu8ajBfo9Pc7Fztc6hCzlbIfH8ZUOjDPk15fS1Hvpry+gJaSqy7CHi8h31agdeB/TPr3gG8BhxU7XOqtXylbQI4tNrx18IXcBJJAaVutjft765+5qsmfnf5dnnl7Aj8ISJezay7BFgZ2LaX/Z6PiJldKyLiLyT/St6xEoHWiP7mq2lFxJv92K1Zr6/+5qspRUSp0Y6/Amv1sNun08/fZfp5GriNxr+2+pMve6uX6PkOQ9P+7upGb/mqCS4yK2cT4F/ZFRHxJMnI3Cbl7Jd6qJf96l1/89Xl/PQ5u2clnSpp5UoE2QCa9fpaXr6+YBuSx1m6swkwOyI6i9Y367XVW766TJX0uqQXJZ0naY1KB1YrJA2SNEzSx4DDgbMiHYYroel/d5WZry5V/d3lZzIr539IhrKLvZxu689+G+UQV63qb76WAGcCNwKvAm3At0me6dw13xAbQrNeX/3l6wuQtB3J+X6ph2b9/W+44fQxXwC/BK4heX51c+A7wAckbRkRb1Q2ypqwABiSfn8B8M0e2vp3V3n5qonfXS4yK6vUvzDUzfo89qt3ZZ93RDzLWx98Lkh6HviZpA9GxN9yjrERNOv1VTZfX8ksVZLnC6+KiOm9NG/6a6ucfEXExMziTEkPAdcBu5BMaGl02wDDSJ6tPB44A/haD+2b/frqc75q5XeXb5dXzsvA6iXWr0bpf431tt/qvexX7/qbr1K6Zmp+eLkiakzNen3lqWmur/TW7fXAk8B+vTRv+murzHyVcgPQSRNcWwARcV9E3BYRp5Lc/v2qpHd207zpr68y81XKgP/ucpFZOf+i6DkRSaOAVSj9XEm3+6W6ex6lUfQ3X6VE0af9V7NeX3lqiutL0jDg9ySTC3aKiAW97PIvYJSkVYrWN8W11Y98vU3m+bqGvra6cV/6uWE32/276616y1cpA359ucisnOuBHSSNyKzbG1gE3NrLfuukD/YCIGlzkmdOrq9EoDWiv/kqZc/08948AmswzXp95anhry9JKwKXAu8CdoyIF/qw243p526ZftYjeYdhQ19b/cxXqX4+Awynga+tHnw0/Xy8m+3+3fVWveWrlAH/3eW/XV4h6cvFHwTuJ3lh7EbAqcBpEXFcpt2jwK0RcWBm3Q3AGJKXqHa9cPaFiGjYF872N1+SpgIjSF42+yrwCZKHoa+LiD0G8hwGWjpy8tl08ShgVWBKunxdRCz09fVf/clXs15fks4BDga+DvylaPNfI2KJpD8CRMR2mf3O5v/bu2OUiKEgAMN/ELFU8AJra2lp6xFs9gTbWXkDt/cK7iEsF/EAYmexYCFsYWWhaCUSi3mNURDjsAnZ/4PXhKR4QxiGl/cmcMzXZuy7wKCbsbeJV1VVE+Kwz5xokH1A/HhiARwO+eBPyUFz4A74IAqmU+CyrutxucfcVbSJV29yV5dNOoc+gH3giliNewSmwEbjngdg1ri2A1wQ+0xeiE3k35r9Dm20iRcwBm6AZ6Lp8z1wBmx1PZ8VxGtEfPb4aYx8v/4fr3V9v0ocfovVNY2G9sTJ13OiwHwjDrHsdT2fPsYLOCIKgCfgHVgSf0za7no+K4jXlFhQeC156BY4ATYbMZ01nlvX3PXnePUld7mSKUmSpHTuyZQkSVI6i0xJkiSls8iUJElSOotMSZIkpbPIlCRJUjqLTEmSJKWzyJQkSVI6i0xJkiSls8iUJElSuk/ZGrofsMiQswAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "(df.country\n", + " .value_counts()\n", + " .head(n=10)\n", + " .apply(np.log10)\n", + " .sort_values(ascending=True)\n", + " .to_frame()\n", + " .plot.barh(grid=True, color='green', fontsize=15, \n", + " title='Number of movies (log) per country', figsize=(10, 5)));" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "countries = set(['Norway', 'Sweden', 'Denmark'])\n", + "df_world_pivot.loc[:, countries].plot(linewidth=3, title='Population growth', \n", + " fontsize=14, figsize=(10, 5))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (7.2) Using matplotlib\n", + "\n", + "Greater control. Allows creating of publication-quality plots. \n", + "Does require more code and knowledge of matplotlib." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "\n", + "ax = (df_world_pivot.loc[:, countries] / 10**6).plot(ax=ax, lw=3, zorder=50)\n", + "\n", + "ax.set_title('Population growth', fontsize=17)\n", + "ax.legend(fontsize=14, loc='upper left')\n", + "ax.tick_params(axis='both', which='both', labelsize=14)\n", + "ax.set_ylabel('Population (millions)', fontsize=14)\n", + "ax.set_xlabel(ax.get_xlabel(), fontsize=14)\n", + "ax.grid(True, zorder=-50, ls='--')\n", + "ax.set_ylim([3, 11]);\n", + "\n", + "#plt.savefig('my_figure.pdf')" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "\n", + "# Compute kernel density estimates\n", + "from KDEpy import FFTKDE\n", + "data = df[['imdb_score', 'gross']].dropna(how='any')\n", + "\n", + "kde = FFTKDE(bw='ISJ', kernel='gaussian')\n", + "\n", + "x, y = kde.fit(data.imdb_score.to_numpy()).evaluate()\n", + "ax.plot(x, y, label='imdb_score', lw=2)\n", + "\n", + "y = kde.fit(data.imdb_score.to_numpy(), weights=data.gross.to_numpy()).evaluate(x)\n", + "ax.plot(x, y, label='imdb_score weighted by gross', lw=2)\n", + "\n", + "ax.set_title('Score distribution', fontsize=17)\n", + "ax.legend(fontsize=14, loc='upper left')\n", + "ax.tick_params(axis='x', which='both', labelsize=14)\n", + "ax.set_yticklabels([])\n", + "ax.set_xlabel('Score', fontsize=14)\n", + "ax.grid(True, zorder=-50, ls='--')\n", + "ax.set_xlim([0, 10]);\n", + "\n", + "#plt.savefig('my_figure.pdf')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (8) Time series manipulations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (8.1) `.dt` accessor\n", + "\n", + "Let's load a data set showing the popularity of the search words `python pandas`, `sas enterprise guide` and `microsoft excel` over the last 5 years. The data was fetched from Google Trends." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Weekpython pandas: (Worldwide)sas enterprise guide: (Worldwide)microsoft excel: (Worldwide)
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" + ], + "text/plain": [ + " Week python pandas: (Worldwide) sas enterprise guide: (Worldwide) \\\n", + "0 2013-12-22 2 1 \n", + "1 2013-12-29 2 1 \n", + "\n", + " microsoft excel: (Worldwide) \n", + "0 53 \n", + "1 62 " + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_trends = pd.read_csv(r'data/google_trends.csv')\n", + "df_trends.head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "# Some values are assigned `<1`, we set these to zero\n", + "for col in df_trends.columns:\n", + " if df_trends[col].dtype != object:\n", + " continue\n", + " try:\n", + " df_trends[col] = np.where(df_trends[col] == '<1', 0, df_trends[col])\n", + " df_trends[col] = df_trends[col].apply(np.int)\n", + " except:\n", + " pass\n", + "\n", + " \n", + "# Change column names, set the 'Week' column to datetime, and use it as index\n", + "df_trends.columns = [c.split(':')[0] if ':' in c else c for c in df_trends.columns]\n", + "df_trends['Date'] = pd.to_datetime(df_trends['Week'])\n", + "df_trends = df_trends.set_index('Date').drop(columns='Week')" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "ax = df_trends.plot(ax=ax, lw=3, fontsize=16)\n", + "ax.set_xlabel('Date', fontsize=16); ax.set_yticks([]);\n", + "fig.savefig('pandas_vs_excel_vs_sas.png', dpi=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "(df_trends\n", + " .assign(week_of_year=lambda df: df.index.to_series().dt.week)\n", + " .groupby('week_of_year')\n", + " .mean()\n", + ".plot(figsize=(10, 5)))" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "(df_trends\n", + " .assign(month=lambda df: df.index.to_series().dt.month)\n", + " .groupby('month')\n", + " .mean()\n", + ".plot(figsize=(10, 5)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (8.2) Rolling window functions" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "window = 48\n", + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "ax = df_trends.plot(legend=False, lw=1, ax=ax);\n", + "df_trends.rolling(window, win_type='triang', center=True).mean().plot(ax=ax, lw=3);" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "window = 12\n", + "\n", + "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']\n", + "\n", + "for column, color in zip(df_trends.columns, colors):\n", + " ax = df_trends[column].plot(ax=ax, lw=1, color=color, alpha=0.5);\n", + " avg = df_trends[column].rolling(window, center=True).mean()\n", + " std = df_trends[column].rolling(window, center=True).agg(pd.Series.std)\n", + " ax = avg.plot(ax=ax, lw=3, color=color, alpha=1);\n", + " ax = (avg + std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');\n", + " ax = (avg - std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (8.3) Resampling" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ax = df_trends.resample('d').pad().plot(figsize=(10, 5))\n", + "df_trends.resample('M').mean().plot(ax=ax);" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "window = 12\n", + "\n", + "agg_func = lambda ser: ser.max() - ser.min()\n", + "\n", + "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']\n", + "\n", + "for column, color in zip(df_trends.columns, colors):\n", + " ax = df_trends[column].plot(ax=ax, lw=1, color=color, alpha=0.5);\n", + " avg = df_trends[column].rolling(window, center=True).mean()\n", + " std = df_trends[column].rolling(window, center=True).agg(agg_func)\n", + " ax = avg.plot(ax=ax, lw=3, color=color, alpha=1);\n", + " ax = (avg + std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');\n", + " ax = (avg - std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (9) Modeling and Machine Learning" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "pd.set_option('display.max_rows', 2**6)\n", + "pd.set_option('display.max_columns', 2**6)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (9.1) Dummy variables for categorical data" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loaded data of size (5043, 6) into memory.\n" + ] + } + ], + "source": [ + "cols_to_use = ['movie_title', 'duration', 'genres', 'content_rating', 'budget', 'gross']\n", + "df_model = pd.read_csv(r'data/movie_metadata.csv', sep=',', usecols=cols_to_use)\n", + "print(f'Loaded data of size {df_model.shape} into memory.')" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3840, 6)" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Drop any row with missing information\n", + "df_model = df_model.dropna(how='any')\n", + "df_model.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " duration gross movie_title \\\n", + "0 178.0 760505847.0 Avatar  \n", + "1 169.0 309404152.0 Pirates of the Caribbean: At World's End  \n", + "\n", + " budget Approved G GP M NC-17 Not Rated PG PG-13 Passed R \\\n", + "0 237000000.0 0 0 0 0 0 0 0 1 0 0 \n", + "1 300000000.0 0 0 0 0 0 0 0 1 0 0 \n", + "\n", + " Unrated X Animation Romance Comedy Horror Biography Musical Sci-Fi \\\n", + "0 0 0 0 0 0 0 0 0 1 \n", + "1 0 0 0 0 0 0 0 0 0 \n", + "\n", + " Fantasy Crime Western Thriller Sport War Family Drama Adventure \\\n", + "0 1 0 0 0 0 0 0 0 1 \n", + "1 1 0 0 0 0 0 0 0 1 \n", + "\n", + " Documentary Mystery Action Music Film-Noir History \n", + "0 0 0 1 0 0 0 \n", + "1 0 0 1 0 0 0 " + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_model.head(2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (9.2) Training a model" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.model_selection import train_test_split" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "df_model['gross_log'] = df_model['gross'].apply(np.log1p)\n", + "df_model['budget_log'] = df_model['budget'].apply(np.log1p)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "linreg = LinearRegression()\n", + "X = df_model.drop(columns=['movie_title', 'gross', 'budget', 'gross_log']).to_numpy()\n", + "y = df_model.gross_log.to_numpy()\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=123)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n", + " normalize=False)" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "linreg.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "y_pred = linreg.predict(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.6093703080115105" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.Series(y_test.mean() - y_test).abs().mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.1842132628414064" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pd.Series(y_pred - y_test).abs().mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pd.Series(y_pred - y_test).plot(figsize=(10, 5))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (10) Misc tips and tricks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## (10.1) Performance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ### Finding the n-largest" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There might exists built in methods which are optimal for your use case. Finding the maximum is an $\\mathcal{O}(n)$ operation, while sorting is $\\mathcal{O}(n \\log n)$. Finding the top $k$ rows can be done in $\\mathcal{O}(k + n \\log k)$ time." + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a series with a million entries\n", + "ser = pd.Series(np.random.randn(1000000))" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(ser.nlargest(50) == ser.sort_values(ascending=False).head(50)).all()" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "6.57 ms ± 916 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "ser.max()" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "31.9 ms ± 7.85 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "ser.nlargest(50)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "257 ms ± 37.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "ser.sort_values(ascending=False).head(50)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Filter *before* computing\n", + "\n", + "It's generally better to apply filters *before* computations, especially if the computations are expensive." + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "57.1 ms ± 997 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "df.mean().imdb_score" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "48.9 µs ± 1.28 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "df.imdb_score.mean()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "-----------------" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.sort_values('gross').dropna(how='any')\n", + "temp = df.set_index('director_name').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "502 µs ± 41.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "temp.loc[lambda df:df.index > 'o', :]" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "718 µs ± 26.2 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "df.loc[lambda df:df.director_name > 'o', :]" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "137 µs ± 1.71 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "temp.loc[slice('o', None), :]" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "temp.index.dropna().is_monotonic" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Vectorize everything (if you can)" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [], + "source": [ + "import math\n", + "\n", + "temp = df.gross.dropna()" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "866 µs ± 18.6 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "temp.map(math.log)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "168 µs ± 2.3 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "temp.apply(np.log)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Another vectorization example" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [], + "source": [ + "import statistics\n", + "\n", + "vector = np.arange(1000000)" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2.01 ms ± 81.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "np.mean(vector[1:] - vector[:-1])" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [], + "source": [ + "vector = list(vector)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "777 ms ± 10.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "statistics.mean((i - j for (i, j) in zip(vector[1:], vector[:-1])))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "----------------" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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" + ], + "text/plain": [ + " country\n", + "0 USA\n", + "1 USA\n", + "2 France" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_countries = df.country.sample(5_000_000, replace=True).to_frame().reset_index(drop=True)\n", + "df_countries.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "354 ms ± 40.4 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "df_countries.assign(USA=lambda df:np.where(df.country == 'USA', 1, 0))" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.38 s ± 38.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + ] + } + ], + "source": [ + "%%timeit\n", + "\n", + "def is_USA(string):\n", + " if string == 'USA':\n", + " return 1\n", + " return 0\n", + "\n", + "df_countries.assign(USA=lambda df:df.country.apply(is_USA))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# (11) Problems and answers" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# References\n", + "\n", + "- [Official Pandas Documentation](https://pandas.pydata.org/pandas-docs/stable/index.html)\n", + "- Videos at [awesome-pandas](https://github.com/tommyod/awesome-pandas), especially" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tutorial/Tutorial.ipynb b/tutorial/Tutorial.ipynb deleted file mode 100644 index 6c139e5..0000000 --- a/tutorial/Tutorial.ipynb +++ /dev/null @@ -1,7628 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "raw_mimetype": "-" - }, - "source": [ - "# Python for Data Analysis using Pandas\n", - "\n", - "> The latest version of notebook is always found at [github.com/tommyod/awesome-pandas](https://github.com/tommyod/awesome-pandas). \n", - " Improvements, corrections or suggestions? **Please submit a [Pull Request](https://github.com/tommyod/awesome-pandas/pulls).**\n", - " \n", - " ![](pandas_vs_excel_vs_sas.png)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Table of contents\n", - "\n", - "- (1) Setup\n", - " - (1.1) Installing Python and packages\n", - " - (1.2) Importing packages\n", - "- (2) Importing data\n", - " - (2.1) Importing .csv files\n", - " - (2.2) Other ways of creating DataFrames\n", - " - (2.3) Changing names and data types\n", - "- (3) Summarizing data\n", - " - (3.1) Peeking at the data\n", - " - (3.2) Null values and summary statistics\n", - " - (3.3) Unique values, value counts and sorting\n", - " - (3.4) Basic visualizations\n", - "- (4) Selecting and computing new columns\n", - " - (4.1) Accessing rows, columns and data\n", - " - (4.2) Selecting subsets of columns\n", - " - (4.3) Selecting subsets of rows\n", - " - (4.4) Selecting subsets of rows *and* columns\n", - " - (4.5) Creating new columns\n", - " - (4.6) Applying functions\n", - "- (5) Filtering and sorting\n", - " - (5.1) Equality, non-equality and logical operators\n", - " - (5.2) Group membership and string filtering\n", - "- (6) Split-apply-combine and pivots\n", - " - (6.1) The groupby operation\n", - " - (6.2) Several groups and aggregations\n", - " - (6.3) Unstacking and stacking\n", - " - (6.4) Pivoting and melting\n", - " - (6.4) Merging\n", - "- (7) Plotting\n", - " - (7.1) Built-in `plot()` methods\n", - " - (7.2) Using matplotlib\n", - "- (8) Time series manipulations\n", - " - (8.1) `.dt` accessor\n", - " - (8.2) Rolling window functions\n", - " - (8.3) Resampling\n", - "- (9) Modeling and Machine Learning\n", - " - (9.1) Dummy variables for categorical data\n", - " - (9.2) Training a model\n", - "- (10) Misc tips and tricks\n", - " - (10.1) Performance\n", - "- (11) Problems and answers" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---------------------------------" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (1) Setup" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (1.1) Installing Python and packages" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Python and Anaconda\n", - "\n", - "If you haven't done it yet, you need to install Python.\n", - "I recommend the [Anaconda Distribution](https://www.anaconda.com/download/), and you should install version `3.X`.\n", - "- If you're on Windows, you will get a program called *Anaconda Prompt*. Open in and run `conda --version` to verify that everything works.\n", - "- If you're on Linux, open a terminal and run `conda --version`.\n", - "\n", - "Type `conda list` to see every installed package, and `conda update --all` to update every package. Type `python` to open an interactive Python terminal, and `exit()` to leave.\n", - "\n", - "### NumPy, matplotlib and Pandas\n", - "\n", - "![](https://indranilsinharoy.files.wordpress.com/2013/01/scientificpythonecosystemsi.png?w=584&h=442)\n", - "\n", - "*Image source: https://indranilsinharoy.com/2013/01/06/python-for-scientific-computing-a-collection-of-resources/*\n", - "\n", - "To install indiviual packages, run `conda install `. \n", - "The Anaconda distribution comes with 3 packages which this tutorial requires, namely [pandas](https://pandas.pydata.org/), [NumPy](http://www.numpy.org/) and [matplotlib](https://matplotlib.org/).\n", - "We'll also briefly use [sklearn](https://scikit-learn.org/stable/).\n", - "\n", - "- **NumPy** implements $n$-dimensional arrays in Python for efficient numerical computations. See the [arXiv](https://arxiv.org/pdf/1102.1523.pdf) paper for a nice introduction. To learn basic NumPy, consider doing these [100 NumPy exercises](https://github.com/rougier/numpy-100). For an in-depth look at NumPy and vectorization to speed up scientific computing, see [From Python to Numpy\n", - "](https://www.labri.fr/perso/nrougier/from-python-to-numpy/).\n", - "- **Matplotlib** is the most popular library for plotting in Python. See the beautiful [gallery](https://matplotlib.org/gallery.html) to get an overview of the capabilities of matplotlib. Read the [Matplotlib tutorial](http://www.labri.fr/perso/nrougier/teaching/matplotlib/matplotlib.html) by Nicolas P. Rougier for an introduction.\n", - "- **Pandas** is a library for data analysis based on two objects, the [Series](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.html) and the [DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html).\n", - "\n", - "### Jupyter\n", - "\n", - "A [Jupyter Notebook](https://jupyter-notebook.readthedocs.io/en/stable/) is an environment for running Python code interactively, displaying graphs and working with data. Think of it as a tool with capabilities somwhere between a simple terminal and a full fledged IDE. Move to a directory using the `cd` command in the terminal, then run `jupyter notebook` to start up a notebook. A video introduction to JupyterLab is [JupyterLab: Building Blocks for Interactive Computing](https://www.youtube.com/watch?v=Ejh0ftSjk6g)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (1.2) Importing packages" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "import matplotlib\n", - "import KDEpy\n", - "import sklearn\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Package versions\n", - "\n", - "To make this Jupyter Notebook reproducible, we list versions of the libraries we will be using." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Today is 2018-12-20 19:23:32.779865\n", - "----------------------------------------------------------------\n", - "pandas version 0.23.4\n", - "numpy version 1.15.3\n", - "matplotlib version 2.2.3\n", - "KDEpy version 0.6.9\n", - "sklearn version 0.20.0\n" - ] - } - ], - "source": [ - "import datetime\n", - "\n", - "print('Today is', datetime.datetime.utcnow())\n", - "print('-'*2**6)\n", - "\n", - "for lib in [pd, np, matplotlib, KDEpy, sklearn]:\n", - " print(f'{lib.__name__.ljust(12)} version {lib.__version__}')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Using Jupyter Notebooks\n", - "\n", - "- Useful shortcuts: `SHIFT + TAB`, `SHIFT + ENTER`, `ESC`, `ENTER`, `E`, `A`, `D,D`, `I, I`. Type `H` to see all shortcuts.\n", - "- Executing terminal commands from within the notebook using `!`.\n", - "- Using markdown and $\\LaTeX{}$.\n", - "- Timing cells using `%%timeit` and other built-in magic commands.\n", - "- Pitfalls when using notebooks: state, order of execution, tidyness." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (2) Importing data\n", - "\n", - "Starting a cell with a `!` let's us use terminal commands. The UNIX `head` command shows the first rows of the file." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (2.1) Importing `.csv` files" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[01;34m.\u001b[00m\r\n", - "├── \u001b[01;34mdata\u001b[00m\r\n", - "│   ├── google_trends.csv\r\n", - "│   ├── movie_metadata.csv\r\n", - "│   ├── wine_data.csv\r\n", - "│   └── world_population_history.csv\r\n", - "├── \u001b[01;35mpandas_vs_excel_vs_sas.png\u001b[00m\r\n", - "├── Tutorial.ipynb\r\n", - "└── Tutorial.py\r\n", - "\r\n", - "1 directory, 7 files\r\n" - ] - } - ], - "source": [ - "!tree . -L 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> **Interested in learning UNIX commands?** The book [The Linux Command Line](https://www.amazon.com/Linux-Command-Line-Complete-Introduction-ebook/dp/B006X2QEQS) gives a detailed introduction, and [Data Science at the Command Line](https://www.amazon.com/Data-Science-Command-Line-Time-Tested/dp/1491947853) shows how basic data manipulation may be done using the command line only." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "color,director_name,num_critic_for_reviews,duration,director_facebook_likes,actor_3_facebook_likes,actor_2_name,actor_1_facebook_likes,gross,genres,actor_1_name,movie_title,num_voted_users,cast_total_facebook_likes,actor_3_name,facenumber_in_poster,plot_keywords,movie_imdb_link,num_user_for_reviews,language,country,content_rating,budget,title_year,actor_2_facebook_likes,imdb_score,aspect_ratio,movie_facebook_likes\r", - "\r\n", - "Color,James Cameron,723,178,0,855,Joel David Moore,1000,760505847,Action|Adventure|Fantasy|Sci-Fi,CCH Pounder,Avatar ,886204,4834,Wes Studi,0,avatar|future|marine|native|paraplegic,http://www.imdb.com/title/tt0499549/?ref_=fn_tt_tt_1,3054,English,USA,PG-13,237000000,2009,936,7.9,1.78,33000\r", - "\r\n" - ] - } - ], - "source": [ - "!head data/movie_metadata.csv -n 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The file has many columns, so we'll only load a couple into a pandas DataFrame.\n", - "To familiarize ourselves with with [magic commands](http://ipython.readthedocs.io/en/stable/interactive/magics.html), we'll use `%%time` to time the execution of the cell below." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loaded data of size (5043, 6) into memory.\n", - "CPU times: user 70.3 ms, sys: 11.7 ms, total: 82.1 ms\n", - "Wall time: 143 ms\n" - ] - } - ], - "source": [ - "%%time\n", - "\n", - "cols_to_use = ['movie_title', 'director_name', 'country', 'content_rating', 'imdb_score', 'gross']\n", - "df = pd.read_csv(r'data/movie_metadata.csv', sep=',', usecols=cols_to_use)\n", - "print(f'Loaded data of size {df.shape} into memory.')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " director_name gross movie_title \\\n", - "0 James Cameron 760505847.0 Avatar  \n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", - "\n", - " country content_rating imdb_score \n", - "0 USA PG-13 7.9 \n", - "1 USA PG-13 7.1 " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.head(2) # Show the top 2 rows" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `df.shape` attribute gives the rows and columns of the DataFrame." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(5043, 6)" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.shape # Alternatively, use len(df) for row count" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (2.2) Other ways of creating DataFrames\n", - "\n", - "**The DataFrame**\n", - "\n", - "> Two-dimensional size-mutable, potentially heterogeneous tabular data\n", - "structure with **labeled axes** (rows and columns). Arithmetic operations\n", - "align on both row and column labels. Can be thought of as a **dict-like\n", - "container for Series objects**. The primary pandas data structure.\n", - "\n", - "**Creating a DataFrame from scratch**" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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450Michael OttoGermany18.1 billionOtto Group
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" - ], - "text/plain": [ - " World ranking Name Citizenship \\\n", - "0 21 Georg Schaeffler Germany \n", - "1 37 Beate Heister (b. Albrecht) & Karl Albrecht Jr. Germany \n", - "2 46 Dieter Schwarz Germany \n", - "3 49 Theo Albrecht Jr. Germany \n", - "4 50 Michael Otto Germany \n", - "\n", - " Net worth (USD) Sources of wealth \n", - "0 26.9 billion Schaeffler Group \n", - "1 21.3 billion Aldi Süd \n", - "2 19.4 billion Schwarz Gruppe \n", - "3 19 billion Aldi Nord and Trader Joe's \n", - "4 18.1 billion Otto Group " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Read HTML tables into a list of DataFrame objects.\n", - "url = r'https://en.wikipedia.org/wiki/List_of_Germans_by_net_worth'\n", - "tables = pd.read_html(url, header=0)\n", - "\n", - "df_net_worth = tables[0]\n", - "\n", - "# Asserts can be useful for sanity checks\n", - "assert len(df_net_worth) > 0 \n", - "assert df_net_worth.Name.is_unique\n", - "\n", - "\n", - "df_net_worth.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Reading from databases is also possible.**\n", - "\n", - "Reading from Microsoft SQL using `pyodbc` and `pd.read_sql(sql_code, connection)`." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---------\n", - "\n", - "> **Gotcha.** Methods on DataFrames return a new instance by default. In other words, they behave like methods on *immutable* Python object, and not like methods on *mutable* objects." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1, 2, 4, 6, 9]\n", - "Tommy\n" - ] - } - ], - "source": [ - "# Lists are MUTABLE\n", - "scores = [6, 2, 4, 9, 1]\n", - "scores.sort() # Changes the object in-place, returns None\n", - "print(scores)\n", - "\n", - "# Strings are IMMUTABLE\n", - "my_name = 'tommy'\n", - "my_name = my_name.capitalize() # A new instance is returned\n", - "print(my_name)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (2.3) Changing names and data types" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Director_nameGrossMovie_titleCountryContent_ratingImdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.1
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" - ], - "text/plain": [ - " Director_name Gross Movie_title \\\n", - "0 James Cameron 760505847.0 Avatar  \n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", - "\n", - " Country Content_rating Imdb_score \n", - "0 USA PG-13 7.9 \n", - "1 USA PG-13 7.1 " - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Alter axes labels\n", - "df_net_worth = (df_net_worth\n", - " .rename(columns={'Net worth (USD)': 'net_worth',\n", - " 'World ranking': 'world_ranking',\n", - " 'Sources of wealth': 'wealth_source'}))\n", - "\n", - "\n", - "df.rename(columns=str.capitalize).head(2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The data type of each column may be listed using `df.dtypes`. Automatic conversion is possible via `pd.to_numeric` and `pd.to_datetime`." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "director_name object\n", - "gross float64\n", - "movie_title object\n", - "country object\n", - "content_rating object\n", - "imdb_score float64\n", - "dtype: object" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.dtypes" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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world_rankingNameCitizenshipnet_worthwealth_sourcenet_worth_num
021Georg SchaefflerGermany26.9 billionSchaeffler Group26.9
137Beate Heister (b. Albrecht) & Karl Albrecht Jr.Germany21.3 billionAldi Süd21.3
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" - ], - "text/plain": [ - " world_ranking Name Citizenship \\\n", - "0 21 Georg Schaeffler Germany \n", - "1 37 Beate Heister (b. Albrecht) & Karl Albrecht Jr. Germany \n", - "\n", - " net_worth wealth_source net_worth_num \n", - "0 26.9 billion Schaeffler Group 26.9 \n", - "1 21.3 billion Aldi Süd 21.3 " - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_net_worth['net_worth_num'] = (df_net_worth['net_worth']\n", - " .str.replace(' billion', '')\n", - " .apply(float))\n", - "\n", - "df_net_worth.head(2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (3) Summarizing data\n", - "\n", - "This section shows some important methods related to summarizing data." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (3.1) Peeking at the data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Three methods that are useful when peeking at the data are `df.head`, `df.tail` and `df.sample`.\n", - "Head and tail are $\\mathcal{O}(1)$ operations, while sample is $\\mathcal{O}(n)$, where $n$ is the number of rows.\n", - "For small datasets, this makes no difference in practice. We'll use `df.sample` here." - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.1
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" - ], - "text/plain": [ - " director_name gross movie_title \\\n", - "0 James Cameron 760505847.0 Avatar  \n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", - "\n", - " country content_rating imdb_score \n", - "0 USA PG-13 7.9 \n", - "1 USA PG-13 7.1 " - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Return the first `n` rows.\n", - "df.head(n=2) # df.tail(n=2) returns the last rows" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
2375Roger Donaldson8600000.0The BountyUKPG7.0
4252Woody AllenNaNEverything You Always Wanted to Know About Sex...USAR6.8
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" - ], - "text/plain": [ - " director_name gross \\\n", - "2375 Roger Donaldson 8600000.0 \n", - "4252 Woody Allen NaN \n", - "\n", - " movie_title country \\\n", - "2375 The Bounty  UK \n", - "4252 Everything You Always Wanted to Know About Sex... USA \n", - "\n", - " content_rating imdb_score \n", - "2375 PG 7.0 \n", - "4252 R 6.8 " - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.sample(n=2, replace=False, weights=None, random_state=None)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (3.2) Null values and summary statistics" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We should make sure the data types are correct. To do so, we can use `df.dtypes`, or `df.info()` for some more information." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 5043 entries, 0 to 5042\n", - "Data columns (total 6 columns):\n", - "director_name 4939 non-null object\n", - "gross 4159 non-null float64\n", - "movie_title 5043 non-null object\n", - "country 5038 non-null object\n", - "content_rating 4740 non-null object\n", - "imdb_score 5043 non-null float64\n", - "dtypes: float64(2), object(4)\n", - "memory usage: 236.5+ KB\n" - ] - } - ], - "source": [ - "# Print a concise summary of a DataFrame\n", - "df.info(verbose=True, memory_usage=True, null_counts=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We have some null values. Let's count them by chaining `df.isnull()` and `df.sum()`." - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "director_name 104\n", - "gross 884\n", - "movie_title 0\n", - "country 5\n", - "content_rating 303\n", - "imdb_score 0\n", - "dtype: int64" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Detect missing values -> sum over rows\n", - "null_values = df.isnull().sum(axis=0)\n", - "null_values # / len(df)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The result of the above is not a DataFrame object, but a Series." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "pandas.core.series.Series" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "type(null_values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "![alt text](https://www.mathsisfun.com/algebra/images/scalar-vector-matrix.svg)\n", - "*Image source:* https://www.mathsisfun.com/algebra/scalar-vector-matrix.html\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can make the output prettier by converting null_values to a DataFrame using the `to_frame()` method, then transposing using `.T`, and finally renaming the first index." - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
Missing values104884053030
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating \\\n", - "Missing values 104 884 0 5 303 \n", - "\n", - " imdb_score \n", - "Missing values 0 " - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "null_values.to_frame().T.rename(index={0: 'Missing values'})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The above is called method chaining, and can be written like so:" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
Missing values104884053030
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating \\\n", - "Missing values 104 884 0 5 303 \n", - "\n", - " imdb_score \n", - "Missing values 0 " - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(df\n", - " .isnull() # Figure out whether every entry is null (missing), or not\n", - " .sum(axis=0) # Sum over each column, axis=0 is the default\n", - " .to_frame() # The result is a Series, convert to DataFrame\n", - " .T # Transpose (switch rows and columns)\n", - " .rename(index={0:'Missing values'}) # Rename the index and show it\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "A tour of summarization would not be complete without `df.describe()`.\n", - "Calling `df.count()`, `df.nunique()`, `df.mean()`, `df.std()`, `df.min()`, `df.quantile()`, `df.max()` is also possible.\n", - "\n", - "> **Gotcha.** There are 200+ methods defined on a DataFrame. See the [API Reference](https://pandas.pydata.org/pandas-docs/stable/api.html) for an exhaustive list." - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
count493941595043503847405043
unique239849176518
topSteven SpielbergPanUSAR
freq26338072118
mean4.84684e+076.44214
std6.8453e+071.12512
min1621.6
50%2.55175e+076.6
max7.60506e+089.5
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating \\\n", - "count 4939 4159 5043 5038 4740 \n", - "unique 2398 4917 65 18 \n", - "top Steven Spielberg Pan  USA R \n", - "freq 26 3 3807 2118 \n", - "mean 4.84684e+07 \n", - "std 6.8453e+07 \n", - "min 162 \n", - "50% 2.55175e+07 \n", - "max 7.60506e+08 \n", - "\n", - " imdb_score \n", - "count 5043 \n", - "unique \n", - "top \n", - "freq \n", - "mean 6.44214 \n", - "std 1.12512 \n", - "min 1.6 \n", - "50% 6.6 \n", - "max 9.5 " - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.describe(percentiles=[0.5], include='all').fillna('')" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(5043, 6)" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(4092, 6)" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.dropna(axis=0, how='any').shape" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(4920, 6)" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.drop_duplicates(subset=None).shape # Use df[df.duplicated()] to see rows" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "df = df.dropna(axis=0, how='any').drop_duplicates(subset=None)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (3.3) Unique values, value counts and sorting" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array(['PG-13', 'PG', 'G', 'R', 'Unrated', 'Approved', 'NC-17', 'X',\n", - " 'Not Rated', 'M', 'GP', 'Passed'], dtype=object)" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.content_rating.unique() # Not the same as: df.content_rating.is_unique" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['PG-13', 'PG', 'G', 'R', 'Unrated', 'Approved', 'NC-17', 'X', 'Not Rated', 'M', 'GP', 'Passed']\n" - ] - } - ], - "source": [ - "print(df.content_rating.drop_duplicates().tolist())" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "R 1818\n", - "PG-13 1352\n", - "PG 596\n", - "G 95\n", - "Not Rated 56\n", - "Unrated 34\n", - "Approved 18\n", - "X 9\n", - "NC-17 6\n", - "Passed 3\n", - "M 2\n", - "GP 1\n", - "Name: content_rating, dtype: int64" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.content_rating.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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movie_titlegross
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26Titanic658672302.0
29Jurassic World652177271.0
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" - ], - "text/plain": [ - " movie_title gross\n", - "0 Avatar  760505847.0\n", - "26 Titanic  658672302.0\n", - "29 Jurassic World  652177271.0" - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df[['movie_title', 'gross']].nlargest(3, 'gross')" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4735Siddiq Barmak1127331.0OsamaAfghanistanPG-137.4
4000Juan José Campanella20167424.0The Secret in Their EyesArgentinaR8.2
4415Fabián Bielinsky1221261.0Nine QueensArgentinaR7.9
4450Lucrecia Martel304124.0The Holy GirlArgentinaR6.7
1491Hark Tsui10076136.0Knock OffArubaR4.8
\n", - "
" - ], - "text/plain": [ - " director_name gross movie_title \\\n", - "4735 Siddiq Barmak 1127331.0 Osama  \n", - "4000 Juan José Campanella 20167424.0 The Secret in Their Eyes  \n", - "4415 Fabián Bielinsky 1221261.0 Nine Queens  \n", - "4450 Lucrecia Martel 304124.0 The Holy Girl  \n", - "1491 Hark Tsui 10076136.0 Knock Off  \n", - "\n", - " country content_rating imdb_score \n", - "4735 Afghanistan PG-13 7.4 \n", - "4000 Argentina R 8.2 \n", - "4415 Argentina R 7.9 \n", - "4450 Argentina R 6.7 \n", - "1491 Aruba R 4.8 " - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Sort by country, then by IMDB_score. Put NA values last\n", - "df.sort_values(by=['country', 'imdb_score'], \n", - " ascending=[True, False], \n", - " na_position='last').head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (3.4) Basic visualizations\n", - "\n", - "Some quick visualizations." - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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grossimdb_score
gross1.000000.20497
imdb_score0.204971.00000
\n", - "
" - ], - "text/plain": [ - " gross imdb_score\n", - "gross 1.00000 0.20497\n", - "imdb_score 0.20497 1.00000" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.corr(method='pearson')" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plot = pd.plotting.scatter_matrix(df, alpha=0.5, figsize=(10, 5))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (4) Selecting and computing new columns\n", - "\n", - "This section is about selecting subsets of a datset, or creating new data from existing data, i.e.:\n", - "\n", - "- Selecting a single column, or a subset of columns\n", - "- Selecting a subset of rows, i.e. filtering\n", - "- Chaining the above operations to do both\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (4.1) Accessing index, columns and data" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Int64Index([ 0, 1, 2, 3, 5, 6, 7, 8, 9, 10,\n", - " ...\n", - " 5021, 5025, 5026, 5027, 5033, 5034, 5035, 5037, 5041, 5042],\n", - " dtype='int64', length=3990)" - ] - }, - "execution_count": 65, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.index" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['director_name', 'gross', 'movie_title', 'country', 'content_rating',\n", - " 'imdb_score'],\n", - " dtype='object')" - ] - }, - "execution_count": 66, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.columns" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([['James Cameron', 760505847.0, 'Avatar\\xa0', 'USA', 'PG-13', 7.9],\n", - " ['Gore Verbinski', 309404152.0,\n", - " \"Pirates of the Caribbean: At World's End\\xa0\", 'USA', 'PG-13',\n", - " 7.1],\n", - " ['Sam Mendes', 200074175.0, 'Spectre\\xa0', 'UK', 'PG-13', 6.8],\n", - " ...,\n", - " ['Edward Burns', 4584.0, 'Newlyweds\\xa0', 'USA', 'Not Rated', 6.4],\n", - " ['Daniel Hsia', 10443.0, 'Shanghai Calling\\xa0', 'USA', 'PG-13',\n", - " 6.3],\n", - " ['Jon Gunn', 85222.0, 'My Date with Drew\\xa0', 'USA', 'PG', 6.6]],\n", - " dtype=object)" - ] - }, - "execution_count": 67, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# This is very useful when using data with libraries\n", - "df.values" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "numpy.ndarray" - ] - }, - "execution_count": 68, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "type(df.values)" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([7.60505847e+08, 3.09404152e+08, 2.00074175e+08, ...,\n", - " 4.58400000e+03, 1.04430000e+04, 8.52220000e+04])" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.gross.dropna().values" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (4.2) Selecting subsets of columns" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['director_name', 'gross', 'movie_title', 'country', 'content_rating', 'imdb_score']\n" - ] - } - ], - "source": [ - "print(df.columns.tolist()) # Get the columns" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0 James Cameron\n", - "1 Gore Verbinski\n", - "2 Sam Mendes\n", - "Name: director_name, dtype: object" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.director_name.head(3) # Alternatively, use df['director_name'].head(3)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Selecting two or more columns." - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
movie_titlecountry
0AvatarUSA
1Pirates of the Caribbean: At World's EndUSA
\n", - "
" - ], - "text/plain": [ - " movie_title country\n", - "0 Avatar  USA\n", - "1 Pirates of the Caribbean: At World's End  USA" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df[['movie_title', 'country']].head(2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The most useful selection function is `df.loc[[row1, row2, ...], [col1, col2, ...]]`.\n", - "\n", - "- `df.loc[:, [col1, col2]]` selects every row, and columns `[col1, col2]`\n", - "- `df.loc[[row1, row2], :]` selects rows `[row1, row2]`, and every column" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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movie_titlecountry
0AvatarUSA
1Pirates of the Caribbean: At World's EndUSA
\n", - "
" - ], - "text/plain": [ - " movie_title country\n", - "0 Avatar  USA\n", - "1 Pirates of the Caribbean: At World's End  USA" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[:, ['movie_title', 'country']].head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "\n" - ] - } - ], - "source": [ - "a = df.loc[:, 'gross'] # Returns a Series\n", - "b = df.loc[:, ['gross']] # Returns a DataFrame\n", - "\n", - "print(type(a))\n", - "print(type(b))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Instead of selecting a subset of columns to *keep*, we can select a subset to *drop*." - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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countrycontent_ratingimdb_score
0USAPG-137.9
1USAPG-137.1
2UKPG-136.8
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" - ], - "text/plain": [ - " country content_rating imdb_score\n", - "0 USA PG-13 7.9\n", - "1 USA PG-13 7.1\n", - "2 UK PG-13 6.8" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Drop specified labels from rows or columns\n", - "df.drop(columns=['director_name', 'gross', 'movie_title']).head(3)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_title
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's End
2Sam Mendes200074175.0Spectre
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" - ], - "text/plain": [ - " director_name gross movie_title\n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End \n", - "2 Sam Mendes 200074175.0 Spectre " - ] - }, - "execution_count": 76, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Integer-location based indexing\n", - "df.iloc[1:3, [0, 1, 2]]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (4.3) Selecting subsets of rows" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating imdb_score\n", - "0 James Cameron 760505847.0 Avatar  USA PG-13 7.9" - ] - }, - "execution_count": 78, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Return the first `n` rows\n", - "df.head(n=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating imdb_score\n", - "0 James Cameron 760505847.0 Avatar  USA PG-13 7.9" - ] - }, - "execution_count": 79, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Access a group of rows and columns by label(s) or a boolean array\n", - "df.loc[[0], :]" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating imdb_score\n", - "0 James Cameron 760505847.0 Avatar  USA PG-13 7.9" - ] - }, - "execution_count": 80, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[[0]]" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4498Sergio Leone6100000.0The Good, the Bad and the UglyItalyApproved8.9
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
4029Fernando Meirelles7563397.0City of GodBrazilR8.7
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" - ], - "text/plain": [ - " director_name gross \\\n", - "4498 Sergio Leone 6100000.0 \n", - "270 Peter Jackson 313837577.0 \n", - "4029 Fernando Meirelles 7563397.0 \n", - "\n", - " movie_title country \\\n", - "4498 The Good, the Bad and the Ugly  Italy \n", - "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", - "4029 City of God  Brazil \n", - "\n", - " content_rating imdb_score \n", - "4498 Approved 8.9 \n", - "270 PG-13 8.8 \n", - "4029 R 8.7 " - ] - }, - "execution_count": 83, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Top three movies / TV-series not from the USA\n", - "df[df.country != 'USA'].nlargest(3, 'imdb_score')" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
2323Hayao Miyazaki2298191.0Princess MononokeJapanPG-138.4
4659Asghar Farhadi7098492.0A SeparationIranPG-138.4
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" - ], - "text/plain": [ - " director_name gross \\\n", - "270 Peter Jackson 313837577.0 \n", - "2323 Hayao Miyazaki 2298191.0 \n", - "4659 Asghar Farhadi 7098492.0 \n", - "\n", - " movie_title country \\\n", - "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", - "2323 Princess Mononoke  Japan \n", - "4659 A Separation  Iran \n", - "\n", - " content_rating imdb_score \n", - "270 PG-13 8.8 \n", - "2323 PG-13 8.4 \n", - "4659 PG-13 8.4 " - ] - }, - "execution_count": 84, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Best non-American films, with content rating PG-13\n", - "mask = (df.country != 'USA') & (df.content_rating == 'PG-13')\n", - "df[mask].nlargest(3, 'imdb_score')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (4.4) Selecting subsets of rows *and* columns" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namemovie_titlecountry
1196James WanThe Conjuring 2USA
1562Martin ScorseseBringing Out the DeadUSA
2163James WanThe ConjuringUSA
2969Peter WebberGirl with a Pearl EarringUK
3858Todd SolondzLife During WartimeUSA
4298Lance MungiaSix-String SamuraiUSA
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" - ], - "text/plain": [ - " director_name movie_title country\n", - "1196 James Wan The Conjuring 2  USA\n", - "1562 Martin Scorsese Bringing Out the Dead  USA\n", - "2163 James Wan The Conjuring  USA\n", - "2969 Peter Webber Girl with a Pearl Earring  UK\n", - "3858 Todd Solondz Life During Wartime  USA\n", - "4298 Lance Mungia Six-String Samurai  USA" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Above average movies, with the title containing 'ring'\n", - "row_mask = ((df.imdb_score > df.imdb_score.mean()) & \n", - " df.movie_title.str.contains('ring'))\n", - "df.loc[row_mask, ['director_name', 'movie_title', 'country']]" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namemovie_titlecontent_ratingimdb_score
0James CameronAvatarPG-137.9
1Gore VerbinskiPirates of the Caribbean: At World's EndPG-137.1
2Sam MendesSpectrePG-136.8
3Christopher NolanThe Dark Knight RisesPG-138.5
5Andrew StantonJohn CarterPG-136.6
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" - ], - "text/plain": [ - " director_name movie_title \\\n", - "0 James Cameron Avatar  \n", - "1 Gore Verbinski Pirates of the Caribbean: At World's End  \n", - "2 Sam Mendes Spectre  \n", - "3 Christopher Nolan The Dark Knight Rises  \n", - "5 Andrew Stanton John Carter  \n", - "\n", - " content_rating imdb_score \n", - "0 PG-13 7.9 \n", - "1 PG-13 7.1 \n", - "2 PG-13 6.8 \n", - "3 PG-13 8.5 \n", - "5 PG-13 6.6 " - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Columns containing and underscore\n", - "cols = [c for c in df.columns if '_' in c]\n", - "df.loc[:, cols].head()" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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grossimdb_score
0760505847.07.9
1309404152.07.1
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" - ], - "text/plain": [ - " gross imdb_score\n", - "0 760505847.0 7.9\n", - "1 309404152.0 7.1" - ] - }, - "execution_count": 90, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Numerical columns\n", - "numeric_cols = df.dtypes[df.dtypes == np.float].index.tolist()\n", - "df.loc[:, numeric_cols].head(n=2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (4.5) Creating new columns" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_scorelog_gross
0James Cameron760505847.0AvatarUSAPG-137.98.881103
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.18.490526
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" - ], - "text/plain": [ - " director_name gross movie_title \\\n", - "0 James Cameron 760505847.0 Avatar  \n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", - "\n", - " country content_rating imdb_score log_gross \n", - "0 USA PG-13 7.9 8.881103 \n", - "1 USA PG-13 7.1 8.490526 " - ] - }, - "execution_count": 94, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "temp = df.copy() # Copy the DataFrame\n", - "\n", - "# Create a new column - based on the gross income\n", - "temp['log_gross'] = temp['gross'].apply(np.log10)\n", - "\n", - "temp.head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "temp.plot.scatter(x='imdb_score', y='log_gross', alpha=0.2, s=15, figsize=(10, 5));" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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log_gross
countrycontent_rating
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" - ], - "text/plain": [ - " log_gross\n", - "country content_rating \n", - "Afghanistan PG-13 6.05\n", - "Argentina R 6.29\n", - "Aruba R 7.00\n", - "Australia G 7.54\n", - " PG-13 7.32" - ] - }, - "execution_count": 110, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Assign new columns to a DataFrame, returning a new object\n", - "# (a copy) with the new columns added to the original ones.\n", - "(temp.assign(log_gross=lambda df:df.gross.apply(np.log10))).head()\n", - "\n", - "# One advantage is that method chaining can be used\n", - "(temp\n", - " .assign(log_gross=lambda df:df.gross.apply(np.log10)) # Create a new column\n", - " .loc[:, ['country', 'content_rating', 'log_gross']] # Filter\n", - " .groupby(['country', 'content_rating']) # Group by and mean\n", - " .mean()\n", - " .reset_index() # Reset the index to sort\n", - " .sort_values(['country', 'log_gross'], ascending=[True, False]) # Sort the results\n", - " .set_index(['country', 'content_rating']) # Re-index\n", - " .assign(log_gross=lambda df:df.log_gross.round(2)) # Re-define the column and round it\n", - " .head(5)\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (4.6) Applying functions\n", - "\n", - "On a `pd.Series`:\n", - "\n", - "- `pd.Series.map` applies an elementwise $f: \\mathbb{R} \\to \\mathbb{R}$ function (e.g. `str`, or `float`)\n", - "- `pd.Series.apply` applies a vectorized $f: \\mathbb{R}^n \\to \\mathbb{R}^n$ function (e.g. `log`, or `sin`)\n", - "- `pd.Series.aggregate` applies an aggreation $f: \\mathbb{R}^n \\to \\mathbb{R}$ function (e.g. `mean`, or `std`)\n", - "\n", - "On a `pd.DataFrame`:\n", - "\n", - "- `pd.DataFrame.applymap` applies an elementwise $f: \\mathbb{R} \\to \\mathbb{R}$ function\n", - "- `pd.DataFrame.apply` applies a vectorized $f: \\mathbb{R}^n \\to \\mathbb{R}^n$ function\n", - "- `pd.DataFrame.aggregate` applies an aggreation $f: \\mathbb{R}^n \\to \\mathbb{R}$ function" - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0 760505847.0\n", - "1 309404152.0\n", - "Name: gross, dtype: float64" - ] - }, - "execution_count": 118, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Map values of Series using input correspondence (a dict, Series, or function).\n", - "df.gross.map(float).head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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content_rating
NaN2042
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grossimdb_score
020.4494942.066863
119.5501591.960095
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" - ], - "text/plain": [ - " gross imdb_score\n", - "0 20.449494 2.066863\n", - "1 19.550159 1.960095" - ] - }, - "execution_count": 126, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[:, ['gross', 'imdb_score']].apply(np.log).head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 128, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " gross imdb_score\n", - "0 760505847 7\n", - "1 309404152 7" - ] - }, - "execution_count": 128, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[:, ['gross', 'imdb_score']].applymap(int).head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 129, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "gross 4.839239e+07\n", - "imdb_score 6.463283e+00\n", - "dtype: float64" - ] - }, - "execution_count": 129, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.loc[:, ['gross', 'imdb_score']].mean().head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 132, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "gross 760505685.0\n", - "imdb_score 7.7\n", - "dtype: float64" - ] - }, - "execution_count": 132, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Or specify your own\n", - "def spread(array):\n", - " return np.max(array) - np.min(array)\n", - "\n", - "df.loc[:, ['gross', 'imdb_score']].aggregate(spread, axis=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (5) Filtering and sorting" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We've already seen basic filtering. \n", - "\n", - "- `==` defines equality\n", - "- `!=` defines inquality equality\n", - "- `~` negates logic, e.g. `True` -> `False`\n", - "- `&` represents elementwise `and`\n", - "- `|` represents elementwise `or`\n", - "\n", - "Remember to parenthesize expressions, write:\n", - "\n", - "> `(df.col_A > 5) & (df.col_B <= 5)`\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (5.1) Equality, non-equality and logical operators" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
3690Morten Tyldum1196752.0HeadhuntersNorwayR7.6
4007André Øvredal252652.0TrollhunterNorwayPG-137.0
4240Petter Næss313436.0EllingNorwayR7.6
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" - ], - "text/plain": [ - " director_name gross movie_title country content_rating \\\n", - "3690 Morten Tyldum 1196752.0 Headhunters  Norway R \n", - "4007 André Øvredal 252652.0 Trollhunter  Norway PG-13 \n", - "4240 Petter Næss 313436.0 Elling  Norway R \n", - "\n", - " imdb_score \n", - "3690 7.6 \n", - "4007 7.0 \n", - "4240 7.6 " - ] - }, - "execution_count": 66, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Movies and TV shows from Norway\n", - "df[df.country == 'Norway'].head(3)" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4498Sergio Leone6100000.0The Good, the Bad and the UglyItalyApproved8.9
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
4029Fernando Meirelles7563397.0City of GodBrazilR8.7
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" - ], - "text/plain": [ - " director_name gross \\\n", - "4498 Sergio Leone 6100000.0 \n", - "270 Peter Jackson 313837577.0 \n", - "4029 Fernando Meirelles 7563397.0 \n", - "\n", - " movie_title country \\\n", - "4498 The Good, the Bad and the Ugly  Italy \n", - "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", - "4029 City of God  Brazil \n", - "\n", - " content_rating imdb_score \n", - "4498 Approved 8.9 \n", - "270 PG-13 8.8 \n", - "4029 R 8.7 " - ] - }, - "execution_count": 67, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mask = ((df.imdb_score > 8) & (df.country != 'USA') & (df.gross > 10**6))\n", - "df[mask].nlargest(3, columns=['imdb_score'])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (5.2) Group membership and string filtering" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
4747Akira Kurosawa269061.0Seven SamuraiJapanUnrated8.7
2373Hayao Miyazaki10049886.0Spirited AwayJapanPG8.6
2323Hayao Miyazaki2298191.0Princess MononokeJapanPG-138.4
2047Hayao Miyazaki4710455.0Howl's Moving CastleJapanPG8.2
3423Katsuhiro Ôtomo439162.0AkiraJapanR8.1
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" - ], - "text/plain": [ - " director_name gross movie_title country \\\n", - "4747 Akira Kurosawa 269061.0 Seven Samurai  Japan \n", - "2373 Hayao Miyazaki 10049886.0 Spirited Away  Japan \n", - "2323 Hayao Miyazaki 2298191.0 Princess Mononoke  Japan \n", - "2047 Hayao Miyazaki 4710455.0 Howl's Moving Castle  Japan \n", - "3423 Katsuhiro Ôtomo 439162.0 Akira  Japan \n", - "\n", - " content_rating imdb_score \n", - "4747 Unrated 8.7 \n", - "2373 PG 8.6 \n", - "2323 PG-13 8.4 \n", - "2047 PG 8.2 \n", - "3423 R 8.1 " - ] - }, - "execution_count": 68, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Top three movies from Japan or Hong Kong\n", - "df[df.country.isin(['Japan', 'Hong Kong'])].nlargest(5, 'imdb_score')" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
0James Cameron760505847.0AvatarUSAPG-137.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.1
2Sam Mendes200074175.0SpectreUKPG-136.8
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" - ], - "text/plain": [ - " director_name gross movie_title \\\n", - "0 James Cameron 760505847.0 Avatar  \n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", - "2 Sam Mendes 200074175.0 Spectre  \n", - "\n", - " country content_rating imdb_score \n", - "0 USA PG-13 7.9 \n", - "1 USA PG-13 7.1 \n", - "2 UK PG-13 6.8 " - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Movies and TV shows NOT from scandinavia\n", - "df[~df.country.isin(['Norway, Sweden', 'Denmark'])].head(3)" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_score
270Peter Jackson313837577.0The Lord of the Rings: The Fellowship of the R...New ZealandPG-138.8
339Peter Jackson377019252.0The Lord of the Rings: The Return of the KingUSAPG-138.9
340Peter Jackson340478898.0The Lord of the Rings: The Two TowersUSAPG-138.7
1170Andrew Niccol24127895.0Lord of WarUSAR7.6
1974Catherine Hardwicke11008432.0Lords of DogtownUSAPG-137.1
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" - ], - "text/plain": [ - " director_name gross \\\n", - "270 Peter Jackson 313837577.0 \n", - "339 Peter Jackson 377019252.0 \n", - "340 Peter Jackson 340478898.0 \n", - "1170 Andrew Niccol 24127895.0 \n", - "1974 Catherine Hardwicke 11008432.0 \n", - "\n", - " movie_title country \\\n", - "270 The Lord of the Rings: The Fellowship of the R... New Zealand \n", - "339 The Lord of the Rings: The Return of the King  USA \n", - "340 The Lord of the Rings: The Two Towers  USA \n", - "1170 Lord of War  USA \n", - "1974 Lords of Dogtown  USA \n", - "\n", - " content_rating imdb_score \n", - "270 PG-13 8.8 \n", - "339 PG-13 8.9 \n", - "340 PG-13 8.7 \n", - "1170 R 7.6 \n", - "1974 PG-13 7.1 " - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Contains the word 'lord'\n", - "mask = df.movie_title.str.lower().str.contains(\"lord\")\n", - "\n", - " # Gross better than 25 % of the movies\n", - "mask = mask & (df.gross > df.gross.quantile(q=[0.25]).values[0])\n", - "\n", - "df[mask]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (6) Split-apply-combine and pivots" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (6.1) The groupby operation" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "![](https://data36.com/wp-content/uploads/2017/06/SQL-GROUP-BY-clause-768x540.png)\n", - "\n", - "*Image source is https://data36.com/sql-functions-beginners-tutorial-ep3/*" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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countryimdb_score
0USA7.9
1USA7.1
2UK6.8
3USA8.5
5USA6.6
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" - ], - "text/plain": [ - " country imdb_score\n", - "0 USA 7.9\n", - "1 USA 7.1\n", - "2 UK 6.8\n", - "3 USA 8.5\n", - "5 USA 6.6" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df[['country', 'imdb_score']].head()" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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grossimdb_score
country
Afghanistan1.127331e+067.4
Argentina7.230936e+067.6
Aruba1.007614e+074.8
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" - ], - "text/plain": [ - " gross imdb_score\n", - "country \n", - "Afghanistan 1.127331e+06 7.4\n", - "Argentina 7.230936e+06 7.6\n", - "Aruba 1.007614e+07 4.8" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.groupby(df.country).mean().head(3)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Directors with the most movies." - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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movie_title
director_name
Steven Spielberg25
Clint Eastwood19
Woody Allen19
Martin Scorsese18
Ridley Scott16
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" - ], - "text/plain": [ - " movie_title\n", - "director_name \n", - "Steven Spielberg 25\n", - "Clint Eastwood 19\n", - "Woody Allen 19\n", - "Martin Scorsese 18\n", - "Ridley Scott 16" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(df\n", - " .groupby(df.director_name)\n", - " .nunique()\n", - " .movie_title\n", - " .nlargest(5)\n", - " .to_frame()\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (6.2) Several groups and aggregations\n", - "\n", - "A group can be a combination of columns, e.g. [`country`, `content_rating`]." - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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imdb_score
countrycontent_rating
AfghanistanPG-137.40
ArgentinaR7.60
ArubaR4.80
AustraliaG6.30
PG6.20
PG-136.59
R6.53
Unrated6.30
BelgiumR7.10
BrazilR8.17
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" - ], - "text/plain": [ - " imdb_score\n", - "country content_rating \n", - "Afghanistan PG-13 7.40\n", - "Argentina R 7.60\n", - "Aruba R 4.80\n", - "Australia G 6.30\n", - " PG 6.20\n", - " PG-13 6.59\n", - " R 6.53\n", - " Unrated 6.30\n", - "Belgium R 7.10\n", - "Brazil R 8.17" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.groupby(['country', 'content_rating']).mean().imdb_score.round(2).to_frame().head(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Serveral aggregation functions may be used. \n", - "Below we see directors and their `average`, `max` and `min` imdb_scores." - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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meanminmax
director_name
Aaron Schneider7.17.17.1
Aaron Seltzer2.72.72.7
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" - ], - "text/plain": [ - " mean min max\n", - "director_name \n", - "Aaron Schneider 7.1 7.1 7.1\n", - "Aaron Seltzer 2.7 2.7 2.7" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(df\n", - " .groupby(df.director_name)\n", - " .agg(['mean', 'min', 'max'])\n", - " .imdb_score\n", - " .head(2)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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meanspreadnunique
director_name
Adam McKay6.9166671.56
Adam Shankman5.9625002.27
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" - ], - "text/plain": [ - " mean spread nunique\n", - "director_name \n", - "Adam McKay 6.916667 1.5 6\n", - "Adam Shankman 5.962500 2.2 7" - ] - }, - "execution_count": 76, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def spread(series):\n", - " \"\"\"Custom aggregation function.\"\"\"\n", - " return series.max() - series.min()\n", - "\n", - "\n", - "(df\n", - " .groupby(df.director_name)\n", - " .agg(['mean', spread, 'nunique'])\n", - " .imdb_score\n", - " .loc[lambda df:df['nunique'] > 1, :]\n", - " .head(2)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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imdb_scoregross
meanstdmeanmax
countrycontent_rating
AfghanistanPG-137.400000NaN1.127331e+061127331.0
ArgentinaR7.6000000.7937257.230936e+0620167424.0
ArubaR4.800000NaN1.007614e+0710076136.0
AustraliaG6.3000000.7071074.245900e+0766600000.0
PG6.2000001.1575845.703676e+07257756197.0
PG-136.5900000.7445366.369501e+07174635000.0
R6.5315790.8550852.382520e+07153629485.0
Unrated6.300000NaN2.651070e+05265107.0
BelgiumR7.100000NaN1.357042e+061357042.0
BrazilR8.1750000.3593983.385652e+067563397.0
Unrated6.100000NaN2.026200e+0420262.0
CameroonNot Rated7.500000NaN3.263100e+0432631.0
CanadaG2.800000NaN1.114452e+0711144518.0
Not Rated6.4750000.7410581.831962e+05703002.0
PG5.5200001.0232305.192535e+07113006880.0
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" - ], - "text/plain": [ - " imdb_score gross \n", - " mean std mean max\n", - "country content_rating \n", - "Afghanistan PG-13 7.400000 NaN 1.127331e+06 1127331.0\n", - "Argentina R 7.600000 0.793725 7.230936e+06 20167424.0\n", - "Aruba R 4.800000 NaN 1.007614e+07 10076136.0\n", - "Australia G 6.300000 0.707107 4.245900e+07 66600000.0\n", - " PG 6.200000 1.157584 5.703676e+07 257756197.0\n", - " PG-13 6.590000 0.744536 6.369501e+07 174635000.0\n", - " R 6.531579 0.855085 2.382520e+07 153629485.0\n", - " Unrated 6.300000 NaN 2.651070e+05 265107.0\n", - "Belgium R 7.100000 NaN 1.357042e+06 1357042.0\n", - "Brazil R 8.175000 0.359398 3.385652e+06 7563397.0\n", - " Unrated 6.100000 NaN 2.026200e+04 20262.0\n", - "Cameroon Not Rated 7.500000 NaN 3.263100e+04 32631.0\n", - "Canada G 2.800000 NaN 1.114452e+07 11144518.0\n", - " Not Rated 6.475000 0.741058 1.831962e+05 703002.0\n", - " PG 5.520000 1.023230 5.192535e+07 113006880.0" - ] - }, - "execution_count": 77, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "funcs = {'imdb_score': [pd.Series.mean, pd.Series.std], 'gross': [pd.Series.mean, pd.Series.max]}\n", - "\n", - "df.groupby(['country', 'content_rating']).agg(funcs).head(15)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Data source: https://github.com/highcharts/highcharts/blob/master/samples/data/world-population-history.csv" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "metadata": {}, - "outputs": [], - "source": [ - "df_world = pd.read_csv(f'data/world_population_history.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "metadata": {}, - "outputs": [], - "source": [ - "df_world = (df_world\n", - " .drop(columns=['Country Name', 'Country Code', 'Indicator Name', 'Indicator Code'])\n", - " .dropna(axis=1, how='all'))" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Data SourceWorld Development Indicators19601961196219631964196519661967...2006200720082009201020112012201320142015
0ArubaABW56225.056695.057032.057360.057715.058055.058386.058726.0...101353.0101453.0101669.0102053.0102577.0103187.0103795.0104341.0104822.0105000.0
1AfghanistanAFG9345868.09533954.09731361.09938414.010152331.010372630.010604346.010854428.0...27294031.028004331.028803167.029708599.030696958.031731688.032758020.033736494.034656032.035530000.0
2AngolaAGO5866061.05980417.06093321.06203299.06309770.06414995.06523791.06642632.0...21759420.022549547.023369131.024218565.025096150.025998340.026920466.027859305.028813463.029784000.0
3AlbaniaALB1711319.01762621.01814135.01864791.01914573.01965598.02022272.02081695.0...2947314.02927519.02913021.02905195.02900401.02895092.02889104.02880703.02876101.02879000.0
4AndorraAND15370.016412.017469.018549.019647.020758.021890.023058.0...83861.084462.084449.083751.082431.080788.079223.078014.077281.077000.0
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5 rows × 58 columns

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" - ], - "text/plain": [ - " Data Source World Development Indicators 1960 1961 1962 \\\n", - "0 Aruba ABW 56225.0 56695.0 57032.0 \n", - "1 Afghanistan AFG 9345868.0 9533954.0 9731361.0 \n", - "2 Angola AGO 5866061.0 5980417.0 6093321.0 \n", - "3 Albania ALB 1711319.0 1762621.0 1814135.0 \n", - "4 Andorra AND 15370.0 16412.0 17469.0 \n", - "\n", - " 1963 1964 1965 1966 1967 ... \\\n", - "0 57360.0 57715.0 58055.0 58386.0 58726.0 ... \n", - "1 9938414.0 10152331.0 10372630.0 10604346.0 10854428.0 ... \n", - "2 6203299.0 6309770.0 6414995.0 6523791.0 6642632.0 ... \n", - "3 1864791.0 1914573.0 1965598.0 2022272.0 2081695.0 ... \n", - "4 18549.0 19647.0 20758.0 21890.0 23058.0 ... \n", - "\n", - " 2006 2007 2008 2009 2010 2011 \\\n", - "0 101353.0 101453.0 101669.0 102053.0 102577.0 103187.0 \n", - "1 27294031.0 28004331.0 28803167.0 29708599.0 30696958.0 31731688.0 \n", - "2 21759420.0 22549547.0 23369131.0 24218565.0 25096150.0 25998340.0 \n", - "3 2947314.0 2927519.0 2913021.0 2905195.0 2900401.0 2895092.0 \n", - "4 83861.0 84462.0 84449.0 83751.0 82431.0 80788.0 \n", - "\n", - " 2012 2013 2014 2015 \n", - "0 103795.0 104341.0 104822.0 105000.0 \n", - "1 32758020.0 33736494.0 34656032.0 35530000.0 \n", - "2 26920466.0 27859305.0 28813463.0 29784000.0 \n", - "3 2889104.0 2880703.0 2876101.0 2879000.0 \n", - "4 79223.0 78014.0 77281.0 77000.0 \n", - "\n", - "[5 rows x 58 columns]" - ] - }, - "execution_count": 80, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_world.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (6.3) Unstacking and stacking" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's load a data set from [https://github.com/highcharts/highcharts](https://github.com/highcharts/highcharts/blob/master/samples/data/world-population-history.csv), which is not tidy.\n", - "\n", - "> (1) Each variable you measure should be in one column. \n", - " (2) Each different observation of that variable should be in a different row. \n", - " (3) There should be one table for each \"kind\" of variable. \n", - " (4) If you have multiple tables, they should include a column in the table that allows them to be linked.\n", - " \n", - "\n", - "\n", - "\n", - "Read [\"Tidy Data\" by H Wickham](https://www.jstatsoft.org/article/view/v059i10/v59i10.pdf) for more information." - ] - }, - { - "cell_type": "code", - "execution_count": 81, - "metadata": {}, - "outputs": [], - "source": [ - "df_world = pd.read_csv(f'data/world_population_history.csv')\n", - "\n", - "drop_cols = ['Country Name', 'Country Code', 'Indicator Name', 'Indicator Code', 'World Development Indicators']\n", - "\n", - "df_world = (df_world\n", - " .drop(columns=drop_cols)\n", - " .dropna(axis=1, how='all'))" - ] - }, - { - "cell_type": "code", - "execution_count": 82, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Data Source1960196119621963
0Aruba56225.056695.057032.057360.0
1Afghanistan9345868.09533954.09731361.09938414.0
2Angola5866061.05980417.06093321.06203299.0
3Albania1711319.01762621.01814135.01864791.0
4Andorra15370.016412.017469.018549.0
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" - ], - "text/plain": [ - " Data Source 1960 1961 1962 1963\n", - "0 Aruba 56225.0 56695.0 57032.0 57360.0\n", - "1 Afghanistan 9345868.0 9533954.0 9731361.0 9938414.0\n", - "2 Angola 5866061.0 5980417.0 6093321.0 6203299.0\n", - "3 Albania 1711319.0 1762621.0 1814135.0 1864791.0\n", - "4 Andorra 15370.0 16412.0 17469.0 18549.0" - ] - }, - "execution_count": 82, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_world.iloc[:5, :5]" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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CountryYearPopulation
0Aruba1960-01-0156225.0
1Aruba1961-01-0156695.0
2Aruba1962-01-0157032.0
3Aruba1963-01-0157360.0
4Aruba1964-01-0157715.0
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" - ], - "text/plain": [ - " Country Year Population\n", - "0 Aruba 1960-01-01 56225.0\n", - "1 Aruba 1961-01-01 56695.0\n", - "2 Aruba 1962-01-01 57032.0\n", - "3 Aruba 1963-01-01 57360.0\n", - "4 Aruba 1964-01-01 57715.0" - ] - }, - "execution_count": 83, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_world_tidy = (df_world\n", - " .set_index(['Data Source'])\n", - " .stack(0)\n", - " .rename('Population')\n", - " .to_frame()\n", - " .reset_index()\n", - " .rename(columns={'level_1':'Year', 'Data Source':'Country'})\n", - " .assign(Year=lambda df:pd.to_datetime(df.Year)))\n", - "\n", - "df_world_tidy.iloc[:5,:5]" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [], - "source": [ - "to_plot = (df_world_tidy\n", - " .set_index(['Country', 'Year'])\n", - " .unstack(level=0)\n", - " .loc[:, (slice(None), ['Norway', 'Sweden'])])" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Return Index with requested level removed\n", - "to_plot.columns = to_plot.columns.droplevel(0)\n", - "\n", - "(to_plot / 10**6).plot(grid=True, figsize=(10, 5));\n", - "plt.ylabel('Population (millions)'); \n", - "plt.ylim([0, 11]); plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (6.4) Pivoting and melting\n", - "\n", - "We'll show how pivoting and meling can help us create data for plotting." - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
CountryYearPopulation
0Aruba1960-01-0156225.0
1Aruba1961-01-0156695.0
2Aruba1962-01-0157032.0
\n", - "
" - ], - "text/plain": [ - " Country Year Population\n", - "0 Aruba 1960-01-01 56225.0\n", - "1 Aruba 1961-01-01 56695.0\n", - "2 Aruba 1962-01-01 57032.0" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# The tidy data set\n", - "df_world_tidy.head(3)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `.pivot()` method is more powerful than unstack. Both move rows up to the columns." - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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CountryAfghanistanAlbaniaAlgeriaAmerican SamoaAndorra
Year
1960-01-019345868.01711319.011690153.021117.015370.0
1961-01-019533954.01762621.011985136.021882.016412.0
1962-01-019731361.01814135.012295970.022698.017469.0
1963-01-019938414.01864791.012626952.023520.018549.0
1964-01-0110152331.01914573.012980267.024321.019647.0
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" - ], - "text/plain": [ - "Country Afghanistan Albania Algeria American Samoa Andorra\n", - "Year \n", - "1960-01-01 9345868.0 1711319.0 11690153.0 21117.0 15370.0\n", - "1961-01-01 9533954.0 1762621.0 11985136.0 21882.0 16412.0\n", - "1962-01-01 9731361.0 1814135.0 12295970.0 22698.0 17469.0\n", - "1963-01-01 9938414.0 1864791.0 12626952.0 23520.0 18549.0\n", - "1964-01-01 10152331.0 1914573.0 12980267.0 24321.0 19647.0" - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Demonstrating the pivot method\n", - "# Return reshaped DataFrame organized by given index / column values.\n", - "df_world_pivot = df_world_tidy.pivot(index='Year', columns='Country', values='Population')\n", - "df_world_pivot.iloc[:5, :5]" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "metadata": {}, - "outputs": [], - "source": [ - "# Drop every country where there are any missing values\n", - "df_world_pivot = df_world_pivot.dropna(how='any', axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
CountryAfghanistanAlbaniaAlgeriaAmerican SamoaAndorra
Year
1960-01-019345868.01711319.011690153.021117.015370.0
1961-01-019533954.01762621.011985136.021882.016412.0
1962-01-019731361.01814135.012295970.022698.017469.0
1963-01-019938414.01864791.012626952.023520.018549.0
1964-01-0110152331.01914573.012980267.024321.019647.0
\n", - "
" - ], - "text/plain": [ - "Country Afghanistan Albania Algeria American Samoa Andorra\n", - "Year \n", - "1960-01-01 9345868.0 1711319.0 11690153.0 21117.0 15370.0\n", - "1961-01-01 9533954.0 1762621.0 11985136.0 21882.0 16412.0\n", - "1962-01-01 9731361.0 1814135.0 12295970.0 22698.0 17469.0\n", - "1963-01-01 9938414.0 1864791.0 12626952.0 23520.0 18549.0\n", - "1964-01-01 10152331.0 1914573.0 12980267.0 24321.0 19647.0" - ] - }, - "execution_count": 89, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Compute the relative change since 1960\n", - "df_world_rel = (df_world_pivot / df_world_pivot.iloc[0, :])\n", - "df_world_pivot.iloc[:5, :5]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `.melt()` method is more powerful than stack. Both move columns up to the index.\n", - "\n", - "> `unstack` and `stack` are inverses. \n", - " `pivot` and `melt` are inverses." - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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YearCountryPopulation
01960-01-01Afghanistan1.000000
11961-01-01Afghanistan1.020125
21962-01-01Afghanistan1.041247
31963-01-01Afghanistan1.063402
41964-01-01Afghanistan1.086291
\n", - "
" - ], - "text/plain": [ - " Year Country Population\n", - "0 1960-01-01 Afghanistan 1.000000\n", - "1 1961-01-01 Afghanistan 1.020125\n", - "2 1962-01-01 Afghanistan 1.041247\n", - "3 1963-01-01 Afghanistan 1.063402\n", - "4 1964-01-01 Afghanistan 1.086291" - ] - }, - "execution_count": 90, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_world_rel = df_world_rel.reset_index().melt(id_vars='Year', value_name='Population')\n", - "df_world_rel.iloc[:5, :5]" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "top_n = 5\n", - "countries = (df_world_rel\n", - " .groupby('Country')\n", - " .max()\n", - " .Population\n", - " .nlargest(top_n)\n", - " .index)\n", - "\n", - "(df_world_rel\n", - " .pivot(index='Year', columns='Country', values='Population')\n", - " .loc[:, countries].plot(figsize=(10, 5)))\n", - "plt.legend(bbox_to_anchor=(1,1));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (6.5) Merging" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "![](https://www.dofactory.com/Images/sql-joins.png)\n", - "\n", - "*Image source is https://www.dofactory.com/sql/join*\n", - "\n", - "> **Tip.** Learning SQL is likely worth your time, see for instance [w3schools.com](https://www.w3schools.com/sql/default.asp) and [sqlzoo.net](https://sqlzoo.net/wiki/SELECT_names)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Add a column showing every directors average imdb score." - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_imdb_score
director_name
Aaron Schneider7.1
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" - ], - "text/plain": [ - " director_imdb_score\n", - "director_name \n", - "Aaron Schneider 7.1" - ] - }, - "execution_count": 92, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "director_means = (df.groupby(df.director_name).mean().round(1)\n", - " .loc[:, ['imdb_score']]\n", - " .rename(columns={'imdb_score':'director_imdb_score'}))\n", - "director_means.head(1)" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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director_namegrossmovie_titlecountrycontent_ratingimdb_scoredirector_imdb_score
0James Cameron760505847.0AvatarUSAPG-137.97.9
1Gore Verbinski309404152.0Pirates of the Caribbean: At World's EndUSAPG-137.17.0
2Sam Mendes200074175.0SpectreUKPG-136.87.5
3Christopher Nolan448130642.0The Dark Knight RisesUSAPG-138.58.4
5Andrew Stanton73058679.0John CarterUSAPG-136.67.7
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" - ], - "text/plain": [ - " director_name gross movie_title \\\n", - "0 James Cameron 760505847.0 Avatar  \n", - "1 Gore Verbinski 309404152.0 Pirates of the Caribbean: At World's End  \n", - "2 Sam Mendes 200074175.0 Spectre  \n", - "3 Christopher Nolan 448130642.0 The Dark Knight Rises  \n", - "5 Andrew Stanton 73058679.0 John Carter  \n", - "\n", - " country content_rating imdb_score director_imdb_score \n", - "0 USA PG-13 7.9 7.9 \n", - "1 USA PG-13 7.1 7.0 \n", - "2 UK PG-13 6.8 7.5 \n", - "3 USA PG-13 8.5 8.4 \n", - "5 USA PG-13 6.6 7.7 " - ] - }, - "execution_count": 93, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.merge(director_means, how='left', left_on='director_name', right_index=True).head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The inner join, or `merge(how='inner')` can be used if you want the intersection." - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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imdb_score_USAimdb_score_Canada
director_name
Adam Shankman6.25.5
Andrzej Bartkowiak5.83.7
Atom Egoyan6.37.0
Bennett Miller7.67.4
Bob Clark2.56.2
\n", - "
" - ], - "text/plain": [ - " imdb_score_USA imdb_score_Canada\n", - "director_name \n", - "Adam Shankman 6.2 5.5\n", - "Andrzej Bartkowiak 5.8 3.7\n", - "Atom Egoyan 6.3 7.0\n", - "Bennett Miller 7.6 7.4\n", - "Bob Clark 2.5 6.2" - ] - }, - "execution_count": 94, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# For every director which has made movies in the USA and Cananda\n", - "# get average imdb scores for both locations\n", - "\n", - "american_directors = (df[df.country == 'USA'].groupby('director_name')\n", - " .mean().imdb_score.to_frame())\n", - "canadian_directors = (df[df.country == 'Canada'].groupby('director_name')\n", - " .mean().imdb_score.to_frame())\n", - "\n", - "(american_directors.merge(canadian_directors, how='inner', \n", - " left_index=True, right_index=True, \n", - " suffixes=('_USA', '_Canada'))\n", - " .round(1)\n", - " .head())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (7) Plotting" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (7.1) Built-in `plot()` methods\n", - "\n", - "\n", - "Excellent for creating plots quickly. The downside is less control.\n", - "\n", - "The built in plot options are:\n", - "\n", - "- `line` : line plot (default)\n", - "- `bar` : vertical bar plot\n", - "- `barh` : horizontal bar plot\n", - "- `hist` : histogram\n", - "- `box` : boxplot\n", - "- `kde` : Kernel Density Estimation plot\n", - "- `density` : same as ‘kde’\n", - "- `area` : area plot\n", - "- `pie` : pie plot\n", - "- `scatter` : scatter plot\n", - "- `hexbin` : hexbin plot\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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GklnAQnji/r9ZVXUJ8EZg36btL4BtR9jPLGBNU160Af3aFrgnyRZ0ZvokSZJaabzu6Xs1cPZ6dV8EXgN8HrgZ+AFwY7NsW+CiJDOBAP+7qT8f+HCS0+kEyfWdCXwhyRrg28Buo/Trr4HrgbuBFYwcKCVJkqasVFW3+9BzZsyeV7MXLRlymT/DJkmSekmSZVU1f7R2/iKHJElSC4znV7ZMGXvNmUW/M3qSJGkKcaZPkiSpBQx9kiRJLWDokyRJagFDnyRJUgsY+iRJklrA0CdJktQChj5JkqQWMPRJkiS1gKFPkiSpBQx9kiRJLWDokyRJagFDnyRJUgsY+iRJklpgerc70ItWrFlL3xkXP/F51dmHd7E3kiRJY+dMnyRJUgsY+iRJklqg50JfkrckWZnk5iTLkzx/E7bxh0nO2Bz9kyRJmox66p6+JC8EXgnsX1WPJtkJeOrGbqeqvgJ8Zbz7J0mSNFn12kzfbOC+qnoUoKruq6qfJFmV5O+T3NC8ng2Q5Igk1ye5McnXk+zS1J+c5Nym/PEk5yT5VpIfJjm2a0cnSZLUJb0W+i4Dnp7k+0n+OclLBi37eVUdBJwLLGnqrgFeUFX7AecDbx5mu7OBQ+jMIp69ebouSZLUu3rq8m5VPZTkAOB/AAuAzw26N++zg97f15TnNm1m07kMfNcwm/5yVT0O3DowG7i+JIuBxQDTfmvnMR+LJElSL+m1mT6qal1VXV1VfwO8HjhmYNHgZs37+4Fzq2ov4HXAzGE2++igcobZ79Kqml9V86dtNWvTD0CSJKkH9VToS/KcJPMGVe0L3N2Ujxv0fl1TngWsacqLNn8PJUmSJqeeurwLbAO8P8l2wK+BO+hccn0lMCPJ9XSC6qub9mcCX0iyBvg2sNuE91iSJGkSSFWN3qrLkqwC5lfVfROxvxmz59XsRUue+OzPsEmSpF6VZFlVzR+tXU9d3pUkSdLm0WuXd4dUVX0Tub+95syi39k9SZI0hTjTJ0mS1AKGPkmSpBYw9EmSJLWAoU+SJKkFDH2SJEktYOiTJElqAUOfJElSCxj6JEmSWsDQJ0mS1AKGPkmSpBYw9EmSJLWAoU+SJKkFDH2SJEktYOgbwoo1a+k742L6zri4212RJEkaF4Y+SZKkFjD0SZIktYChT5IkqQV6KvQl+e0k5ye5M8mtSS5JsjjJV4dp/5Eku090PyVJkiab6d3uwIAkAS4EPlFVxzd1+wJHDLdOVf3xBHVPkiRpUuulmb4FwGNV9aGBiqpaDnwT2CbJBUluT3JeExBJcnWS+U35oSTvTHJTkm8n2aWpPyLJ9UluTPL1gXpJkqQ26aXQtyewbJhl+wFvBHYHngkcPESbrYFvV9U+wDeA05r6a4AXVNV+wPnAm4faQXMZuT9J/7qH1276UUiSJPWgXgp9I7mhqlZX1ePAcqBviDa/Agbu/Vs2qM1c4NIkK4C/APYYagdVtbSq5lfV/GlbzRrPvkuSJHVdL4W+lcABwyx7dFB5HUPfi/hYVdUQbd4PnFtVewGvA2aOQ18lSZImlV4KfVcCM5IMXJYlyYHAS8a43VnAmqa8aIzbkiRJmpR6JvQ1s3RHA7/ffGXLSuBM4Cdj3PSZwBeSfBO4b4zbkiRJmpTy5BVRDZgxe17NXrQEgFVnH97l3kiSJA0vybKqmj9au56Z6ZMkSdLm0zNfztxL9pozi35n+CRJ0hTiTJ8kSVILGPokSZJawNAnSZLUAoY+SZKkFjD0SZIktYChT5IkqQUMfZIkSS1g6JMkSWoBQ58kSVILGPokSZJawNAnSZLUAoY+SZKkFjD0DWHFmrX0nXFxt7shSZI0bgx9kiRJLWDokyRJagFDnyRJUguMGvqSPLTe55OTnLv5ugRJPp7k2Ka8Q5Ibk5yyOfcpSZI0lfX0TF+SWcClwNKq+li3+yNJkjRZjSn0JXlGkiuS3Ny8/05T//Ek5yT5VpIfDpq1e0qSf06yMslXk1wysGwI2wD/Bnymqj7YrJ8k705yS5IVSY5r6g9NcnWSC5LcnuS8JGmWvaKpu6bp01fHcsySJEmT0YaEvi2TLB94Ae8YtOxc4JNVtTdwHnDOoGWzgUOAVwJnN3WvAvqAvYA/Bl44wn7fC1xTVe8bVPcqYF9gH+D3gHcnmd0s2w94I7A78Ezg4CQzgX8BDquqQ4Cdh9tZksVJ+pP0r3t47QjdkiRJmnw2JPT9V1XtO/AC3jZo2QuBzzTlT9EJeQO+XFWPV9WtwC5N3SHAF5r6/wCuGmG/VwJHJnnaoLpDgM9W1bqq+inw78CBzbIbqmp1VT0OLKcTLp8L/LCq7mrafHa4nVXV0qqaX1Xzp201a4RuSZIkTT7jfU9fDSo/Oqic9d43xPnAB4FLkmy7AesP3t86YPpG7k+SJGnKGmvo+xZwfFM+AbhmlPbXAMc09/btAhw6UuOqWgJcAVyY5KnAN4DjkkxLsjPwYuCGETZxO/DMJH3N5+NG6Z8kSdKUNNbQdzpwSpKbgROBN4zS/ovAauAWOvfaXQ+MeANdVf0l8GM6l48vAm4GbqJz+ffNzWXi4db9L+DPgK8luQb46Wj7kyRJmopSVaO3Gs8dJttU1UNJdqQzS3fwSMFtHPcX4APAD9Z7OOS/mTF7Xs1etIRVZx++ubolSZI0LpIsq6r5o7WbPhGdWc9Xk2wHPBX4280Z+BqnJVnU7O9GOjOMkiRJrTLhM32Twfz586u/v7/b3ZAkSRrVhs709fQvckiSJGl8GPokSZJawNAnSZLUAoY+SZKkFjD0SZIktYChT5IkqQUMfZIkSS1g6JMkSWoBQ58kSVILGPokSZJaoBu/vTspPfbYY6xevZpHHnmk213pWTNnzmTu3LlsscUW3e6KJElaj6FvA61evZptt92Wvr4+knS7Oz2nqrj//vtZvXo1u+22W7e7I0mS1uPl3SGsWLOWvjMu/o26Rx55hB133NHAN4wk7Ljjjs6ESpLUowx9G8HANzLHR5Kk3mXokyRJagHv6dtE61/+HatVZx8+rtvbWEuWLGHx4sVstdVWXe2HJEnaPHpupi/JQ93uQxstWbKEhx9+eMhl69atm+DeSJKk8dZzoU/D++QnP8nee+/NPvvsw4knnsjdd9/NwoUL2XvvvVm4cCE/+tGPADj55JO54IILnlhvm222AeDqq6/m0EMP5dhjj+W5z30uJ5xwAlXFOeecw09+8hMWLFjAggULnljnbW97G89//vM566yzOProo5/Y3uWXX86rXvWqCTxySZI0Vj15eTfJNsBFwPbAFsBbq+qiJH3A14Drgf2A7wMnVdXDSd4GHAFsCXwLeF1VVZKrm/YLgO2AU6vqmxN7RGO3cuVK3vnOd3Lttdey00478cADD7Bo0SJOOukkFi1axEc/+lFOP/10vvzlL4+4nRtvvJGVK1ey6667cvDBB3Pttddy+umn8973vperrrqKnXbaCYBf/vKX7LnnnrzjHe+gqnje857Hvffey84778zHPvYxTjnllIk4bEmSNE56dabvEeDoqtqfTlh7T558NPQ5wNKq2hv4OfBnTf25VXVgVe1JJ/i9ctD2plfVQcAbgb8ZaodJFifpT9K/7uG1m+GQxubKK6/k2GOPfSKU7bDDDlx33XW85jWvAeDEE0/kmmuuGXU7Bx10EHPnzuUpT3kK++67L6tWrRqy3bRp0zjmmGOAzlO5J554Ip/+9Kd58MEHue666zjssMPG58AkSdKE6MmZPiDAu5K8GHgcmAPs0iz7cVVd25Q/DZwO/COwIMmbga2AHYCVwL827b7UvC8D+obaYVUtBZYCzJg9r8bzYMZDVY36lSgDy6dPn87jjz/+xHq/+tWvnmgzY8aMJ8rTpk3j17/+9ZDbmjlzJtOmTXvi8ymnnMIRRxzBzJkz+aM/+iOmT+/VU0eSJA2lV2f6TgB2Bg6oqn2BnwIzm2XrB7JKMhP4Z+DYqtoL+PCg9gCPNu/r6N2gO6KFCxfy+c9/nvvvvx+ABx54gBe96EWcf/75AJx33nkccsghAPT19bFs2TIALrroIh577LFRt7/tttvyi1/8Ytjlu+66K7vuuitnnXUWJ5988hiPRpIkTbReDUCzgJ9V1WNJFgDPGLTsd5K8sKquA14NXMOTAe++5n7AY4EL2Iwm+itW9thjD97ylrfwkpe8hGnTprHffvtxzjnn8NrXvpZ3v/vdT9xrB3Daaadx5JFHctBBB7Fw4UK23nrrUbe/ePFiDjvsMGbPns1VV101ZJsTTjiBe++9l913331cj02SJG1+qeqdK5lJptOZ1XsOnUuzWwDLgYOBgZvILgG+AbwI+AFwYvMgx1nA8cAq4MfA3VV1ZvMgx5uqqj/JTkB/VfWN1I8Zs+fV7EVLfiPY3XbbbTzvec8br0OdlF7/+tez3377ceqppw7bxnGSJGliJVlWVfNHa9drM317AHdW1X3AC9df2Dy9+3hV/cn6y6rqrcBbh6g/dFD5Poa5p08jO+CAA9h66615z3ve0+2uSJKkTdAzoS/Jn9B5KOON3e6L/ruBewQlSdLk1DMPclTVh6pq96q6bIQ2q5qvZNms9poza8h79nrpUngvcnwkSepdPRP6et3MmTO5//77DTbDqCruv/9+Zs6cOXpjSZI04Xrm8m6vmzt3LqtXr+bee+/tdld61syZM5k7d263uyFJkoZg6NtAW2yxBbvttlu3uyFJkrRJvLwrSZLUAoY+SZKkFjD0SZIktUBP/SJHr0jyC+B73e7HFLETcF+3OzEFOI7jx7EcP47l+HEsx08bx/IZVbXzaI18kGNo39uQnzPR6JL0O5Zj5ziOH8dy/DiW48exHD+O5fC8vCtJktQChj5JkqQWMPQNbWm3OzCFOJbjw3EcP47l+HEsx49jOX4cy2H4IIckSVILONMnSZLUAoY+SZKkFjD0DZLk5Um+l+SOJGd0uz+TQZJVSVYkWZ6kv6nbIcnlSX7QvG/f1CfJOc343pxk/+72vruSfDTJz5LcMqhuo8cuyaKm/Q+SLOrGsXTbMGN5ZpI1zbm5PMkrBi37v81Yfi/JHwyqb/XfgCRPT3JVktuSrEzyhqbe83IjjTCWnpcbKcnMJDckuakZy7c39bslub45xz6X5KlN/Yzm8x3N8r5B2xpyjFujqnx17mucBtwJPBN4KnATsHu3+9XrL2AVsNN6df8AnNGUzwD+vim/Avg3IMALgOu73f8uj92Lgf2BWzZ17IAdgB8279s35e27fWw9MpZnAm8aou3uzb/vGcBuzb/7af4NKIDZwP5NeVvg+814eV6O31h6Xm78WAbYpilvAVzfnG+fB45v6j8E/GlT/jPgQ035eOBzI41xt49vIl/O9D3pIOCOqvphVf0KOB84sst9mqyOBD7RlD8BHDWo/pPV8W1guySzu9HBXlBV3wAeWK96Y8fuD4DLq+qBqvpP4HLg5Zu/971lmLEczpHA+VX1aFXdBdxB599/6/8GVNU9VfXdpvwL4DZgDp6XG22EsRyO5+UwmvProebjFs2rgJcCFzT165+XA+frBcDCJGH4MW4NQ9+T5gA/HvR5NSP/A1VHAZclWZZkcVO3S1XdA50/fMDTmnrHeHQbO3aO6che31x2/OjAJUkcyw3SXBLbj86siuflGKw3luB5udGSTEuyHPgZnf+JuBN4sKp+3TQZPC5PjFmzfC2wI46loW+QDFHn99mM7uCq2h84DPjzJC8eoa1jvOmGGzvHdHgfBJ4F7AvcA7ynqXcsR5FkG+CLwBur6ucjNR2izrEcZIix9LzcBFW1rqr2BebSmZ173lDNmnfHchiGvietBp4+6PNc4Cdd6sukUVU/ad5/BlxI5x/jTwcu2zbvP2uaO8aj29ixc0yHUVU/bf5D8TjwYZ68jONYjiDJFnRCynlV9aWm2vNyEww1lp6XY1NVDwJX07mnb7sk05tFg8fliTFrls+ic/tH68fS0Pek7wDzmqeBnkrn5s+vdLlPPS3J1km2HSgDLwNuoTNuA0/rLQIuaspfAU5qnvh7AbB24JKRnrCxY3cp8LIk2zeXiV7W1LXeeveLHk3n3ITOWB7fPOG3GzAPuAH/BtDc9/T/gNuq6r2DFnlebqThxtLzcuMl2TliP5QHAAAA/UlEQVTJdk15S+D36NwjeRVwbNNs/fNy4Hw9Friyqorhx7g9uv0kSS+96DyJ9n069wq8pdv96fUXnafJbmpeKwfGjM69E1cAP2jed2jqA3ygGd8VwPxuH0OXx++zdC7vPEbn/0BP3ZSxA15L54bkO4BTun1cPTSWn2rG6mY6f+xnD2r/lmYsvwccNqi+1X8DgEPoXO66GVjevF7heTmuY+l5ufFjuTdwYzNmtwBva+qfSSe03QF8AZjR1M9sPt/RLH/maGPclpc/wyZJktQCXt6VJElqAUOfJElSCxj6JEmSWsDQJ0mS1AKGPkmSpBYw9EmSJLWAoU+SJKkF/j+TPMzpZFMipQAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot countries by number of occurences\n", - "(df.country\n", - " .value_counts()\n", - " .head(n=10)\n", - " .sort_values(ascending=True)\n", - " .to_frame()\n", - " .plot.barh(figsize=(10, 5)));" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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kCL8yoTOScsArEXFQkW0PAg9HxLh0lvnHgAAGALtExHPd9D0eGA/Q1NQ08qTzTso4+sbVPKCZ2UtnVzuMuuF8lc65Ko/zVZ7u8jVy45G9GE3ta29vZ/DgwdUOoy70dq5aW1tnRsT23bXzSGbX3gT6dbKtX7q9w2vA54F7gdslfTQiXu2s44iYAkwBGLblsJjwxIRsIu4D2ka04XyVzvkqnXNVHuerPN3lK0Z50CdfLpejpaWl2mHUhVrNld+T2bW5wEadbNsYeDl/RUQ8BewFbAL8XtKgyoZnZmZmVptcZHbtT8BISZvmr5S0E7Bhuv1t0ndi7kfyfOY1kjxabGZmZn2Oi8yuXQY8C0yXdISkT0g6GrgJ+DPwh2I7RUQOGA3sCVwiyX8z0szMzPoUF5ldiIh24OMkI5Y/ICkqTwZ+A+wVEW91se+1wNHAGOCsykdrZmZmVjt8K7cbEfECMK6bNkW3R8T/Af+XfVRmZmZmtc1FZg0Y1H8QMdGzCkuVy+U8C7MMzlfpnKvyOF/lcb6sr/HtcjMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy9zq1Q7AYNHyRWiyqh1G3Wgb0Ubr5NZqh1E3nK/SOVflKSVfMTF6KRozqzU1P5IpaZKkKPJ1R7VjMzMzM7Pi6mUk83Xg00XWmZmZmVkNqpci882IuL+UhpLWjIjFlQ7IzMzMzDpX87fLuyJp9fTW+dclnSdpLvDXdNu+ku6QNFfSG5Luk/TJgv3PkPSSpO0lzZC0SNJDknYpcqwvS3pY0hJJcyT9VtKQvO27SZqe9vGqpIskDa54EszMzMxqUN0UmWlBmf+VP1PmJKAJGAN8I123BXADMBo4EJgB/EHSTgVdDwYuBS5M270JXCdpYN6xJ6Xb7wQ+B3wVWAgMSrd/HJgGPJ/2cQLwWeDnmZy8mZmZWZ2pl9vlQ4HlBev2AHLp97Mj4tD8jRFxXsf3klYD7gI+AHyJpODssBZwdERMT9vOBR4APgrcIWkoSRHbFhHfytvvd3nf/xC4OyJG5R3zReA2SZMi4l/lna6ZmZlZfauXIvN14JMF6x7P+/7mwh0kDQO+B3wC2BjoGPnsV9B0CfCnvOVH08/m9HMXYADJaOc7pLfEdwK+LCk/n9OBt4CRwDuKTEnjgfEATU1NtI1oK9a9FdE8oNn5KoPzVTrnqjyl5CuXy/VOMHWgvb3d+SiD81W6Ws1VvRSZb0bEg4Ur84q6OQXr+wG/BwYCpwJPkdze/h6wdkE3r0dE/ovclqWfHbfLh6afL3YS21CSAnZK+lVoWLGdImJl+2FbDosJT0zopHsr1DaiDeerdM5X6Zyr8pSSrxjl92R2yOVytLS0VDuMuuF8la5Wc1UvRWZ3Cn+LvQfYFtgjIla+T1PSmj3o+9X0c2NgfpHtr6WfpwJ/KLL9+R4c08zMzKyuNUqRWaijmFzasULSlsBHgJll9nUvyS31sSTPZr5NRLwh6QFgRESc2bNwzczMzBpLoxaZjwAvAD+WdBqwDnA6MLvcjiJinqTvAZPTGee3khSx+wCnRMQc4FvA7emE92uBdmBzYG/g2xHxn1U/JTMzM7P60ZBFZkQskXQAcAFJ0fccSZG5J7BVD/r7rqRXgONIXl/0GnA3yXOeRERO0m7AJODXJJOLniEpSOeu6vmYmZmZ1ZuaLzIjYhJJ8VZs25v8d9Z44bYZwPYFq39V0OZUkmcpu+0zIi4keVdmZ3HeR1LEmpmZmfV5NV9k9gWD+g8iJnoGZqlyuZxnrJbB+Sqdc1Ue58vMulI3f/HHzMzMzOqHi0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPL3OrVDsBg0fJFaLKqHUbdaBvRRuvk1mqHUTecr9I5VxATo9ohmFmDqPhIpqTPSbpd0quSlkl6XtJVknat9LHNzMzMrDoqWmRK+jFwLfA8cCTwSeAkYAhwj6R3VfL4ZmZmZlYdFbtdLmk/4HjgiIiYWrD5V5L2BRavQv/9gbciYkXPozQzMzOzSqjkSObxwANFCkwAIuKmiHgBQNJqkk6S9KSkpZKekDQ2v72knKRrJI2X9B9gCbCJpEmSXpG0k6QHJS2WdI+kLSRtIOl6Se2SHpP0iYI+D0/bzpP0mqS7JG1f0GZq2u8ekv4haWG6zzZ5ba6WdFfhOUqaLGlOWhCbmZmZ9RkVKTIlrQ7sDNxe4i4/BU4FpgB7A9cBl0jap6DdrsBXgW8D+wKvp+sHpfv+GBgFbAb8CrgSuAc4gOSW/dWSBuX1Nxy4DDgYOBSYDUyXtGXBcTcDfgScmfa/AfBbSR2zdX4O7CZpi7wcCDgc+HVELC8xD2ZmZmYNoVK3y4cCA4Dn8lemhVe/vFUrgHeRFI5HRMQv0/V3SNoYmAj8Pq/9usCHIuKlvD4B1gSOi4i703WbABcAEyOiLV03G3gE2A24FSAiTs/rZzVgGrADcBiwchuwHrBrRPw7r+11wHuAf6X7PQeMS2MGaCUpYi/tOlVmZmZmjadSRWbHCF/huzBOJBkR7HAssBx4C7guHQHt8EdglKR+ec9dzswvMPMsA/6Ut/xk+nlnkXWbrgxSei/wPWAXktHJDiMK+p/VUWCmHk0/m4F/RcRbkqYCh0uaFBFBUnA+GBEPF4kXSeOB8QBNTU20jWgr1syKaB7Q7HyVwfkqnXMFuVyu5Lbt7e1lte/rnK/yOF+lq9VcVarIfAVYSlKE5fsVkEu/fyD9bCIZ3Xyd4jYmuY0NMKeTNgsi4q285WXp5/yOFRGxLB31HAggaQjJ7fw5wAnAMyTPef68o02e+QXLHf3nt7sU+A7QKukB4EBgQifxEhFTSG7xM2zLYTHhiU6bWoG2EW04X6VzvkrnXEGMKv09mblcjpaWlsoF02Ccr/I4X6Wr1VxVpMiMiDcl3Qd8Cjgtb/0c0kLxv48zMg94k+R5y7d4p5fzu84wzJ1JiuA9IuJfHSslrdOTziJilqQ7SEYwtyB53vXKDOI0MzMzqzuV/Is/5wLXSxoTEb/qot2dJCOZ60TEtArGU2jN9HNpxwpJu5A8Rzmzh33+ArgE2Aa4PiIKR0DNzMzM+oSKFZkRcYOkc4GpklqBm0huow8F9kibtUfE45L+D7hK0lnAgyS3obcBRkTEkRUK8X6gHbg4PW4zMIlkFnpPXQ/8DPgwcPKqBmhmZmZWryr6t8sj4huSpgNfIxnlGwLMBe4DPhMRt6ZNjwaeAI4imdX9Bsnkml9UMLY5kg4G2oAbgH8DXwG+tQp9LpV0K/Bx4I5MAjUzMzOrQxUtMgEi4jqS1/101SZIbq+f20Wblk7WTyIZgcxfl+O/M9zz16tg+TbgtoJmtxS0GVekn1nF+k9nx7cClxRMRDIzMzPrUypeZPYFktYAPkjyQvehwEXl7D+o/yBiYpZzmhpbLpcrawZsX+d8lc65MjPLjovMbGwC/IVkJvyXI2J2N+3NzMzMGpqLzAx0dvvczMzMrK+qyN8uNzMzM7O+zUWmmZmZmWXORaaZmZmZZc5FppmZmZllzkWmmZmZmWXORaaZmZmZZc5FppmZmZllzkWmmZmZmWXORaaZmZmZZc5FppmZmZllzkWmmZmZmWXOf7u8BixavghN9p8+L1XbiDZaJ7dWO4y64XyVrlFzFROj2iGYWR9UcyOZkg6QdKek+ZKWSnpC0hmSmqodWwdJbZJmVTsOMzMzs1pVU0WmpLOBq4GngDHAp4AfA/sCF1cxNDMzMzMrQ83cLpe0L3AC8KWIuCRv092SppAUnGZmZmZWB2ppJPMbwEMFBSYAEbEiIm4FkPQDSf+U1C5ptqTLJW2U317SrPSW9jfSNq9JukrSunlt1pJ0vqTHJS2S9LSkCyStXdDXupKukLRQ0ouSTimMT9LGki6R9JSkxXm3+NfILDtmZmZmdaQmRjIl9Qd2Ac4uofkGwPeAF4D1gROBOyV9ICJW5LX7PPAPYDzQDJyT7ve1dPsgoB9wCjAXGJZ+fzWwZ14/lwItwPHAS8AE4F3Am3ltmoB5JCOxrwEjgElpfF8u4ZzMzMzMGooiqj/rMB2JfBH4SkRcVMZ+/YCNgNnAbhExPV0/C1gBvCci3kzXnQt8ISI26qSv1YGdgHuAzSPiWUnbAA+n+/0mbTcYeBZ4IyKGd9HX54FLgLUjYlmRNuNJCmCamppGnnTeSaWedp/XPKCZ2UtnVzuMuuF8la5RczVy45EV6be9vZ3BgwdXpO9G5HyVx/kqXW/nqrW1dWZEbN9du5oYyczTbcUraS/gO8A2QP6t7RHA9LzluzoKzNSjwAaS1ugo+iSNIRl9fDewVkFfzwI7pMs3rgwwol3SNJKCtCMmAV8nKRq3AAbm9bUZ8OQ7TjRiCjAFYNiWw2LCExO6O3VLtY1ow/kqnfNVukbNVYyqzGBCLpejpaWlIn03IuerPM5X6Wo1V7XyTOarwFKSgqxTknYgKfhmk8w+3xn4SLp5YEHz+QXLywABa6R97Q9cBtwHHJz2s39BXxsBCyJicUFfLxcsH09yq/86YD9gR+DoTuIyMzMza3g1MZIZEcsl3UvyLOSpXTTdn+T5yUMivc8vafMeHvZgYEZEdDyjiaTdCtq8BAyRtGZBoblBkb6ujoiVk4Ikva+HcZmZmZnVvVoZyQQ4F9he0tjCDZJWk/RpYE1gebz9QdLRPTzemiSjp/kK+3og/fxsXiyDgT160JeZmZlZn1ETI5kAEXGTpHOAX0jaFbgBaAe2Br4CzCJ5Ifvx6SSem0hmpB/Ww0NOAy5IX0k0A/gMsHtBTI9IuhG4MH210YvAN4FFRfo6TtIM4D8kBeZWPYzLzMzMrO7VTJEJEBEnSvozcAxwBckI4SyS5zDbIuIlSd8GjgWOInmech/giR4c7iJgS5IJOwNJCsVDgfsL2o0DLiQZaW0HLiAZ4Twor83pJK8rOiNd/h1wHEkhbGZmZtbn1FSRCRAR1wLXdrH9LOCsgtUqaDO8yH5Tgal5yytI3nlZOJW0sK/XgC8UCWVCXpt24IgibVRk3TsM6j+ImFj9V0nVi1wuV7HZso3I+Sqdc2Vmlp1aeibTzMzMzBqEi0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8uci0wzMzMzy5yLTDMzMzPLnItMMzMzM8vc6tUOwGDR8kVosqodRt1oG9FG6+TWaodRN5yv0mWRq5gYGUVjZlbfem0kU4mnJYWkrSrQ/xqSJknaLuN+p0p6MG95XHoOg7M8jpmZmVkj6c3b5TsDw9Pvv1CB/tcAJgKZFplF3ExyLosqfBwzMzOzutWbReYoYCEwI/2+aiSt2dN9I2JuRNwfEW9lGZOZmZlZI+mVIlNSP+Bg4EbgEuB9krbN2z5J0itF9gtJx+Qtf1bSTEkLJb0maYak3dLNC9LPS9P9QtLw9CskjZZ0maT5wE1pf4dLukfSvLS/uyRt3825vON2uaQfSPqnpHZJsyVdLmmjHqbLzMzMrO711kjmJ4ANgauAa4DllDmaKeld6b53AvsCo4HfA+vlHQPgDJLb2TsDL+Z10UZSiB4MfC9dNxy4LF13KDAbmC5py3JiAzZI+9wbOB7YErgzLa7NzMzM+hxFVH4mpKRLgP2BDSNimaSbgfcBW0ZESJoEHBMRTQX7BXBsRJwv6SDgoogY2skxBpMUkUdExNS89cOBp4HrI2L/LmJcjaTofhi4IiJOT9dPBd4fEduny+OAS4EhEdFepJ9+wEYkBetuETG9k+ONB8YDNDU1jTzpvJM6C80KNA9oZvbS2dUOo244X6XLIlcjNx6ZUTS1r729ncGDPQeyVM5XeZyv0vV2rlpbW2d21EVdqfgrjCQNICkwr4uIZenqK4FfAR8B7iuxq38C60j6JXA5cG9ELCwjlJuLxPZekhHIXUgI9bjtAAAcKUlEQVRGIzuMKKNfJO0FfAfYBli7oJ+iRWZETAGmAAzbclhMeGJCOYfs09pGtOF8lc75Kl0WuYpRfecVRrlcjpaWlmqHUTecr/I4X6Wr1Vz1xu3yvYB1gVskrStpXSAHLKWMW+YR8TiwH8mt6FuAVyRdIWn9EruYk78gaQhwOzAMOAH4GLAD8HdgYKlxSdqB5FnT2cAYktv0H0k3l9yPmZmZWSPpjZexdxSSVxfZ9nlJ3wCWkLyCaCVJ/1PYOCJuBm6WtA7J84/nAj+ltFciFQ4v7Aw0A3tExL/yjrtOCX3l2x+YCxwS6bMHkjYvsw8zMzOzhlLRIjN9TnIfktvjUwo2fwg4B2glGQUcImnTiHg+3f6pzvqNiNeBK9KZ5TunqztuxZc6etjxGqOlefHuQjIZaGaJfXT0szze/nDr6DL2NzMzM2s4lR7J3A8YBPwkImbkb5B0L3AKyUjnt4HFwCWSzga2AL5S0P7LJAXlbcALwLtJZoVfBpBOKHqaZHT0YZLR0X90Edv9QDtwsaSzSEY1JwHPd7FPMdOA4yWdS/JqpF2Aw8rsw8zMzKyhVPqZzFHAvwsLTICIWA78FjiAZFb4gSSF3vUkRdqhBbv8A1ifZPTzduBU4GKSArXDV4Am4A7gAWCTzgKLiDkkRepGwA0krx76CvBkOScYEbekMRxI8mzmbiSjt2ZmZmZ9VkVHMiOiy2IrIr4GfC1dvDX9yqe8tveRPIfZVX+3A9sW2aQi64iI20hGRvPdUtBmXMHyVGBqwbqzgLNKOWYxg/oPIib2nRmpqyqXy/WpGbyryvkqnXNlZpad3vyzkmZmZmbWR7jINDMzM7PMucg0MzMzs8y5yDQzMzOzzLnINDMzM7PMucg0MzMzs8y5yDQzMzOzzLnINDMzM7PMucg0MzMzs8y5yDQzMzOzzLnINDMzM7PMucg0MzMzs8y5yDQzMzOzzK1e7QAMFi1fhCar2mHUjbYRbbRObq12GHWjr+YrJka1QzAz69MaZiRT0jhJMyUtkPSapL9KOqdCx2qRFJLeX4n+zczMzOpdQxSZkk4Gfg78ATgAOBy4AfhshQ75ELAz8J8K9W9mZmZW1xrldvkxwEUR8b95626SNLkSB4uIN4D7K9G3mZmZWSNoiJFMYF3gpcKVEbHyoSxJw9Nb3IdK+lV6W/1lSRPz95G0taSrJD0naZGkRyQdL2m1vDbvuF2eLn9d0vckzU37vkDSgAqds5mZmVnNapSRzIeAYyU9C/w+Il7tou2PgN8DBwEfByZKeiUiLki3bwo8DlwOLAC2AyYDawLf7yaOE4E7gcOAbdP2zwBn9eSkzMzMzOpVoxSZRwPXA1OBkPQYcC3Qlt7azvdIRHw5/f4PkjYA/lfShRHxVkT8EfgjgCQB9wCDgKPovsicFRHj8vreleQZUReZZmZm1qco745yXUtvS38K2BP4BPBe4N/AhyOiXdJw4GngaxFxYd5+ewG3AJtHxLOSBgInA6OBzYD+eYfpHxFvSmoB7gI+EBEPp/0E8J2IOCOv7+8Bh0dEc5F4xwPjAZqamkaedN5JmeShL2ge0MzspbOrHUbd6Kv5GrnxyLL3aW9vZ/DgwRWIpjE5X+VxvsrjfJWut3PV2to6MyK2765do4xkEhFLgZvSLyR9iWTG+ZeAn+Q1fblg147ljYFngR8CR5LcIn8ImA/sB5wKDATauwhjfsHysnSfYvFOAaYADNtyWEx4YkIX3Vq+thFtOF+l66v5ilHl/wM6l8vR0tKSfTANyvkqj/NVHuerdLWaq0aZ+PMOEfELYB6wdcGmDTpZfjH9PBj4aUScFRF3RMSDwJuVi9TMzMys8TREkZk+V1m4bn1gHWBOwab9C5YPICkwO+4nrgkszeunH/CFzII1MzMz6wMa5Xb5PyXdANxOcvt7c2ACsAj4ZUHbbSRdRDIx6OMkt9O/HhFvpdunAUdLepJkJPRowK8hMjMzMytDoxSZp5M8N3kesB7JOzP/DBwSEU8XtP0WsA9JkbkE+C5wft72Y4H/Ay4AFpMUqdeRPj9pZmZmZt1riCIzfcflBd02TLweEaO66GsO77ylDnBxXpscoIL9VLhDREwCJnUX0KD+g4iJjTHLvzfkcrkeTeroq5wvMzOrhoZ4JtPMzMzMaouLTDMzMzPLXEPcLi9FRMyi4Ba3mZmZmVWGRzLNzMzMLHMuMs3MzMwscy4yzczMzCxzLjLNzMzMLHMuMs3MzMwscy4yzczMzCxzLjLNzMzMLHMuMs3MzMwscy4yzczMzCxzLjLNzMzMLHN95s9K1rJFyxehyf6Ll6VqG9FG6+TWaodRN2olXzExqh2CmZn1ooYayZR0gKQ7Jc2XtFTSE5LOkNQkabikkLRPN31MkvRKb8VsZmZm1ogapsiUdDZwNfAUMAb4FPBjYF/g4jK6+jmwZ+YBmpmZmfUhDXG7XNK+wAnAlyLikrxNd0uaQlJwliQiZgOzMw7RzMzMrE9plJHMbwAPFRSYAETEioi4NW/VIEkXSXpd0mxJkyWtzEPh7XJJLelt9hZJV0tql/SUpK/lH0fSzpJulPSCpIWS/iZpdCVO1szMzKzW1X2RKak/sAtwW4m7nAW0AwcBvwZOS7/vzsXA34H9gRxwgaQd87ZvDtwLHElyi/5a4FJJo0qMy8zMzKxhNMLt8qHAAODZEttPj4gT0++nSfo0cADw2272uzIizgCQlCMpJA8A/gIQEVd1NJQkYDrQDBwFXFlibGZmZmYNoRGKzA6lvh/l9oLlR4HNytkvIpZL+jdJEQmApP8BJgP7AZsC/dJNzxfrTNJ4YDxAU1MTbSPaSgzfmgc0O19lqJV85XK5aofQrfb29rqIs1Y4X+VxvsrjfJWuVnPVCEXmq8BSSisUAeYXLC8DBmaw31TgI8B3SQrXN4CvkhSd7xARU4ApAMO2HBYTnphQQggGyXsfna/S1Uq+YlTtvyczl8vR0tJS7TDqhvNVHuerPM5X6Wo1V3VfZKajiveSvHbo1GrEIGkgsDdwTET8X976un/m1czMzKwnGqUIOhfYXtLYwg2SVkufu6ykASS3x5fmHXcI8NkKH9fMzMysJtX9SCZARNwk6RzgF5J2BW4gmUG+NfAVYBbJa44qdfzXJT0AnCbpDeAt4CTgdWDtSh3XzMzMrFY1RJEJEBEnSvozcAxwBbAmSXF5I9BGac9dropDSZ6xvIzkOdHzgUFpPGZmZmZ9SsMUmQARcS3J+yk7oyL7jCtYngRMylvOdbJfS8Hyk8AnihxzUpF1ZmZmZg2toYrMejWo/yBiYu3PvK0VuVyuLmYq1wrny8zMqqFRJv6YmZmZWQ1xkWlmZmZmmXORaWZmZmaZc5FpZmZmZplzkWlmZmZmmXORaWZmZmaZc5FpZmZmZplzkWlmZmZmmXORaWZmZmaZc5FpZmZmZplzkWlmZmZmmXORaWZmZmaZW73aARgsWr4ITVa1w6gbbSPaaJ3cWu0w6kZv5SsmRsWPYWZm9aPbkUxJkyS90sm2qZIezD6sVSMpJB1TsG5HSa9Luk3SgGrFZmZmZtYX9Inb5ZK2A24DZgL7R8TSKodkZmZm1tAavsiUtA0wDXgU2DciFlc5JDMzM7OGl3mRKWk7SX+UtEjSa5Iul7Rh3vbh6e3sz0u6KL2FPVvSZEmrFfR1sKR/S1os6S5JH0r3HVdiLCOAO4CngM9ExMJajdXMzMyskZRcZEpavfALUEGb9YEcMAg4FDgW2A2YJmmNgi7PAtqBg4BfA6el33f0tT1wFfAQsD9wI/CbMs5tC+CPwIvAnhHxRg3HamZmZtZQSp1dPhRY3sm2mXnfn5h+rizqJD0BzAAOBK7Mazs9IjraT5P0aeAA4Lfpum8DjwFfiIgAbpPUH/hhiTGfACwGdoiI+UW211KsZmZmZg2l1CLzdeCTRdZPBDbOW94RuD1/1DAi/iJpFvBR3l643V7Q16PAZnnLOwBXpkVbhxspvXC7A/gE8ANJRxT0U/VYJY0HxgM0NTXRNqKtpJMyaB7Q7HyVobfylcvlKn6MSmtvb2+I8+gtzld5nK/yOF+lq9VclVpkvhkR73hVkaRXeXuRuTHwSJH95wDrFawrHF1cBgzMW94ImFvQpnC5KzcA1wEXAC8D3yrYXtVYI2IKMAVg2JbDYsITE7pqbnnaRrThfJWut/IVo+r/PZm5XI6WlpZqh1E3nK/yOF/lcb5KV6u5ynriz4vABkXWbwjMK7Ovl4D1C9YVLncpIn4GfBf4pqQTCjbXVKxmZmZmjSTrInMGsKekIR0rJO0ADAfuKbOvB4B9JeVPLvpsuQFFxGnARUCbpMNqOVYzMzOzRpF1kXlO+vkHSftJGg38DvgncG2Zff0QeC9wlaRPS/oGcFS67a0y+/oacD1wSTppp5ZjNTMzM6t7mRaZETEXaAWWkEycuQD4E7BHRCwrs68HgVHASJIC8UDgq+nmNzrbr5O+3kr7+jNwjaSdajVWMzMzs0bQ7cSfiJgETOpk27gi6/5KMqu7s/5mUfB+zS76+i3/fU0Qebe7/95NzMX6Xwq01FqsZmZmZo2o1NnlVSHpQpI/Cfka8GHgVODmiHi6qoEVsSqxDuo/iJhY/zNze0sul2uImcy9xfkyM7NqqOkik+Ql8D9LP18l+Ss6ha8iqhX1FKuZmZlZRdV0kRkRn692DKWqp1jNzMzMKi3r2eVmZmZmZi4yzczMzCx7LjLNzMzMLHMuMs3MzMwscy4yzczMzCxzLjLNzMzMLHMuMs3MzMwscy4yzczMzCxzNf0ydjMzM7NKWL58ObNnz2bJkiXVDmWVrbPOOjz22GOZ9ztw4ECam5vp379/j/Z3kWlmZmZ9zuzZsxkyZAjDhw9HUrXDWSULFixgyJAhmfYZEbz66qvMnj2bLbbYokd9uMisAYuWL0KT6/sC701tI9pondxa7TDqRm/lKyZGxY9hZpaVJUuWNESBWSmSGDp0KHPnzu1xHw3xTKakSZJeqXYcZmZmVj9cYHZtVfPTEEWmmZmZmf3Xueeey6JFi6oag2+Xm5mZWZ+X9WNr1X6E6Nxzz+Wwww5j0KBB79i2YsUK+vXrV/EYGm4kU9Jaks6X9LikRZKelnSBpLUL2oWkEyT9RNI8SfMl/VTSGnltNpZ0iaSnJC2W9ISkMwraDE/7+rykiyS9Lmm2pMmSGi6/ZmZmlo3LLruMbbfdlg9+8IOMGTOGZ555ht13351tt92W3XffnWeffRaAcePGcc0116zcb/DgwQDkcjlaWloYM2YMW2+9NaNHjyYiOO+883jhhRdobW2ltbV15T6nnXYaO+20E2eccQb777//yv6mTZvGAQcckPn5NeJI5iCgH3AKMBcYln5/NbBnQdsTgfuB0cA2wJnAEuCb6fYmYB5wAvAaMAKYBKwPfLmgr7OAa4GDgN2B04BHgN9mdWJmZmbWGB555BHOPPNM7r33Xpqampg3bx5jx47l8MMPZ+zYsVxyySUcd9xxXH/99V3289e//pUZM2YwYsQIdt11V+69916OO+44zjnnHO666y6ampoAWLhwIe9///s5/fTTiQje+973MnfuXNZff30uvfRSjjjiiMzPseFG2iJibkR8NSKuiYi7gauAI4FPSdqsoPkC4OCIuDUi2oDTgaMlrZf29c+ImBAR16d9XUpSgI7NH81MTY+IEyNiWkScBPwdyP6fBWZmZlb37rzzTg466KCVReB6663Hfffdx6GHHgrAmDFjuOeee7rtZ8cdd2TTTTdltdVWY7vttmPWrFlF2/Xr148DDzwQSCb0jBkzhl//+tfMnz+f++67j7322iubE8vTiCOZSBpDMvr4bmCtvE0jgGfzlm+IiLfyln8HnAG8H5iuZFrV14HxwBbAwLy2mwFP5i3fXhDGo2mbzmIcn/ZLU1MTbSPauj8xA6B5QLPzVYbeylcul6v4MSqtvb29Ic6jtzhf5XG+ylPpfK2zzjosWLCgYv131/fixYtZtmzZ29pFBAsWLKB///4sX758ZT8RwcKFC1d+37HfokWL6NevHytWrGDBggWsWLGC9vb2le3a29sZMGAAkLxYPX8i0MEHH8whhxwCwH777cfixYuLxrlkyZIe/xwarsiUtD9wGXAh8L8kt7s3Bq7j7UUiwMudLG+cfh4PtAE/AO4muWW+A3BBkb7mFywvK9JmpYiYAkwBGLblsJjwxISuTsvytI1ow/kqXW/lK0bV/3syO55vstI4X+VxvspT6Xw99thjmb/APF93fe+9997sv//+nHTSSQwdOpR58+ax6667cvPNNzNmzBimTp3Kxz72MYYMGcK73/1uHn30UcaOHcv111/P8uXLGTJkCIMGDWL11VenX79+DBkyhDXWWIOBAwcyZMgQ1l57bSLibXEUft/c3ExbWxvTpk3rNN6BAwfyoQ99qEc5aLgiEzgYmBERX+tYIWm3Ttpu0Mnyi3l9XR0Rp+T19b6sAjUzM7O+aZtttuGUU05ht912o1+/fnzoQx/ivPPO44tf/CI/+tGPVj4rCXDUUUex3377seOOO7L77ruz1lprddM7jB8/nr322ouNN96Yu+66q2ib0aNHM3fuXN73vsqUNo1YZK4JLC1YN7qTtvtJOjnvlvkBwGLg4R70ZWZmZnWqGq8cGjt2LGPHjn3bujvvvPMd7TbccEPuv//+lcvf//73AWhpaaGlpWXlLffzzz9/ZZtjjz2WY489duVye3v7O/q95557OOqoo1btJLrQSEVmx9UxDbhA0inADOAzJLO9ixkCXC3pYpLZ5acB50fEvLy+jpM0A/gPSYG5VYXiNzMzM+sVI0eOZK211uLss8+u2DEapchck+QZSICLgC1JJuwMJCkUDyV5VVGhs9O2V5LMtP85yXOcHU4neV3RGeny74DjgJuyDd/MzMys98ycObPix2iUIvNdpLPGI2IFMCH9ylfsVf7LIuIY4JhinUZEO1DsxVHKazOrWN8RMa6EuM3MzMwaUl0XmZK2AVqBfYCJVQ6nxwb1H1T1Pz9VT3K5XEPMZO4tzpeZWXERQfK2QismYtX+31HXRSZwPsko5k+Ac6oci5mZmdWJgQMH8uqrrzJ06FAXmkVEBK+++ioDB3b6NsZu1XWRGRGtq7CvrygzM7M+qrm5mdmzZzN37txqh7LKlixZskrFYGcGDhxIc3Nzj/ev6yLTzMzMrCf69+/PFltsUe0wMpHL5Xr8wvRKari/XW5mZmZm1eci08zMzMwy5yLTzMzMzDKnVZ2ebqtO0gLg8WrHUUeagFeqHUQdcb5K51yVx/kqj/NVHuerdL2dq80jYv3uGnniT214PCK2r3YQ9ULSg85X6Zyv0jlX5XG+yuN8lcf5Kl2t5sq3y83MzMwscy4yzczMzCxzLjJrw5RqB1BnnK/yOF+lc67K43yVx/kqj/NVuprMlSf+mJmZmVnmPJJpZmZmZplzkVlBkt4n6Y+SFkl6QdLpkvqVsN86ki6V9Jqk1yVdLmlob8RcTT3Jl6ThkqLI11W9FXc1SNpK0kWS/i5phaRcifv11Wur7Hz14WvrYEk3SnpeUrukmZJGlbDfAElnS3pZ0kJJN0saXvmIq2sV8lXs2rq/N2KuJkkHSfqzpFclLZH0uKRTJa3RzX599XdX2fmqpd9dfoVRhUj6H+AO4FFgP+BdwNkkhf2p3ez+G+A9wJHAW8APgeuBj1Uq3mpbxXwBTADuzVtu9HerbQN8Brgf6PKXc4E+d22lepov6HvX1gnA08A3SM71M8AVkpoi4qdd7HcecFC631xgEjBN0gciYkllQ66qnuYLkt9x1+QtL6hMiDVlKHAX8CNgPrAjybWyEXBMF/v11d9dPc0X1MLvrojwVwW+gJOB14C189Z9C1iUv67IfjsDAXw8b92O6bpPVvu8ajBfw9Pc7FPtc+jlfK2W9/01QK6EffrktbUK+eqr11ZTkXVXAE93sU8z8CZweN66TYFlwJHVPqday1faJoBjqh1/LXwBZ5IUUOpke5/93dXDfNXM7y7fLq+cvYA/RMQbeeuuAtYEdutmvzkRMb1jRUT8heRfyntVItAa0dN89UkR8VYPduur11ZP89UnRUSx0Y6/Aht0sdun0s/f5fXzPHAPjX9t9SRf9nav0vUdhj77u6sT3eWrZrjIrJytgX/lr4iIZ0lG5rYuZ7/UY93sV+96mq8Ol6bP2r0o6RxJa1YiyDrXV6+tVeVrC3YheZSlM1sDsyOivWB9X722ustXh0mS3pT0iqRLJK1X6cBqhaR+kgZJ+ihwHHBhpMNwRfT5311l5qtD1X93+ZnMyvkfkuHsQq+l23qy35YZxFWrepqvpcAFwO3AG0AL8G2SZzr3yzbEutdXr62e8rUFSNqd5Hy/2EWznv7323BKzBfAL4GbSJ5f3R74DvBBSTtGxIrKRlkTFgID0u8vA77ZRVv/7iovXzXzu8tFZmUV+1eGOlmfxX71ruzzjogXefvDzzlJc4CfSdouIv6WcYz1rq9eW2XztZXMUiV5vvCGiJjaTfM+f22Vk6+IGJe3OF3SY8AtwL4kE1oa3S7AIJJnK08Dzge+1kX7vn59lZyvWvrd5dvllfMasG6R9etQ/F9k3e23bjf71bue5quYjtmaH16liBpPX722stRnrq301u2twLPAYd007/PXVpn5KuY2oJ0+cG0BRMRDEXFPRJxDcvv3q5Le1UnzPn99lZmvYqryu8tFZuX8i4JnRSQNA9ai+LMlne6X6uyZlEbR03wVEwWfluir11aW+sS1JWkQ8HuSyQV7R8TCbnb5FzBM0loF6/vEtdWDfL1D3vN1DX1tdeKh9HOLTrb7d9fbdZevYqpyfbnIrJxbgT0lDclbdwiwGLi7m/02Sh/uBUDS9iTPndxaiUBrRE/zVcxB6efMLAJrIH312spSw19bklYHrgbeDewVES+XsNvt6ef+ef1sQvIOw4a+tnqYr2L9fBoYTANfW13YNf18upPt/t31dt3lq5iq/O7y3y6vkPTl4o8CD5O8NHZL4Bzg3Ig4Na/dk8DdEfGlvHW3ASNIXqTa8dLZlyOiYV8629N8SZoEDCF54ewbwMdJHoi+JSIO7M1z6E3pyMln0sUTgbWBienyLRGxyNfWf/UkX3342poCHAV8/f/bu0OdBoIgAMP/hhAkJLxAsUgkto+A6RPgULwB9XgUfQhkIWjSgEKQIJogUAgICELIIuYEHAg4Fq65/l+ypncndnKZTLa7c8BZ7fJFzvk5pXQMkHPuv3vuANjiYzP2VaDTzdibxCultE0c9hkTDbI3iI9OXAGbXT74U+WgMXAJvBIF0y5wlHMeVPeYuypN4jVTuavtRp1dHsA6cEKsxt0CQ2Chds8UGNV+WwEOib0mD8RG8k8Nf7s2msQLGAAT4J5o/HwN7AFLbc/nj2PVI/72+Gr0fLd+H685frem34jVKbWG9sTJ132iwHwiDrGstT2fWYwX0CcKgDvgBbghvpi03PZ8/iFeQ2Ix4bHKQ+fADrBYi+mo9ty85q4fx2uWcpcrmZIkSSrOPZmSJEkqziJTkiRJxVlkSpIkqTiLTEmSJBVnkSlJkqTiLDIlSZJUnEWmJEmSirPIlCRJUnEWmZIkSSruDSU4vnkDBDH0AAAAAElFTkSuQmCC\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "(df.country\n", - " .value_counts()\n", - " .head(n=10)\n", - " .apply(np.log10)\n", - " .sort_values(ascending=True)\n", - " .to_frame()\n", - " .plot.barh(grid=True, color='green', fontsize=15, \n", - " title='Number of movies (log) per country', figsize=(10, 5)));" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 97, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "countries = set(['Norway', 'Sweden', 'Denmark'])\n", - "df_world_pivot.loc[:, countries].plot(linewidth=3, title='Population growth', \n", - " fontsize=14, figsize=(10, 5))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (7.2) Using matplotlib\n", - "\n", - "Greater control. Allows creating of publication-quality plots. \n", - "Does require more code and knowledge of matplotlib." - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 5))\n", - "\n", - "ax = (df_world_pivot.loc[:, countries] / 10**6).plot(ax=ax, lw=3, zorder=50)\n", - "\n", - "ax.set_title('Population growth', fontsize=17)\n", - "ax.legend(fontsize=14, loc='upper left')\n", - "ax.tick_params(axis='both', which='both', labelsize=14)\n", - "ax.set_ylabel('Population (millions)', fontsize=14)\n", - "ax.set_xlabel(ax.get_xlabel(), fontsize=14)\n", - "ax.grid(True, zorder=-50, ls='--')\n", - "ax.set_ylim([3, 11]);\n", - "\n", - "#plt.savefig('my_figure.pdf')" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 5))\n", - "\n", - "# Compute kernel density estimates\n", - "from KDEpy import FFTKDE\n", - "data = df[['imdb_score', 'gross']].dropna(how='any')\n", - "\n", - "kde = FFTKDE(bw='ISJ', kernel='gaussian')\n", - "\n", - "x, y = kde.fit(data.imdb_score.values).evaluate()\n", - "ax.plot(x, y, label='imdb_score', lw=2)\n", - "\n", - "y = kde.fit(data.imdb_score.values, weights=data.gross.values).evaluate(x)\n", - "ax.plot(x, y, label='imdb_score weighted by gross', lw=2)\n", - "\n", - "ax.set_title('Score distribution', fontsize=17)\n", - "ax.legend(fontsize=14, loc='upper left')\n", - "ax.tick_params(axis='x', which='both', labelsize=14)\n", - "ax.set_yticklabels([])\n", - "ax.set_xlabel('Score', fontsize=14)\n", - "ax.grid(True, zorder=-50, ls='--')\n", - "ax.set_xlim([0, 10]);\n", - "\n", - "#plt.savefig('my_figure.pdf')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (8) Time series manipulations" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (8.1) `.dt` accessor\n", - "\n", - "Let's load a data set showing the popularity of the search words `python pandas`, `sas enterprise guide` and `microsoft excel` over the last 5 years. The data was fetched from Google Trends." - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Weekpython pandas: (Worldwide)sas enterprise guide: (Worldwide)microsoft excel: (Worldwide)
02013-12-222153
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" - ], - "text/plain": [ - " Week python pandas: (Worldwide) sas enterprise guide: (Worldwide) \\\n", - "0 2013-12-22 2 1 \n", - "1 2013-12-29 2 1 \n", - "\n", - " microsoft excel: (Worldwide) \n", - "0 53 \n", - "1 62 " - ] - }, - "execution_count": 100, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_trends = pd.read_csv(r'data/google_trends.csv')\n", - "df_trends.head(2)" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "metadata": {}, - "outputs": [], - "source": [ - "# Some values are assigned `<1`, we set these to zero\n", - "for col in df_trends.columns:\n", - " if df_trends[col].dtype != object:\n", - " continue\n", - " try:\n", - " df_trends[col] = np.where(df_trends[col] == '<1', 0, df_trends[col])\n", - " df_trends[col] = df_trends[col].apply(np.int)\n", - " except:\n", - " pass\n", - "\n", - " \n", - "# Change column names, set the 'Week' column to datetime, and use it as index\n", - "df_trends.columns = [c.split(':')[0] if ':' in c else c for c in df_trends.columns]\n", - "df_trends['Date'] = pd.to_datetime(df_trends['Week'])\n", - "df_trends = df_trends.set_index('Date').drop(columns='Week')" - ] - }, - { - "cell_type": "code", - "execution_count": 102, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 5))\n", - "ax = df_trends.plot(ax=ax, lw=3, fontsize=16)\n", - "ax.set_xlabel('Date', fontsize=16); ax.set_yticks([]);\n", - "fig.savefig('pandas_vs_excel_vs_sas.png', dpi=100)" - ] - }, - { - "cell_type": "code", - "execution_count": 103, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 103, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "(df_trends\n", - " .assign(week_of_year=lambda df: df.index.to_series().dt.week)\n", - " .groupby('week_of_year')\n", - " .mean()\n", - ".plot(figsize=(10, 5)))" - ] - }, - { - "cell_type": "code", - "execution_count": 104, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 104, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "(df_trends\n", - " .assign(month=lambda df: df.index.to_series().dt.month)\n", - " .groupby('month')\n", - " .mean()\n", - ".plot(figsize=(10, 5)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (8.2) Rolling window functions" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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ldhZ2lNSUdPj9r3VxuXGM8B6BhcKCGf1n8PHpj5scezT/KMO9hhu+drF2wUxhRnFNcVdMVRAEoV3Cw8PZuXMny5YtY9++fTg5OQGwe/duRowYQXh4OL/++iuJiYkAREREMHfuXL744gvMzRvnSHbs2MFnn31GZGQkI0aMoLi4mNTUVACGDx+Or68vCoWCyMhIMjIyGl0fFxdHUlISo0ePJjIyknXr1pGZmWk4P3v2bKPxc+botzYeN24cFRUVhsBv2rRp2NjYNLr/6NGjeeaZZ1i1ahVlZWWYm5uzY8cOduzYweDBg4mKiiIlJcUw5waHDx9m/PjxuLq6YmFhwZ133tnabzEAe/fuNXTOj4iIICIiolXvtyP03CBL1XFBVmdksqo0VdhZ2OFl59Xjlgx1so7DeYcZ4T0CgAfDHuRU0akmlw3z1fmNPssApwBRlyUIwjUtKCiIY8eOER4ezl/+8hdefvllampqePTRR9m0aROnTp1i4cKF1NTomyxv3bqVxx57jGPHjjFkyBDq6+uN7ifLMu+88w7x8fHEx8eTnp5uyGRd3jnezMys0bUN199yyy2G65OSkli7dq3hvJ2dndH4K1cKGr6+clyD5cuX89FHH1FdXU10dDQpKSnIssxf/vIXw2ueO3eu0V6NzW0vZ25ubthMWpZl6urqTI4ztarR0vvtCD12uTCrMotb/W696vs0LBfqZB0ZFRm4WLngYu1y1fdtCLI87fTF76FuoS1fdINIKUnB1doVLzsvAOwt7Xl7wtvM/2k+gS6BRLhHGI0vqynD2crZ6FjD5zLceziCIAgtaWpJrzPl5OTg6urKvffei729PZ9++qkhoHJzc0OlUrFp0yZiY2PR6XRcvHiRCRMmMGbMGNavX49KpcLZ+dLffZMnT2b16tXcdNNNWFhYcPbsWXr1ar722MHBgcrKStzc3IiOjuaxxx7j3Llz9O/fH7VaTVZWFkFBQSav3bhxIxMmTGD//v04OTkZMnFNOX/+POHh4YSHh3Pw4EFSUlKYPHkyf/vb35g7dy729vZkZ2djYWGBh4eH4brhw4ezZMkSSktLcXBwYPPmzYSHhwP6WrFjx45x11138f3336PRNH7af9y4cXz55ZdMmDCB06dPk5CQANDm99sePTrI6oiaLAdLB+wt7DlRcIKndz/NZL/J/F/0/131fVUalT6TZevV49o4JBYnMsjdeL3d38mfFSNX8Oxvz7Lhtg242bgZzpXWljYKbDvrgQRBEISOcurUKZYuXYpCocDCwoLVq1fj7OzMwoULCQ8Px8/Pj2HDhgH6ovZ7772X8vJyZFlmyZIlRgEWwIIFC8jIyCAqKgpZlnF3d2fLli3NzmHRokVMmTIFb29vdu/ezaeffsqcOXOora0F4JVXXmky6HBxcWHUqFFUVFTw8cdNl3Q0WLlyJbt378bMzIyQkBCmTJmClZUVycnJjBw5EtAXrn/xxRdGQVavXr3461//yogRI/Dx8SEkJMQQ0C1cuJDp06czfPhwJk6caDKLtnjxYh544AEiIiKIjIxk+HD9/3y7u7u36f22h9RcGq6rDB06VO6qnhUAGq2GEetHcGjuISwUFld9vwU/LyC5JJmZgTP5NvVbfon9BVsL26u650M/P8TCiIWcLjpNeW05zw599qrneb1YeWwltha2LIpY1OjcOyfe4Xj+cT6Y9IHhs7vp65vYcNsGPO08DeP2Zu3li6Qv+GDSB102b0EQri/JyckEBwe3PFBoJCYmhjfffJOhQ4d2yeupVCrs7e2pr69nxowZPPjgg8yYMaNLXtvUz4kkScdkWW7xzffImqx8dT5KG2WHBFgAwcpgxvqO5ZkhzzDYYzA/Z/x81fdUaVTYW9jjZefV43plZamabq/x6KBHsVBY8PWZrwH9mnppbSnO1sb/R9dZDyQIgiAIXe/FF18kMjKSsLAw/P39ueOOO7p7Sq3SI5cLq+ursTM3XZjXHk9HPY1CUiBJErFBsXx06iNmBF5dhK3WqLG1sNUvF/a0IKuZJz/NFGbE9I4xBFBVmiosFZaG9g0NfOx9KK8tN9S2CYIgCB3n8tYMXeHNN9/s0tfrKD0yk1Wnq8PSzLLD7memMDM8uTCm1xhyq3JJLU1t4armGWWyurAmK6Ukpd0tI2RZZn/2/mafBGmN5vaUBPCw9aBQXQiYrscCUEgK+jr27bS9JQVBEAShJT0yyNJoNViYdcxS4ZXMFebM6D+DzanNdylvSUMGxsPWg6LqoqsOXFpDlmWW/raUNSfXtOv6dYnrWLxzMdmq7HbPobKukjptHa7Wrk2OcbNxo7D6jyCrphQXK9NPcwYrgzlVdKrdcxEEQRCEq9Ejg6w6bR2Wio7LZF1pZuBMtqZtpaa+pl3Xa3VaarW12JjbYGmmXwpTaTq21b8pR/OPUqutZVv6tlZtyny5uNw41iWtI9wtnKTipHbPIVuVja+Db7Od2t1t3Q1BVlltWaN6rAbR3tHE5cS1ey6CIAiCcDV6ZpDVwcuFV/Kx9yFUGdqqjY1NUdersTG3MWyl42zlTFlN4y0UOsLaU2t5+/jbAGxO3cx9IfcR7hbe5rn/3/7/47UxrzG211iSS5LbPZ/W7CnpbuNOUXUROlnXbCZrhPcIjuQfoV7XuOmeIAiCIHS2nhlkdXImCyA2KJZNZ9u3A/iVxdouVi6U1pZ21NSMHMk/wmeJn7E+eT17L+7l9oDb2zz3iroKKusqifaOJkQZclWZrNb0L7M0s8TOwo6y2jJ9kNVE81c3Gzc8bT1JLm5/0CcIgtDdfvjhB15//fUuf92UlBTDZs7Hjh3j/fff7/I5AHz66aeGDaGvNz0zyNLVdVpNVoPxvcdzofJCu9oIVGmqsLewN3ztbO1MaU3nBFnpZen8c9w/WXl8JWN9x+Js7cw433FkVWZxvux8q+6RXXlpia8hyGpvDVlrtztyt3GnUF3YZOF7g2jvaOJyxZKhIAjXr2nTprF8+fJWjZVl2bDNzNXasmUL06dP58SJEyiVym4Lsq5nPTLI0mg1nbpcCGChsGCY1zASixLbfG1Dt/cGrtaunZLJqq6vprimmJjeMbw/8X0eH6z/PwULhQXjfMdxLP9Yq+5z+dOA7rbumCvM2912Iqsyi94OvVsc526jr8sqq228pc7lRJAlCMK1KiMjg4EDB7JgwQLCwsKYO3cuO3fuZPTo0QQGBnL48GHAOJOTn5/PjBkzGDRoEIMGDeL3338nIyOD4OBgHn30UaKiorh48SIbNmwgPDycsLAwli1bBui7xs+fP5+wsDDCw8N56623AIiPjyc6OpqIiAhmzJhBaWkp27ZtY+XKlXz00UdMmDCB5cuXc/78eSIjI1m6dGmj9/LFF18wfPhwIiMjefjhh9FqtWRmZhIYGEhRURE6nY6xY8eyY8cOAD777DMiIiIYNGgQ9913HwCFhYXMmjWLYcOGMWzYMA4cONDpn0Fn65F9srpiuRBAaa1sVzuEK5cLO6smK6M8g94OvTFTmDHUy7hxbVu2pcmqzKKXw6U6qoZslre9d5vnlK3KbtV2R+62f2SymqnJAhjqNZSle5dSXV+NjXnjXeHbQ5blZgvzBUG4/vx79tROu/ezG39s8ty5c+f45ptv+OCDDxg2bBjr169n//79/PDDD7z22muNtsV58sknGT9+PN999x1arRaVSkVpaSlnzpzhk08+4f333ycnJ4dly5Zx7NgxXFxcmDRpElu2bKF3795kZ2dz+vRpAMrK9L9X7r//ft555x3Gjx/PCy+8wEsvvcTKlSt55JFHsLe357nnniMjI4PTp08THx/f6D0kJyezceNGDhw4gIWFBY8++ihffvkl999/P8uWLeORRx5hxIgRhISEMGnSJBITE3n11Vc5cOAAbm5ulJTof08+9dRTLFmyhDFjxnDhwgUmT55McvL1Xe7RIzNZnV343kBpo6S4urjN1zWqybLunJqs9PJ0ApwCTJ5r2GC5Na6sowpRhpBY3PYMnlanJUeVg4+9T4tjG4rfm6vJArCzsCPQOZDTRafbPB9TMsozuGfrPejkjknHC4LQs/n7+xMeHo5CoSA0NJSJEyciSRLh4eFkZGQ0Gv/rr7+yePFiAMzMzAx7+PXt25fo6GgAjhw5QkxMDO7u7pibmzN37lz27t1LQEAAaWlpPPHEE/z00084OjpSXl5OWVkZ48ePB2DevHns3bu3Te9h165dHDt2jGHDhhEZGcmuXbtIS9P/T/qCBQuorKxkzZo1hoaiv/76K7Gxsbi56fegdXXVt+zZuXMnjz/+OJGRkUybNo2KigoqKyvb+B29tvTMIEtb12Fb6jRHaa2kuKbtQZaqTtW48L0TarLSytPwd/I3ea4t29I0tF1oEOIaQlJJ24vfC6sLcbJywtrcusWx7rbuFKgLmm3h0MDPyY+syqw2z8eUEwUnOF18WrSGEAShQ1hZXdqtQqFQGL5WKBTU17f+yejLN0ZuqibWxcWFkydPEhMTw3vvvceCBQvaOWtjsiwzb9484uPjiY+P58yZM7z44osAqNVqsrL0f/+qVCrDeFOrATqdjoMHDxruk52djYODQ4fMsbv0yOVCja7za7Lgj0xWO4Isdb3aeLnQ2rnTMlkT+0w0ec7bzpuymjLD9j6Xk2WZLee2MNlvMrYWto2K1YOVwUZP9Gl0Gv53/n/MDJzZ7HwuVl5ssX1DAzcbN47mHdUXvjezXAjg6+DLxcqLrbpvSxKLE+nv3J9NqZsY1WtUh9xTEITu19yS3rVk4sSJrF69mqeffhqtVktVVVWjMSNGjOCpp56iqKgIFxcXNmzYwBNPPEFRURGWlpbMmjWLfv36MX/+fJycnHBxcWHfvn2MHTuWzz//3JDVupyDg0OTWaWJEycyffp0lixZgoeHByUlJVRWVtK3b1+WLVvG3Llz6du3LwsXLuTHH39k4sSJzJgxgyVLlqBUKikpKcHV1ZVJkybx7rvvGmq+4uPjiYyM7NhvYBfrsZmsLgmyrJWUVLe9JktVpzJ6utDFyqVTarKay2SZKcz029JUNF4y3JCygRd+f4Hfc35Hq9OSq8o1Co48bT2p09ZRXlsOQGZ5Jit+X9FiNq6irqLZpb/Ledh6kFeVh6pOhaOlY7Njfe19yVJ1TCYruTiZp6OeJi43jqLqog65pyAIQmu9/fbb7N69m/DwcIYMGUJiYuPSDG9vb/7xj38wYcIEBg0aRFRUFNOnTyc7O5uYmBgiIyOZP38+//jHPwBYt24dS5cuJSIigvj4eF544YVG91QqlYwePZqwsLBGhe8hISG88sorTJo0iYiICG655RZyc3P57bffOHLkiCHQsrS05JNPPiE0NJTnn3+e8ePHM2jQIJ555hkAVq1axdGjR4mIiCAkJIQ1a9q3+8i1pEdmsuq0dV2yabCrtWu7MllV9VVGgUNn1GTV6+q5WHkRPye/Jsf4O/mTVpZGqDLUcOx4/nH+m/BfZg+YTVxuHKHKUJytnI02aJYkCV8HfWDjZOVkCHAO5x1mst/kJl9Po9W0ehnXzcaN8+XncbR0xExh1uxYXwdfsiub3uqnXlePuaLl/xTqdfWklqUy1GsoN/e5mR/O/8CDYQ+2ar6CIAhX8vPzMxShg/4pQlPn5s+fz/z58wHw9PTk+++/b3Svy+8DcM8993DPPfcYHRs0aBDHjx9vdG1kZCRxcY1LIBqW/BqsX7++yfcye/ZsZs+e3ej45ff99ttvDX+eN28e8+bNMxrr5ubGxo0bG93j8vd/vemZQZauDhez1mVMroarjSslNSVtfhqtqq4KH7tLxd+dUZOVo8pBaa1s9om7AKeARsXvrx9+nReiX6CXQy+W/raUyX6TTfa18rX3Jasyi1BlKFmVWdiY2xCXG9dskNXwQIJOp6UwM4OspFOUZGehKi2mrka/zY+5hSW2jk7YuLrgdUHCzsuJeo0Gc4umg7PmMllqjZop305hy/QtLWbR0srT8LT1xM7CjqkBU3n7+NsiyBIEQRCa1DODrC4qfLcys8LazJqKugqcrJxafV1V/aWnC5P27QYJamvUrc64tEZaeRr+zqaXChv4O/nzc8bPhq+1Oi3p5emM6jUKKzMrymvLOZp31HR96JRUAAAgAElEQVSQ5eBr2Cg6S5XFrX63NlksrtNpKbqQSdG+eJzOXGD1J3OpqWp5r8bxuAMyq3bMws23D72Cw/ANDsM3OBQ750sBk5uNG2qN2mR92U8ZP1FSU0K2KrvFICupOIlgZTAAnnae7WrPIQiCIPQcPTLI6qrCd7hU/N6aIGtDygZmBs6kqk4fZMk6Hfu/+ozKokJizX3Ypv4PI6bMxDOg/1XP63zZefwdWw6yLn/CMFuVjau1qyH7Ndx7ON+e+5aZ/RsXtPey78XZ0rMAZFVc5HafKcSf3s+hfVuxrNJRWVxERVEhZXm5FGddoL6uFgALoK3bass6HYUXMii8kEH8z/riVfc+fgwYNY6Bo8fh5OFFL/teZKmyCHIJMrp209lNOFo6kleVR5hbWLOvk1ScZFg6dbR0pKKuoo0z7XjrEtcxZ+CcLvt5FoQbjeh7JzSnvbuXNOiRQVZXFb6Dvi6rpLqkyX5UDfKq8njt0Gs4WjoaMlkXk05RWVQIgEW9ROrevaTu3YvPgBCiptxO4PBRKMyar0dqyi+Zv/BY5GPNjmlofaDR6Wul0svTjbJf0d7R/JzxM70celGjUlGWl0NZfi5l+XnUpSdAVgofb3yYPgXZnNauYTy27P91davmZ+fsQu/QCLwDB+CgdMPK1h5JAk1tLVXlpZTl5bLr+A/YlYOivLbR9Q1B1/6vPsM7cADBHo5kFp43CrLOlJyhQF3ArX63tqpDfVJxErf0vQUAB0sHVBoVOlln2Mi7qxWoC3jz6JtEekQyyH1Qt8xBEK5n1tbWFBcXo1QqRaAlNCLLMsXFxVhbt9xWqCk9N8jqgo7vYLpXVk19TaNeUHG5cbhau7I5dbPh6UJXHy9G3TWXpL2/UpaXaxibcyaJnDNJ2CvdCB13E8FjYlD69mn1nJKLkympKWGUT/MtCKzMrPCw9SCrMsuQ1fK360vhhQyKMtOxPpfDzcc8yDywgffKP2h0vR1QSjatCQPtXFyp87ZB42vPA1OW4OLdq8W/9Lb5puBi58Xi4IXkpJ4hO/k0WcmJ5KamoL2sv0xu6hncUiHh8H+Rx6Yy6JY/4RnQn01nNzEzcCZWZlYmg6zLg3GtTsvZ0rMMdB0IgLnCHBtzG1Salp9u7CyHcg8B+s9TBFmC0Ha+vr5kZWVRWFjY3VMRrlHW1tb4+ra8C0lTemaQ1QUbRDdwtXY1qt25WHmROVvn8M+x/zTqsxSXG8cjgx5hzck11GprsbWwxd5JychZc4ieeTfLNywm6IIdFQnn0Wn1AYSquIhD333Noe++xr2vPwNHj6f/sJG4+jTfa2pz6mZmBM5o9qk8WZapKislTOXD/u/Wk6yypjD5IOaldXymvbSflC821NFyR15LGxusXZw5r8tmYuifcFC64eDmjqO7B0rfPtg6OrH65GokXT2uPq37gR7iOQQXKxcsbWzxixiMX8RgAOqq1Zw7eoiUA7+RmXACnVarv0BTz6lfd3Dq1x049fElWXmWfyz8mITyRJJLjLduKKkpYdqWafzvjv/hYu1CQlECPnY+OFheaoznaOlIZV1ltwVZcblxBLkEkVTc9savgiCAhYUF/v7Nl00IwtXokUGWRqvpukzWZVvrVNdXs2T3EgKdA/n67NeGIEuWZQ7lHuLxyMfJVeXySeInRn2yJEnC1t8bhyHBzH74eU7+sp2EndtRl1/qnVWYmU5hZjr71n+Ki7cPAVHD8YscgmdAf2zsLwUGao2a7enb2TxtMzqdluqKCsoL8vXLfHk5lOXlUpafS2leLjWVFXgBBeRTAM1mpMwsLHDx8sHJ0xtnTy+cPb1548zbxA69ly35P/H5jPXUaesYsX4Er937qMklNo1WY9QKoiWxQbEmj1va2BIydgIhYyegrijnzO97+X37ZmryLvW1Kr+QxeALtmx5diluQ8IoczFu8ZBYlEh5bTk/nP+BeaHz2Hx2M9P7Tzca42jpSEVtRasbqHakhp+Zp6KeYl3iui5/fUEQBKFlPTLI6qq9C0G/XHim9AwAbxx+gyCXIJ6Pfp5bNt1CoboQd1t3zpedx8rMCl8HX2YGzuSTxE8a9fFqaONg7+LK6LvmMmLGXaTHHyVl3x7OHz+MVqMxjC3NzeHY1i0c26rfWNTO2QVbRycsbGwpqS7mNpUH3+1+juqKCuR27MHn6O6BWx8/3Pv4497XD7c+frh4+TSqD7OSv+GkfA5vpT4zZWlmiZ2FHWW1Zbhauza6r0anMcoUdQRbRycG33o7dsMH8PLmZ7mnNobE33ej+CO5VVddTc7+IwQD6888x6CbpxA0cgzJJfoluIas368XfmXJkCXG3wer7it+z6jIQJIkbul7Cy8dfIlabW2bAlRBEASh8/XMIKsrC99tXCnOKUaj0/Bzxs9snbkVOws7JvWdxJZzW1gYsZC43DiivfUbe/o5+fHN7d80ajXgYu1CjirH8LW5hQWBw0YSOGwkteoqUg8f5NyRODJPnaC+1rgQvKqslKqyS322rAA1LXeQt7C2wb2PH79rEpg8dCYf5m3g6we3YmXbukauvva+xOXGMTXg0u727jbuFKoLTQZZndlaw9fBlxSbXM4PtSTF15WHzadzeucOSnMvZbByz6aQezaFPes+pDDAjNhbbuOT3I28EvcKI31GorRRGt2zO58wPJR7iBFeI7A2t6avY19SS1NbfDpSEARB6FpXFWRJkrQEWADIwCngAcAb+ApwBY4D98myXHeV8+xQ3VH4nliUiK+DryG4iA2K5bnfnmNUr1HsydpDbOClpa+G4urLOVs5c7rodKPjAFa2doTF3ExYzM3U19VxMekUaccPk5t6hqILGUZF4FeydnDEwcUVZ28fnL18cPb0xsXLG2cvH+xdXJEUCuL3LmO/lI6TXZ9WB1igD2y+P/+9UR8tdxt3CqsLGcCARuM7M8Noa2GLvYU9W85tYePUjbjZuDHstplkJZ3i5C/bSY7bi0LWF9rXVKlwOAXnT63npr7u7HL5jT/P/VejezYsF3aGouoi8tX5mElmBLkENVpejcuN4+a+NwMQogwhqTjJZJBVXF3cKDgUBEEQuka7gyxJknoBTwIhsixXS5L0NXA38CfgLVmWv5IkaQ3wENC65/a7iEan6fLC94O5Bw3ZKoBQZShDPIfw0u8vYWlmaXTOFBdrF8pqW84+mVta4h85BP/IIQBo6+upKiuluqKcKnUFj+96nP/+6SOclR7YOjpjZt7yj0C0dzQvx73M9H7TWxx7uYZaJV/7y4IsW30my5S2bKvTHnf0v4OJfSbiZuMG6GvdeodG0Ds0gq83nWBm7SiK4k5SXpBvuKY+s5Dxme4knF+DbsJ5IibeirOXN9C5maylvy2luKaY6vpqJvedzHPDnjM6f6LgBMuHLwcuBVlXyqzI5O4f72b/3ftb3HpIEARB6HhXu1xoDthIkqQBbIFc4CagYcOkdcCLXGNBVpdmsv4ofD+Ue4gF4QsMxyVJ4tUxr7b6Pi7W7dtax8zcHEc3dxzd3DlVeApbfx96B4a06R7R3tHU6+qb3Ey6Kb0degOYzGSZ0tlPfT495Okmz7m5+WDdN4iH5jzO9j3ridv+Lc5Z9cg6fc1adWUFR37YzJEfNtM3YjCDbp6Cg6V9pwRZOllHckkyP8/Sd9uf/eNsQt1CmeI/BYCymjLqtHV42noC+iDru9TvGt3nYM5BVBoV6eXp9He5+ga2giAIQtu0O8iSZTlbkqQ3gQtANbADOAaUybLcsD6VBXT9o1ct6MrCd3sLezQ6DUnFSUR5RLX7Pq5WrhRVF11Vd+LkkmRClG0LsAC87b3xc/RrsaHqlXwdfLFUWBqCAdBnsjLKM0yOr9fVd8l2R6Z42nqSr85HUijIca/B4a6RLOr3IKd27+DUrh1UFl8KDDMTTpCZcAKFvTW1Ia5U9C7A0d2jw+aSWZGJs5WzYZeAlRNWsmjHIiLdI/G29ya9Ih1/J3/Dz0GQSxDp5elU11cb7UUZlxuHrbktySXJHRpk/ZL5C3bmdkYtSARBEITG2t2qWpIkF2A64A/4oO89OcXEUJM96SVJWiRJ0lFJko52dSO4rix8lyQJpY2SUGVoo2L2tvCy88LOwo6ThSfbfY+k4qR2BVkAq29e3WLz0iu52bix5Y4tRktVbjZuFFUXmRzflRnGK3nZeRkakjZ8n+xd9X3KFrz7EXf8+QUCoobBZQGuTlWDxeEcPnpiAdvf/TflBS13jW+NKz+nga4DGe49nCP5RwBIK0szyiramNswzGsYOzJ2GI5pdVqO5B1hVtCsDu2jpZN1vHXsLd458U6H3VMQBOFGdTX7gdwMpMuyXCjLsgb4FhgFOEuS1JAh8wVyTF0sy/IHsiwPlWV5qLu7+1VMo+06u/bnSq7WrozwHnFV95AkiVmBs/jm7DftvsflGxy3la+Db7vqehqWDBt42HpQUF1gcmxX1spdyVSQ1UChMKPfkOHMWLaChe+sJXrmbKMNqGVZR9K+3Xz89CPs+ni10ZOc7WEqGA5RhpBcrG+Yml6e3mjpNjYolk1nNxm+Ti5JxsPWg3G+4wxBlizLhk272+tI3hGsza0prikmpSTlqu4lCIJwo7uaIOsCEC1Jkq2kX7eYCCQBu4GGR+XmAd9f3RQ7XlcuFwJM8ZvCZL/JV32faf2nsfvC7nbVAdVp60gvT2eAS+On+rqSm40bReprN5O1LW0bCklBX8e+Jsc5unswevZ9LHzvEyIW3EOF16XAU6etJ/7nrXz0xAL2rf+UGpWqXXNpKshqCJbSytMaLd2O8x1Htiqbc6XnAAxtQYJdg0kpSUGr0/Jb1m889PND7ZpTg01nNxEbGMuM/jOMgjpBEAShsXYHWbIsHwI2oW/TcOqPe30ALAOekSTpHKAE1nbAPDuMLMtd/st8ftj8NheNm+Jq7cqoXqPYmra1zdemlqXS27F3oz0Tu5q7jbuhtuxKGp2mS4Pfy3nZepFWnsbrh1/nrZi3Wtz02czcnP7DR3IsRsvsF1/HZ8CloKi+rpbD32/ioyceYu/6T6ksMR1UmqKTdaSUpBDiahxkNQRLOlmn30Pyip8nc4U5d/S/g82pmwF9kDXCewROVk64WruSWZnJprObyK3KRaPT0B4lNSUcyD7A1H5TmRE4g+3p21Fr1O26lyAIQk9wNZksZFleIcvyQFmWw2RZvk+W5VpZltNkWR4uy3J/WZbvlGW5tuU7dZ16uR6FpLhuH2mfGTiT78+1PTmYWJRIsGv7lgo7krW5NVbmVpTXljc615nNSFviZuOGTtaxfPhyBri2LtvX0CfLNziMu196gxnLV+De91LwU6uu4sj3m/jo8YfY/u6/yU8/3+I9L1ZexNHSEWdrZ6PjTlZOuFi7cLb0LIXqQqMnNhvMDJzJd+e+456t95BQmMBQz6GAPgu2+8JuThScQGmtJE/Vvtqx7enbiekdg6OlI152Xgz2GMyOzB1Njl9zcg3ny1p+z4IgCDeqHtfxXaPtvmxJRwh3CyetPK3NTxkezTvKSJ+RnTiz1mto43BlINGdNVlmCjN2xO7Axdql5cF/cLTSbxDd8FkEDB6G/6AhnInbz+9ff2noJq/Taknat5ukfbvx6hdIaMwt9B86AnvXxk1Cm3s4IUQZwrb0bfg6+JoMRn0dfPl66teU1ZbhYOmAvaW94boPEj7g9n63k1GewUXVRXo79m50fUsyyjMIdQs1fD0rcBZrT6/ljv53NBqr0Wn4+PTH5FXl8eKoF9v8WoIgCDeCq8pkXY+6M1vSERwsHVBIijbVZelkHYfyDrXY8LSruNua7pWl0XXtAwlXakuABWChsMDCzAJ1/aUlM0mhYOCoccz/z/tMe+55eg00Dpjyzqeya+37/HfxPNYtf5K4zV+Rn3aOzJIMdmXuYmfmziYfTghRhrAtbVuzrTT6OPYhwj3CaDkxWBmMul5NbFAsvg6+ZFVmAfrvd3p5eqvfb1F1kaGRK8BY37HkqnJJLU1tNPZU4SlcrV3ZkbmDKk1Vq19DEAThRtLjMlldXfTeGbxs9UXaDX2UWpJamoqDpQPe9t6dPLPWaajLulJXttboKA1Lhldu6K1QmBn2lsw9d4ZjW7/n3OHfjbY4KkpPoyg9jQNff4HOXELtqsDe24HAocPJtz+Hs5cPVraX2n6EKEPIV+czzWlam+YY6R7Jk4OfZKDrQH2QpdIHWXsv7uXd+Hf5bnrjRqamFFQX4GF7qR+YucKcOwL1dWAN3ecbxOXGManvJC5WXmRb+jbuDLqzTXMWBEG4EfS8IKsbn2DrKF52XuSr81tdO3T5BtTXAncbdwrUjds4dHcmqz0crfRb63jTdADr3X8AU5/6M9WVFSTv/43zRw+SmZiAdFntv6Jexr5ACwVlHD/5Ocf5HABbJ2dcvHvh4u2DtbsrffJs8Al0or6uDnPL1v0c21rYsjBiIaDf6ig5U98KIrE4kbTytEZNTJtSpDbOZIG+DuzuH+/m6ainjR6qOJR7iEURixjuPZx3TrwjgixBEHqknhdk3QiZrMt6OrVGXG4cMwNnduKM2sbd1t1kv6brMQBuy/6FNg6ORE25nagptzP7m1k4Zmu4QzGW7DNJVBaZbsirLi9DXV5GdkoiADfhQebxb3hb2oSjmwcu3j5//NPL8I+TuweSwnQlgK/9pUxWUom+JcSZkjNEekQ2O3dZlimqLsLdxrinXS/7XoQoQ9iTtYdb/W4FoEpTRXJJMoM9BmNlZsWrca8y9bupWJpZ8uLIF4lwj2jV90sQBOF61+OCLI22+4qrO4qnnWergyyNVsOJghO8Pvb1Tp5V67nbuBNfEN/oeHcWvreXg6UDFbVt71uWrc3nrLKK1XOXcKHiAs9ufYJ/Bj5P7rmzlGRnUZaXQ1lejtHyohFZpqIwn4rCfDITThidsrazxytwAN79g/AOHIhX/yBs7B0ADDVZsiyTXJzMaJ/RJBUntRhkldeWY2VuZbIFyAjvEZwsOGkIso7lHyPMLcyww8HG2zdSVF1EYlEiz+x5hq+mftUoIyYIgnAj6nFB1vWYLbmSl60XR/KOmDxXWVdJUXWRofD5ZOFJ/Bz9Wl2/1RXcbNxMF75rNdfdZ9OWTFaD6vpqqjXVeNp6klWZRXp5Or28/AkcPorA4Ze2LtLptFQWFVKam0NJTjZleTmU5mZTmptNRWEhsqwzef+aKhUZ8cfIiD9mOObi40uf0HB6hw1CUasjtUxfrB7TO4aEwoQW51xYXdgoi9UgRBnC6ouX9oCPy41jhNelHQ4cLR1xtHQkwCmAC5UXeHbPs6ydvBZzRY/766dTpZam4mPv06g+UBCE7tPj/pa7YZYL1Y0zWfW6ep7Z8wyyLPPR5I8ASClJIdwtvKun2CwXaxfKasuMjulkHfVy/XX3i7c9QVZ+VT4eth74O/mTVp5msoM76IvnnTy8cPLwwm+Q8ebi9RoN5fl5hqBL/08ORVkXqKlsPJ/SnCxKc7I4+ct2pqPkx/iXGOPpg6evJSmFLe9tWFhdiLut6SAr2DWYM6Vn0Mk6FJKCuNw4VoxcYXLs4kGL+fH8j6SVpxHkEtTi6wqt9/z+57kn+B6TLTUEQege19dvtA5wQ2SymqjJWnViFYXqQqOO3nlVedfMU4UNrMysqK037lHbUPTelt5f1wJHK0eTjVWbk6fOw8vOiwCnANLL00kvT2eY17A23cPcwgKlb2+Uvsb9rmRZpjw/j9zUFHJSz5CbeobCzDR0Wq1hjATIueW45sLR+I8YppD5OvF5+g0ehl/kEFx9fBt9DoXqpjNZTlZOOFs5k1mRiYOlA3mqPEKVoSbHKiQFvRx6UaQuEkFWByqtKSW5JJm08rTunoogCJfpcUHW9Vj3cyUvOy/yq/KNGpLGF8SzPX07625dx7Qt0wzn8tR5TTa37C7W5tbUaGuMjl2vTWIdLR3JKM9o0zV5Vfogy9/Jn+MFx0krT+OuAXd1yHwkScLZyxtnL2+Cx04AQFNXS+7ZM1w4fZILp+LJOX/G6MlGc53ExVMnuXjqJHz2EY7unvgPHop/5BD6hEZgYW3d7HIhXNpbUUJiqNfQZjOSDc1ohY5zKO8QNuY2bep7JghC5+txQdaNkMmyMbfBxsKGkpoSlDb6ruF7s/Zye8Dt+Nj7YGVmRWltKa7WroZf6NcSazNrarXGmaw63fXZJLY9y4UNn0mAcwCbUzeTXp7eIXtbNsXC0oo+YRH0CYuAu+/jyxPrWL/jPR52uouilFRDZ/oGFYX5nNyxlZM7tqIwM8O9bwAlTipc/PtS3icfR3ePRpmuhiCrsq6SEd4jaE5TzWiF9juUe4jbAm5rslZTEITu0SM7vl+PGZMredka12XF5cYZts25fDnxWgyyrMytqKk3kcm6DoNfJyun9gVZtl74O/qTXJyMjblNlz6Y0Mc9gIq+Vtz+8LM8uPK/eC6ZQfXEPvQfNhJLG+N+WTqtlvy0VMxO5FLxbRwfPfEQ/33kfn5c+QZnDu6jrqYagBBXfZAVlxvHSO/mt29yt3GnUC2CrI4UlxPHXUF3kavKpU5bZ3wuN87o2IHsA9TrmnhqVRCEDtXzgqwboPAdjAOpiroKzpedZ5D7IKNz9bp6imuKmyxY7i4NGavLa8fqdHXX5TJuf+f+JBYlNsrMNaehJsvZ2hlHK0cCnJveJqczRHpE8udhfzZkoyL6DeOkdyHTn3ueRz9az51/e42ht8/ErXdfk9dXlZVy5uA+flz5Bmsevp+da1fjVeNIfGE8Wp22xaycWC7sWFmVWVTXVzPQdSA+9j5cqLhgOFdRV8ETu57gRIG+zYdWp+Wp3U/xW9Zv3TVdQehRel6QdZ3vXdjg8iDrSN4RIj0iDcFjw7Y7RdVFuFq5XpPv19rc2qj4XaO9/rq9A/jY+zDQdSA7M3e2+pr8qnxDdtHfyb/ZvQg7g4OlA7f3u93wdZBLEBnlGdRqazEzt6BPWATj732QeW++x6NrNzBz+YukhejwCB7YKNOlqanm5I6tfPfX5Uw55M2Y6oEgy1e+pBF3W5HJ6kiHcg8xwnsEkiQZnlhtsDVtKzXaGsOxnKocarW1bD67ubumKwg9So8LsjS667PA+koNxe+gXyq4fNuchhYP1+JSYQMrMyuj4vfr+YGE2KBYNp3d1Orxl38uocrQbn8wwdrcmj6OfUxu9Gxj74Bf5BAO9Stg1vMv89jHX3HfG6sYdedcXH18jcYqCxU4bsvk82VPcjZuP7LOdB8vkcnqWMcLjjPUayiA4YlV0D9puunsJmJ8Y0gr0wdZ6eXpRHlEkVCUQK4qt9vmLAg9RY8Lsm6EwncwzmQdyjvUOMiq0gdZnnae3TXFZl1Z/H49fy4Tek8grTytVU8ZqupUaGUtjpaOACwdtvSa2PKooXDdlEpNJeYKc2wtbFEozPDwC2Bk7Bzm/2c1d73wGoEjRhlt41N4IYP/vfU665Y+TsqB39DptEb3c7Nxo6i6CLmFjJfQOuW15bhZ6zvoX57JOl10GrVGzeyBs0mv0Ade6eXpBCuDmeI3he/OtW5jcEEQ2q9nPl14I2SybL1IKErgnRPvUFpTarRZdEOW65rOZF1R/H49ZxgtzCyY3m86m1M38+zQZ5sdm1eVh6et5zXXDyzYNbjJIKtI3XjPQtC3i+gdGkHv0Agqi4s4vv0HTu7YhqZW/7kWZ11g66p/8fumDYyMncPAkWORFApsLWyxUFhQUVdhKPiXZZlNqZsori7G1dq1xZYW5bXlbDyzEZ2sI1QZyljfsVf5Hbh+qTQq7C3tAX0m68vkLwHYeGYjs4Jm0c+pH+ll+iArrTyNUGUog9wHsXjnYhSSAmcrZ+4acBcKSYFWp2V/9n7G9x7fbe9HEG4kPS+TdZ0WWF8pRBnC9P7TAXg++nkU0qWPsqEmK0+tf4rtWmRtZtwr63pt4dDgTwF/YvfF3S2Oayh6v9Y0l8lqrtt7AwelG+PvfZAF765lxIy7jGq3SnOy2LbqX6z/23Nkp+hfoyGb1eBk4Uk+TPgQjU7Dv4/+m7KaskavcbldF3ax68Iu8tX5vHPinda+zRuSWqM27BPp5+RHRkUGuy7sIi43jlmBs/C086RSU4mqTmVoFzLAdQCLIxej0Wn4NPFTjuYdBWB/9n4e//VxVHWq7nxLgnDD6HGZLI1Wg625bXdP46rZWtiyeNBik+c87TwpqC4gR5VDlEeUyTHdzWTh+3Uc/Aa5BFFZV0mOKgcfe58mx12r2cUBrgNIL083mektUBe0ekNnW0cnxtx9P0OmzuD4tu85vu0H6qrVAOSdO8tXK/5M0IjR+PR2pbC6kH7O/QDYdHYTcwbO4YGwBzief5ykkiRG+Yxq8nXicuK4e8Dd3Nz3ZiZ+M9GwpU9PpNKosLfQZ7IcLB1wsHDgb/v/xppb1uBi7QKAn6Mf6eXppJWnGZ7+vDPoTgBcrV3ZlLqJ4d7D2ZS6CYWkIKUkxVDnJQhC+/W4v5VulBYOzbE0s8TR0pHEosRr8hc6NC58v94zWQpJwXCv4RzKPQTog4ZX415tNC5HlYOPXdNBWHexMbfB18GXc2XnGp0rqSlBaa1s2/3sHRh9170sfPdjhk2Pxczi0md79tABAr8rIXnLVjQ1NVTWVfLrxV+Z1m8a0HxWDfT7XDbUITYEFaa2meopqjRVRptCR/tEs3TYUiLcIwzH/J38OZZ/DJ2sa/RZTg2Yyv6s/ZwpOcPx/ONMDZja7PdfEITW63lB1nVcYN0WXnZeFFQXXLNBlrWZdeOarOv8c4n2jiYuNw5Zllmfsp6zpWcbjUkuSTaqn7uWNBXcqOvVRr/E28La3p5x98zngf+sYcCocYbjklamZM8JPn7mEb75/j1GekUbdi9oKchKLU3F3sLesCenv5N/j95O5sog69UxrzIjcIbRmACnAHZd2EWAU0CjekAnKyfG9x7P07ufZrLfZEzUkdQAACAASURBVIZ6DiWpRARZgtARemaQdYNnskBfl2Uumbc5A9FVrMytjJ4uvN6XC0GfQYjLjSOhKIFCdSFZlVlG52VZJqk4qdtbNjSlqeCmtr4Wa3Prq7q3k4cnU5/6M3P+/i+8+gUajquKiyjdtJ+BO6opyNA/FResbLoIH/QdzC9/mvbK3lA9iUanoV5Xj7VZ859PgHMAJwtPNtmTLTYolixVFrFBsUbff7VGzf/O/6/D592T/O/8/6iur+7uaQjdpOcFWTdI4XtLvOy88LD1wExh1t1TMelGzGT1su+Frbkt/zzyT+4PuZ+y2jKj95iv1vc187S9Nttq+Nj5mGwSWqOtafGXeKtfIyiYe175N96zJqC1ufSzWZF2kS+WP80vH7yLu86JstoyymvLTd7jUO4hon0uBVkBzgE9NpPVUPTe0tOq/o7+yMhNduOP8ohi9c2rCVGG0M+5H7mqXNQaNT+m/cjKYys7Y+o9glan5e9xf+d00enunorQTXpckHW97pHXVl52XtfsUiH8Ufh+RZ+s67kmq0G0TzRJRUnMCJyBj70POaocw7mk4iSClcHXXPuGBjYWNqjr1Y2O19TXXHUm63KSQkHguHEkz3CkbrAnKPTfD1nWkbDrJz556mHGZvbmdO7JRtdqtBqOFxxnuNdww7FrKZOlvaInWGvIsoxONt24tSVVmipD0Xtz+jj2wUwyazKTJUkSY3qNAfTbXvV37k9KSQqbUzdTVlsmepq1U2ZFJtX11YZmsG3R3p8J4drS44KsnlD4Dvoll8Eeg7t7Gk2yMjPuk3WjLOPe6ncrdw64EzcbN3rZ9yJLdWnJMLkkmRDXa3OpEPTF76aWNarrq7Eys+rQ13KzceNCbQ7/65vMtL+/Qt+ISz+rmtoavOKrOfT3t0nY9RM67aXA5UzpGXrZ9zLaUPvyLufd6UjeESZ8PaHF9hNX+i3rN5bvXd6u11RpVK2ql7M0s2RMrzEMdB3YqvuGKEP0AVZNGZIkGT2kIrReYnEigKEZbGv9lPETd3x/R2dMSehiPS/I6iGF79He0Tw95OnunkaTbqRtdS43wnsEfx3xVwB8HXyN6rKSipMIVYZ219Ra1FSQVautxcbcxsQV7edh60FBdQHDPIcR2H8Qs/76MjP/8pLRptSyqpZfPniXz/78BKmHf0fW6bhYebHRkpe7jTt12romlxe7Ql5VHsv2LsPTzpP/pbWthim5OJncqvZtcXNl0Xtz3p34bqt3gAhWBvPD/7N33+FtlWfjx79HwxoesuW9R2wntrNjZ0MCYSRsSgqUpj/ghUJbWlZZXW/ft7yllBZaOoBCF3slQFihrECmnT3txNuOty3vIUuyzu8PxYoVy3tJzvO5rlzgo6NzHtlOdOt+7ud+it7n2pRrMWgMU/q99Wa5plwywzNHlMkqaCrgsezHnPvPCt7tnAyypsObubfrN13o5S0c3Inxi3HJZHly0TuAXqV3G2SN93QhgK/aF51Kx/rU9YBjuipx/iK+88SfuOR7d6MNPJOpMlWU8/6Tj/HSw3dTsienXwsMdxsjTyZZlvnx1z/mprSbeDjrYTblb3KZXmu3tPNuwcBb2JS0lNDU3TSqe48kyBqJ9OB0FJKCa5NFkDUWuaZcLk+6fNiZrO6ebu7dei8PZj3IvNB5opXGNHDOBVnevH3LdNKv8H0a1sr1zWTVd9Zjs9s8uk5Op9LRae1fkzUR04UAz6x5hhXRK1yOKRRK5lxwCbf/8QXqF/qD+kxxfEN5KV3v7EP17/3kbvuSHpvN+dhUtnGo6aihsq2S22bfxqLwRfTIPRyqP+R8fHPRZn61+1duv7fg2OqmyTy6IGu404UjlWZM47XLXiPcN5xATSDN3SObAhUcNVUnm06yJm4NzebmAX/+feWZ8vBV+3LljCuHXGUreIdzLsg6V6YLPZ1WpZ2W04V9xfifyWT1ZrE8tegdJne6ECAzInPALu0anZ5H7nmWr9Z1E7xqIWrNmUyatb6FLX99ir/ffTv7PniH7s5ORyZrFMXF4yG38czPVpIk1qeuZ2P+RuD0noz5G/H38Wdf7T7ncyw9FsBRKF/WWkaHtQOb3eb2+oPptI6+h9lgJEkiI8QxtW3wmX6ZrN7v/0Qqay0jUBNIkDaIuIA454eAvh8uz5ZrynV+39OD08kz5Y3rmCw9llH9ngmjd+4FWedI4bun0yg1rtvqTIMWDmeL9oumoq0CWZbJqclx6cDtibQqLRa7pd8KObNt/Fo4jESgNpDHL32SfwV/ze1//jtLrr0em6rPNJypga9f+Scv3HUrmp0VnKru361+Mpw9DXzljCvZXrGdo/VHOVx/GKvdyrfTvk12dTbg2Hfx5i03A1DdUY1BYyDAJ2BUgUy7pX1YqwvHwqAxTKtM1raKbdz00U0TvmKy7+9FkiGJ4pZiWi2tXPDWBXxW9tmAz0kzpgGQYcwY96awT+57ks2Fm8f1msLgzr0gS2SyPIJGdda2OtOkhUNf/j7++Ch9qO2s5aPij7gq6aqpHtKgFJKi34IEcPTJ0qjGf7pwODJCMlBIClqUXSy5/lu8e2ENy274NnpDoPOc7s4O6rbuI+b1Cj559o+YKsondYy9rTl6GbVGfrn8l9z/9f3889g/uS7lOpZGLXVuufTmiTc5ZjpGQ1cDxS3FJBmSCNIGjWrKsMPW4dwcupdst2OzWLB0dWKzWsccTBg0BlotrWO6hifZVrGNk00nOVzfv0XIeOobZPVOZ39U/BEJAQk8uvtRipqL+j+n8czimBj/GDosHTSaG8dtTPVd9dR39e+FJ0ycc3KD6Ok2LeWNdEqda8f3aVorF+MXw4vHXyQlKIXYgNipHs6QeqcM+05BmW3mCZkuHK7eTvSp9lQCA0NZ/o1vsfiK68jd/iX7PniXpupKABR2OP7V5xz/6nOSFmaRdeV1RKdljOsU7QtHXuDGWTfi7+MPnOnif/aq0TVxazjecJx/Hf8Xv1z2SwwaA9Xt1RypP0JeYx4rolawp3oP9V31JAUm0d3TPeLid6ulm46yanwb7Xy650/UlZbQZqqnq7UVuU+PJUmhwNcQiH9IKP4hYQSEhBIcE0dEUjLG6FgUysEbFhs0hlHXjPXaVbULH4WPR2w6nVOdw2WJl7ExfyPzw+aP+PmflH5CrF+sc1pvIHmNedw2+zbAkcn6pPQTtlVs4/7M+6nrrOPerfey6apNzn/3zDYzp1pPkRLk2BFBkiTSgtPIM+UR4x9DTnUO18+8fsTj7avV0jqtAmZvcM4FWWK60DNoVK7ThZYeCyrF9Pt1jPGP4c2Tb/LYeY9N9VCGRafS0WXtgj4x1Xh2fB+NNGMax03H0al1xPjFAKDy8WHumrXMueASCvfnsO/9d6jKP1O/UnxgL8UH9hKRnErWld8gefEyFGPc/aClu4U/H/wzcQFxXJpwKTB4F/+75t/FpQmXOvdkzIzI5L93/jdXJF3heNOsyUFCIs2YRk1HzYBTct2dHZgqTtFYeQpT5Zn/ttTVIskyncDRQcYt2+20NzXS3tRIdcFJl8dUPhrCEpKIzZhLwvyFRKXM6hd0BWoCx7yo4MOiDwnVh055kFXTUUNLdwsPZj3IVe9eRaullQCfgGE/v8few+/3/p7rUq4bMsiq7aglys+xEjbRkMiuql0YtUaWRi5FISn4oOgDvjz1JWsT1gKQ35RPgiHB5f0pPTidfbX7eGLvE9hl+9iDrO5WWrtFkDWZpt+72hDEdKFn0Cq1dPWcKbKezpksP7UfF8ZeONVDGRa9Wt+v67vZNnXTheB4o3kr/y0ifCOI8Y9xeUxSKEjJWkZK1jLu+NcNrKyKo/7oCTg9RVZTmM8Hf3icgNBwFq67itkXXIxGr3d3myHtrdmLJElkV2c7g6w8U96AXfyVCqXLZuBLIpew9dRWfr/q9ygkBS8df4lw33AuT7qcE00nMLXUUV1wkpqyIoqLjtJWVUNXbQOdTSPPIilVKiSlErutB3vPwIXONks3Vfl5VOXnkfPum2j0vsTPmU/ykuXMWJiFj04/osJ3S48FS48FPx/XOrGSlpIp+fvd0t3i0rg2uzqbxZGLCdGFsCxqGR8Xf8yNs250eY7NbqOgqQBwdMrvm9XdWbWTus46l9YsA97b0kKgxjGtHR8Qj9lmZn3qeudij+tSrmNT/iZnkOWuxUuaMY1Htj/CRfEXOWv6xqLV0kqbpW3M1xGG79wLskQmyyP0K3yfhi0cABZHLCZUH+o1v3NnrzC02q1ISFNaL9e7yio1MLVfkNVX4Ix4gs4/jytuvYd9H77raPNgtQLQWl/LVy+9wK63XyVj9RpmLV9FZMrMEU0lZldnc0XSFWRXnXmzy23MHXYX/wtjL6SirYIEv3gaK08RViqjbCyj+OB7+JWepLJlL6/x+rDHI0kKugMUhCclMydjOeGJyQRFRqE3GFCqzvy8bFYrHU2NtDXU02qqp6W2htqSImqLC2hvNLlcs7uzg/ycneTn7ESl9iFxYSaqtChabcMrfH8t7zXym/JdMreyLFPSWjLp7Uv21uzlB5//gJfWveSsmcupznFuLn5d6nU8te8pbph5g8vvwZ8O/oktJVsAuCjuIh5e/LDzsbfz3+bypMv7bf5+Nrtsp93S7pxW1qq0XJN8Ddckn+niviZ+DY/veZxTraeIDYh1O+2cFZHFlTOu5L+X/TdLX1s65p0x2ixtYrpwkp1TQZZdtmOz26ZdgbU30qg0/ZuRTsNaueXRy1kevXyqhzFsOpXr/oUT0Yh0pHqn4vbX7WdD2oYBz+tt/mqccSWX3PEjVly/gYOffMjhz7dgbnO8sVi6Ojm45QMObvkA/+BQUpcuJzlrGZEpM10CE3dyqnN44vwn2FG5g4q2CmL8Y8g15XJt8rVuz7f39NBcW4PpVBkNp/+EnSrjT3+4DtluZz4+gA8VDF6ArVSpCIqMxhgdizE6luDoGIJj4giKjOa2L77LRQtuICsia8Dnq9RqDGHhGML6T2l2NDdReTKX0kP7KTm03yXoslktFOTsghxIU8GWsidJW7mauDnzB6zj2lW1q9+0Z21nLR3WDlosk9sG4u38t8mMyOS+r+7jjcvfwKAxkF2dzQ/m/wBw7IrRbm3nuOk4s0NmA45M3ObCzby87mVKW0t5Ne9V5/XqOus4UHuAl9e9zHc//e6g926ztKFX611KIH614lcu52iUGq6YcQXvFL7DPQvvIa8xz9mct1eoPpRfr/w1AEaNkUZz46iDVbtsF0HWFDingiyr3YpaofboXkXnCp1S169P1nTMZHmbszNZZpt5QhqRjkRvAfDOyp3EZA2cyYrxj+FA7QHn176BQay88Tssufab5G7byv6PN9NUdSYD0WaqZ/9Hm9n/0WZUGg3RM9OJzZhLVOosQuIS0Pn5O8/treWZaZzJ0kjHSkGj1sjxumPcl3oX1QUnaayqcPyprKCpupKm6qpBp+rOJksQEh1HuY+JGclziZ+RztNl/+DNDZsGDGrG2vHdNzCI1CUrSF2yAlmWMZ0qo3BfDid3b6ehvNR5nsoGudu3krt9K3pDIDOXn0faitVEJKc6/z3t7unmcP1hZBwbXvdOi5W0lIy6RcVoNZmb2FGxgy3XbeHvR//Ohi0bCNeHo1FqiPV3LEBRSAquS7mOjfkbnUHWl+VfkhKYQlxAHApJ4bKLwPtF73NJwiXEB8TT3N086AeQlu4WDD4Gt4/1tT5lPRs+3kCuKZfSllJSg1IHPNeoM2Iym0YdZLVb25GRRZA1yc6pIGu6bEI8HWhU/TeIno6ZLG+jV+ldOlObe6Y+kwWQbkx3BFmDTBfG+MXwftH7/Y6rNVrmXbyOuWsupezoIU7u3k7hnt2YO9qd59i6uyk7cpCyIwedx7T+AfgHh6Dz86Ohp4VLOyPZVPALYlsbKOh8jaLOl7iiy5/N7z004tdjCI/AGBOLLiKEhBmzOeVj4l3Tf3hg7TNcu/labjhvPQmGBIpP/R/yIJ8JO6wd49YnS5IkQuISCIlLYOk3bsBUcYqTu7eTt/Nrmk+v4ATobGl2ZgP9jMHMyFxKcuYSaozdJAclU9NeQ01HjbPou7ilmPlh8znReGJcxjkc7xe9z+rY1Rg0Bu5deC/nRZ+H1W4l0jfS5bxrkq/h6s1X82DWg/iqfdlYsJHrUq8DINI30tmpXa/Ws792P+tT1qNUKIn0i6Sqo4okQ5Lb+zd3NzvrsQaTFJjEC5e+QLO5mbsX3D3o37VgbTCNXaNv59Da7SjyF4Xvk+vcC7JEtsQjaJXa/i0cxM9myrnLZE1l+4ZeGcEZ+Kp9B33jOntD7rNJCgUJ8xaSMG8hF91+F6eOHSZ/zy7Kjx2mpbam3/nmtlbnNCOAFig/PbU33I8DfkFGgmPjCenzxxgTi4/W9XtqbziOqeYNZFmmoq2CaL9oNEoNgZpA6jrriPSLdHv9idq7ECA4Jpbl37yJZeu/xdpnVvCA/jsU5eymo+nMG317o4nDn37E4U8/Ah8Vi2aEUBEeQUF1LlEpjiCrpKWEBWEL2FO9Z0LG2dexhmN02brYmL+R/1n+P4BjAcLiyMVuzw/Vh5IVnsU/j/2TdGM6BU0FrIlb43xefEA8Ja0lpBsdbUTSlzrq72L8HL9rAwVZZxfcD2a4m8YbtY5M1mi1WlqJ8I2gqLnIOasjTLxzKsjqsnV5xBuG4KhHMNvMyLKMJEnTtoWDt/HE6UKAheEL+xUony1cH06TuYnunu4hx6xUqUiYv4iE+YsAaK2vo/z4ESpyj1FfVoKpstxZND8UXYABvyAjQRFRBEXFYIyOwRgVQ1Bk9LBXMgZqHfsDmswmdCqdc3Ve79ZMUxFk9ZIkCXu4Lxlrr2bNzXdw6thR8nZ8RdG+bJdsIBYbcl4N0Xmw7+unqZnl6FdW2VnA6pWrscv2Ca3xK28t57b/3EZ6cDoLwhawMGzhsJ733bnf5Q/7/8CB2gP8cMEPXWY7kgxJFDcXE6INQZZl51TdUAF9c3czAZrht4YYjmBd8Jgak7ZaWjFoDPj7+NNmacOoNY7j6ISBnFPvaiazSfxieQilQolSoXS2brDZbWIq1wPo1XrXIMtDpguDtEHct+i+Qc9RKpSE+4ZT1V5FoiFxRNcPCA1j9uqLmL36IsDRW6qjpZk2Uz1trU089MWPeWLV7/DR6lCp1ah8NOgNBnwDg4YsmB+OIE0Qzd3NzoL6Xr1v5u4K2609VuyyfVKC4N42DlF+UcTPnU/83PnYe3qoPHGcwr3Z5O/dTXtDn07iskxF3jEq8o6RDBzb/gLLDSHk7dvBnIXno/IZ/7/r2dXZXBR/kbNQfLhmh8zmH5f+4/SwZTpbmulobqKrrY3Yai2FRdvoUJ9gRXUMu956BZvVSlBDI5VUkXNChcrHB5WPBrVWi9pHg1qjob6qgCCzgqr8EyhVKmcgPlTj18EYtUYauhpG/fze6cLeKUPxXjg5xhRkSZIUCPwdmA3IwH8BJ4E3gQSgFLheluWxtQseJ41djRh14hfLU+iUjqyJj9JnWm6r4410Kp1LYawnrC4ciRi/GCrbK0ccZIHjDfaJvU9wpP4IkiTxq+W/Iil5Jq2NJyEllNTFE7dKVKfSYZftFDYXEu0X7Tzeu2LSnQ6rY0udyVjIE6hxZNrKWsv4+Y6fY+/TUZ5Q6Ly4gxhzGDepLuZIzlbay6tcx9pgIqFBzZd/+CPbNM8SP2c+SQuzSFyQib8xZMj7/3bPb7l9zu3Oxq7uZFdnc0HsBUNey97TQ1NNFaZTZTRVV9HaUEdr/ek/DfXYLN39nlNJHiFA9v43nccUwI7dLw14Hx/g9TcfcH4tSQp8jUYCgkMJjU8gYkYqEcmpGKNjhtUoN1gXzMmmk0OeN5DexqsBPgHTsvj9mUPPcEXSFcQFxE31UFyMNZP1NPCJLMvrJUnyAfTAT4EvZFl+XJKkR4BHgIcHu8hkMZlNBGsH/ksqTK6+bRymazNSb6NT6ajtqHV+PdXd3kdqqGmcwbx4/EUO1h3kkcWP8HLuy+yu3k1SoGNj36RA97U340WSJAI1gRxrONYvk7Wjcofb57RbJ35z6F4BmgBaLC2cLD9JhG8EG9L7t9KI9osmRBfCjMvWsOHt63kq7mcczP6c6mPHUfZZZGnr7qZoXw5F+xx7OYYlzCBpYSYxaXMIjo3DNzDIJXA8bjrOK3mvMNM406XPVF899h721OzhkcWPOI/Jdjst9XU0nCpzttEwnSqjsaqCHtvwV32OF1m2025qoN3UQFV+Hoc/c/TiUmt1xKbPdtYLBkZEuQ2cjVrj2Arfe4MszfQMst4tfJdY/9jpE2RJkhQAnA/cAiDLsgWwSJJ0NbD69GkvAl/hIUFWo7lRpEg9SN+GpBa7WJTgCfQqfb+aLK/KZJ3e4y1MH8bskNmE6cOG9byc6hxezH2R1y57jUi/SAqbCzlY51hpWNxSPKrM2EgFaYM42nCUm2bd5DzWW5PlTm8mazIEagJpMbeQXZ3N+tT1zAudN+C5obpQ2tTdxCzLojC2g+PLZL4ffBP/2vw7gqslLA2ufbTqSouoKy3CMQECGl9fgqPjCAyPwD8kjG2tOSy0xrPvwJcsV81FrdWi8vHBZrFgNZuxmLsoqMlj9qkgTrz7EXvq6xz9ySrLsXX3z0oNxUenw88Ygs4/AI2fL5/WfoWkUXHlzKsJ1BtRqtV093Tzz0MvcOusW+ixWLBaurGazVi7u7F2myk05ROgDiBIbcBmczSD7Wxx39DVau5ybgMFjpWnKYuXM2vFKsISkpwBV7A2uF/hu6XHMuzeWa3drQRoAqblCsNOayc1HTXD6sQ/2caSyUoC6oF/SZI0D9gP3AOEy7JcDSDLcrUkSW7/lZMk6Q7gDoC4uMmJPE1dpkGXgAuTS6vUOntliRYOnkGnPqsZqZdlspZFLuNg3UFezn0ZGZl/r/33sJ737OFn+cninzgLzNOD052NKEtaSlgdu3qCRnxGkCaInJoc10yW38CZufFs3zAUg8ZAfVc9h+oP8dvzfzvouZIkkWhIJNeUy0u5L3Frxq3Ez5iP3JZMZMgcLvRbRslBR1BRkXe8Xy+x7o4O51Y/ABpgLgDFvLzp7gHvmwLsZdOwXo+fMdix0jM6FkNoGAGh4QSEhhEQEobG19clk/T8pt20Wdv46w0/cDn+E8uzzL7mKrcf3L/32ff4dtq3OS/mPOcxm9VKu6mB5roaaosKqCnKp7ow32W1JkBLbQ37PniHfR+8Q1BUDGkrVpGxag1GvbFf4fsbJ97gvaL32HTlpiGnjXtXF/YWvk8nJa2OvTVHm8WeSGMJslTAQuBHsiznSJL0NI6pwWGRZfl54HmAzMxMeQzjGLZGc+Ogn8CEyaVVaV2nC0Uma8p5eyYrLTiNP1/4Z6x2K5dsvISSlpIhs1Cd1k5yTbmsjF7pPJYSmEJFWwVdti6KW4r5r9n/NdFDJ1AbiF22u9RkhehC6LR2Ons19TUZKwudY9ME8nHJxyQGJA6rNUGiIZGf7fwZy6OWc0XSFYAjUGvpbsGYGo0xKppFl19Dd2cnZUcPUnr4AA3lpZgqTmHp6hzi6sOnNwQSEhtHcIyjfUZwTBzBsXFofYcfnCYFJmHpsfQLYqL9oqloq3AbZLlr4aBSqwmMiCQwIpKEuQucx5trayg9fIDSw/spP3oYa/eZ/oFNVRXsevtVdm18jYR5C/FTmbHZrKhOL7bIrs6mqLmIow1HmRs6d9DXMZ1rskpaSgjWBk+7IKsCqJBlOef01xtxBFm1kiRFns5iRQJ1Yx3keDGZTaLw3YNolBq6bF3O7Y5EC4epd3YLh+6ebq/KZPVSK9RcPeNqNuVv4oGsBwY990DdAdKD012CGLVSTaIhkRONJyhvLSchIGGCR+zIZCklpcvUjyRJRPlFUdleSUpQisv5kxlkBfgEkGvK5bbZtw3r/JlBMyloKuAXS3/hDE7cbTSt0eudHefBsfigvcmEqeIUrfV1vJzzAhnqGfiaVZTUF6KRVfiixWa1ovLxwUejBR8VR1pzWZ12CcHh0QSEhBEQGkZwdCx6w9ANQYeSGpSKRP8sUW+Q5S64GW4zUoDA8AjmX3IZ8y+5jB6blbKjhzixcxuFe3afCbhkmdJD+1lNMH//0W3MvXAts1ZfwIG6A9ycfjMb8zcOHWT1ThdqAmgye8RaNAB2Ve4itzGX2+fcPuprFDcXszJ65bhsoj3eRv2uJstyjSRJpyRJminL8klgDZB7+s/NwOOn/7t5XEY6Dhq7GkXhuwfpzWT17icptjuaemcHWV22Lq/KZPV1Xcp1bNiygbsX3j3ooorsqmznpsF9pQen83nZ5xi1xkmpfQrUBhLpG9nvw0ZvMf9UBlm9AcPSqP7fJ3e+lfYtvjXrWy4lAIGaQMrbygd9niRJ+BtD8DeG0GppZVvNf/PrG1/DR+nDJyWf8FHxR/x5zZ+d53f3dHPzlpu5JOFGrpigbOP35n3P7fEwfdiALRVaLMNvRtqXUqUmaUEWSQuysHabKdq/h2NbP3PZiaCjsZHdG19j96bXuSg6nAuT5vGDsl/wUNZDzv5q7rRZ2pyZrLLWshGPbaK8cPQFck253DTrplH/PSttLWVN3Bo+Lvl4WH3yJpNijM//EfCqJElHgPnAYziCq4slSSoALj79tUcQfbI8S2/hu2jf4Dn6batj866arL5iA2JJCUrhi/IvBj0vu3rgIGtLyZYBu3qPN6PG6LZmdKA2Du3W9kkLsgwaAxqlhgVhC4Y+GUcm8ewaS4PGQLPZffG3O3tr9jI/bL4zQF4cuZh9tft4v+h955+fbv8p0X7R3Jpx6/BfzAhplBq3b9pGbf8aKXCsdOy0duLv49/vsZFQa7TMWn4+63/2KLc9/QJZV6/Hpu3zQVSWCaro4Ys//IGrvwjj9X/9hvamgVcftlpa8ffxn7TC9x575eQv8gAAIABJREFUD8cajvU73m5pd26xVNpSSnFLMQvDF7KlZMuo71XcXExyYDIRvhFUtVcN/YRJNKb5GVmWDwGZbh5aM5brTgSb3Ua7pX3YKVxh4vUWvov2DZ7D7XShl2ayANYlrGNbxTbWJa5z+3ijuZGq9irnBsF9ZQRnUN9Vz6UJl070MAHIisxy2wcq0jeS6o7qfscnM5OVHJTM/YvuH1OGwKAx0GIZ/ibROdU5LsGvUWtkQ/oGsquyXY7dt+i+KcmCB2uDOdV2qt/xVksrfj5+zg2yx0NgRCTn33QLm8OPkNWegPJIDeXHjjgfV7XbaP3yMM9/dQvJmUuZe9Fa4ufMR1KcGcNkt3DIa8zjjk/vYNuN25zZ2R57Dw98/QAH6g7w8rqX+bD4Q66ecTWZEZk8d/g5576RI2Gz26horyA+IN65UGQyVgMP1zlTBNNkbiJAE4ByGE3fhMmhVWkx28xiT0kPMp2mCwEyQjJ4OfflAR/fU72HReGL3NYDJgclo5JUk/YPdpIhyW3WLFgXzImm/psrd1g7CNWFTsbQCPAJ4Ka0m4Y+cRC9he/DlV2dzePnuU6E3DX/rjGNYTwNtM1NS3fLhH2YD/YLoScqmKsuu50r/rmGn2pv4eT2r517bMp2OwV7dlGwZxcBoWGkLF5O8uJlRKbMdEwXaiav8L2us442axt5pjzmhM4B4K+H/orFbuHnS3/OvVvvpdPWyYtrXyTWP5ZHsx/lZONJZhpnjug+FW0VhOhC0Kq0g7Y8mSrnTJDVaG4ctFuwMPk0So0zkyXaN3gGvVrv2sLBi6cLAWYEzqCqo8rt6jyA7ZXbB6wz0ig1pAenM8s4a6KHOaiBmlB2WDuID4ifghGNjrvC94HUdNTQZG6a8u/9YIxaI6au/hs2N3c3Y/AZeT3WSO65pWQLSQkZXHTpnay+6b84vOMz3n77aUJNZ/4dba2vY/9H77H/o/fQBRhYHhhM2YED6BNCJmW6sLdeLacmhzmhczhYd5D3i97nzSvedHSvbzxJQVMBCYYEAG6YeQO3fnIrOpWOtYlreTDrwWHdp6SlxPnhJMY/hsq2ygl5PaN1zgRZpi5Rj+VpegvfLXZRk+Up1Ao1siw7Al+F2uunC9UKNTMMMzjZdLJfPVG7pZ2tp7YOuifiv9b+a8qnsoN1/ZtQwuROF44Hg8ZAc3ezc1P4weRU55AVkTWuU27jbaBMVqulddw3h+57z82FmylvLXfut6hSq1m4eh0/rH6U15f+g5LtO8n9+guXzbu7WluY0apj8+8eRalWMydI5lDAxyQtzCQgZHgNe0eqvque9OB0squyuX3O7bx+4nVuybjFmex4IPMBbPKZHmm3zb6NK5OuxGK3cNcXd5FkSBrW9GFxS/GZIMsvhiP1R4Z4xuQ6d4IssaWOx+ktfLf2iEyWp5AkyTllqPZRe12fLHfSgtPINeX2C7I+LvmYpZFLCdENvHfeVAdYMHDGpNPW6VVBllalRSkp6bJ1DbmK7Ox6LE/U+3M5O2gcSfuG0dzzcP1hfnf+71xWm0qSRIx/DB0GmQtu/i7nf/sWyo8doXDPbgr3Zbt0m++xWoms8+GLfzzDF/8AY2wcKZnLSFqYRURyyrD2Uey1v3Y/C8MWug2a6zvrWZewjmcPP0tNRw07KnbwsyU/cxmzWlK7fB3uGw7A0xc8zS2f3MJM40xnvWRRc5GzRcMl8ZcQqndMlZe0lDj/bkf7R3tcryzP/ZgwzsSWOp5Hq9LS1dMlGpF6GJ1KR5fVUZfV1dPl1dOF4FglmGvK7Xd8Y/5GrksZeaHtZAvSBtHS3eK6KTPel8kCRzZrqHqgLlsX2yq3cX7M+ZM0qtHRqXSoFCo6rB0ux901Ih0vmeGZPLbyMdYmru33WN/dAZQqNYnzF3HxHT/kzudeZO7dt1A3R0dwTP/dVRpPlZPz7pu8/osHeO7O/8eWvzxJ3vatA24D1Ku+s55bPrmF46bj7h/vqic+IJ7UoFQezX6U82PPH/b3JdGQyI8W/IhnDj3jPPazHT/jcP1hNhdu5pPST5zHy9vKndPmvStxZXlS+psPyzkTZJm6TKImy8NolVrRwsED9a3L6rZ593QhuA+yjpuO09LdwrKoZVM0quFTK9T4+vjS3O36ptdp7USvmpy9C8dL75ThYD4t/ZS5IXOHtR/fVDNqjf2mcicyyDJoDFw540q3j/U2Rz2bQqFEigmka3kktzz5DLf/+e+cWNCDJjmSHoVrMNLV2kLu9q18/JcnefaODbz88D1se+3fmCr7r6LMNeUiIbExf6Pb8dR31hOmD2Np1FK2VWwb8Qeay5Mu50jDEarbqznReIJGcyO/Wfkbrki6gsr2M3VXFW0VztYnBo0BhaQY8ndsMp07QZaYLvQ4GpWG7p5umsxNXveJfDrru8LQ2/YudCc5MNm5RU6vLcVbuDr5ao+u+ekrWBvcr/i90+a+mN+TBWoChyx+31SwifWp6ydpRGMTrAvuN5U7kYXvg3G3su61vNd4Yu8TzvYNAIawCFoy/PloYQUHvqmn8/IkZl9wsdvu+HWlRezdvJHmmv69p3JNuVw540o+Lfu0XzYPHJmsEF0Iq2JWMSdkDpnh7ro9DUyn0rEuYR3vFr7LxvyNXJt8LUqF0tmcFxxZz5buFpeN4GP8YlyCsKl2btVkiUyWR+ntk/Vh8YdcGHfhVA9HOK1vkOXtLRzAUVeVaEgkvynfuXdpSWuJV0wV9uotfk8m2XnMW6cLB8syFDYVUtFW4fFThb3cNSRt7W6dkn6MMf4xfFn+pcuxHZU72Fe7j0RDIovCFzmPB2gCKG0t5e7ld/Ne4Xv84uJ7kO12aosLKT3i2EuyuuAE9p4eFEoVsRn9t+zJbczlyqQrabe0s6Vki0tgbLPbaDY3E6wLJtw3nFcve3VUvczWp67nB1/8ALPNzKarHJt/983YVbVXEeUX5fJh6d9r/41OpRvxvSbKORNkiS11PI9GqaGyrZKiliIeXfHoVA9HOK1v13dv3bvwbL1Thr1BVt8pBm/g7s28w9rhldOFg2WyNhVs4prka7xmH9MBM1kTNF04mLN3BpBlmVxTLn+84I/c/9X9XBB7gfOxAJ8A1iasZUbgDGo6agCQFAoiklOJSE5l6TduoLuzk1O5R2mprcZH2z9oyTXl8lDWQ2hVWp499KxLkNVobsSgMTh/jqNtFjvTOJNwfThB2iDn9HGMvyNTJcuy27/Hnpbd9Y7f5HEgttTxPFqVlkP1h/hGyjcG3XNLmFwu04U2MxqV5+wDNlqpQakUNBUAYJftVLZXEuPnPUFWsNb1zdwu2zHbzB73hjKUcH242+71vXZX7eax8x6bxBGNjbvgt83SNuYtdUYjyi+Kmo4abHYbKoWK+q56euQelkUu428X/80lu3bTrJuI8I0gQBNATUeN27YaGr2e5Mwlbu/V0NWA2WYmxi+GKN8ofrrjp9R21DpXB9Z31TtX/43Vz5f+3CWb7qv2Ra/W09DVQEV7BdF+0eNyn4niHQUJYyTLsmN1oU4EWZ6kN0PiTdM254LeIMsu27H0WDxqs9XRSgpMorilGHC8QfT+Q+0tzi6w7p3G9Zaasl6JhkRKWkrcPtZp7aSyvZKUwBS3j3uiYG3/HmYdtg781JP/odFH6YNRa6S2sxZwZJrSg9ORJIl5ofNcGtdmRmQS4x+Dv9oRDLZZ20Z0r1xTLmnBaUiShFKhZHHEYnJqcpyPN3Q2jNtuBOnB6f12Quitu6poqyDWP3Zc7jNRvOtv6Cj1bqQ6Hd4sppMQXQiLwhcxJ2TOVA9F6KM3yOrdzd7b3sjdSQw48+Ze2V7pVVOF0L/xpTdOFYJj66DeYPdsJ5tOMiNwhlf1zDPq3EzjWjqmLIDvWxTeG2QNRpIkInwjnFOGw5VnynO59tLIpeRUnwmy6rrqxi2T5U60fzSn2k5R0V7h8Rlp7//Xcxj8ffzZdsO2qR6GcJakwCT+vfbfU7K5qzCw3hYO02WqECBMH4alx0JLdwsVbZ4/xXC2sxuSdlq9qxFpr/iAeCrbKrHarf0eG05Q4GnOnsaFqctkgevKurMDoYGMJsjKNeWSbnQNsrKrsp39qRo6GwZt8jtWvfVn3lBbeU4EWcC0+DQuCJOhN5Pl7fsW9iVJknOqqqLN8z/9nq1fJsvmfSsLwTGlFeEbwak2932X0oLTpmBUo3f2z8Uu24fV0X6ixPjHODO2uaZc0oxDfz9HGmT12Hs4ZjrmEsDF+seiVCgpaXXcu76rnjDdxGzXA2cydpXtlR7/gUlEHoIguOjt+G7uMXvUUuixSjQkUtxSTEW759dxnM1dJsubasr6SjQkUtLcvy5rOmSyumyOHRKm6kP9xfEXs7lwMzsqd9Bt7x5WABKhH1mQ9aeDfyLRkOjyd0iSJGc2CxyNSEP0E5vJOlJ/BI1S4/GLpkSQJQiCC51Kd2a6cBrVMSYaEiluLvaKKYazBWsdGZPe6Rhv7Pbey11dVpeti4q2Cq8qegdHK4Suni4sPRbAsen4VE0VAswInMFPlvyEe7feS5oxbVilGBG+Ec5i+aF8Wvopn5R8wu/O/12/a/ety5qMTFZpa6lXZKRFkCUIgguj1khVe5Wj27uXNyLtK9GQSElriVcUy55Nr9YjSZJzuyNvbETay90Kw/ymfBINiR6xIfdISJKEUXOm+L3DNnVF773WJa7j1tm3sipm1bDOD/cNH1Ymq6i5iP/L/j/+cMEfCNIG9Xt8SeQS9tftp6i5aFxbOLgTrg9HJam84sOSCLIEQXCxMnolRxuOUtZaNq2CrCRDEicaT9BkbnLZhsNbGLVG59Y63lqTBWembfvyxqnCXr3d+MGxsnAqM1m97pp/FxvSNwzr3OHUZLVZ2rh36738OPPHA/6cgnXBPJD5APduvZdG88Q2/1YqlET5RYkgSxAE76NX61mbsJY3TrwxbQrfwTHF0GhuJNI3EqVCOdXDGbG+PZk6rZ1eWy/Xm8nqnfoEON5w3GuDrL71ct4Y/EboHdOFfX8efdllOz/d/lOWRi7l6uSrB73WNcnXsCRyCf5q/wlvxRHjH+PxRe8ggixBENxYn7qe46bj0yqTpVaoifOP84pPv+4YdWfezL21hQM4ttbRqXTOOqDunm6+rviaFdErpnhkoxOkDXLux9hh8b4gS6/Wo1FqaOpucvv43478jRZLCw9lPTSs6z2c9TB/WfOX8RyiW/cvup+L4y+e8PuMlQiyBEHoJy04jfTg9GmVyQLHlKG31WP16pvJ8uaaLHDtwP9Z2WdkBGd4RVbCnb77MXpjJgsGnjLcVrGNjfkbeWr1U8POTKmVauaG9t9QerzNNM6ckj0iR0oEWYIguHXr7FuZZZw11cMYVyuiV5AZkTnVwxiVvtNSnTbvXV0IMDdkLu8VvIcsy2zM38h1qd67tZZBY3Bmstot7V4ZZM0MmsknJZ+4HCtrLeMXO3/Bk6uenNDGotOdCLIEQXBrbcLaYRfPeov1qetZl7huqocxKmH6MOq76oHT2+p4aZ8sgDvn3UlJawm/2fMbSltKWR2zeqqHNGoGnzOZrE6bd07jPpj1IP8p/Q+flX0GOKaj7916L3fNv4v5YfOneHTeTTXVAxAEQRCGFqoLZWfVTsC7a7LA0Yvtjxf8kRs+vIHrUq7zqv0Kz9Z3urDd0u7xzTHdCdIG8dQFT/H9z77Pp6WfUt5WzpyQOXwz9ZtTPTSvJ4IsQRAELxCiD6GhswHw3oxJX9F+0bx62atePxUVqAk8U5Nl7fDK9iAAGcEZPHfxc5S1lqFSqFgVs0rsKzsORJAlCILgBcJ0YdR11QGnpwu9uCarV3xA/FQPYcz61mR1WDu8MpPVKz043WtbaXgqUZMlCILgBUJ0ITSaG7HLdq9fXTidGDQGWi2tALRb2/FViZ+LcIYIsgRBELyAWqnGT+1Hk7nJsbrQiwvfp5O+maxOaye+PiLIEs4QQZYgCIKXCNWHUt9V79ggWgRZHsFf7Y/ZZsZqt4pMltCPCLIEQRC8RKgulLrOOq/vkzWdSJJEgE8Ard2tjmlckckS+hBBliAIgpcI0YVwqu0UPgofVAqxbslT9LZx6LB2iEyW4EIEWYIgCF4iTB9GWWuZmCr0MAaNgRZLi9evLhTGnwiyBEEQvESILoTy1nIxVehhAjWBNJobMfeY0al0Uz0cwYOIIEsQBMFLhOpCKW0tFe0bPIxBY6CmowadSodCEm+rwhnit0EQBMFLhOnDqGqvEkGWhzFoDFS2V4p6LKEfEWQJgiB4iRBdCDIyOrWYkvIkBh+DI/gVKwuFs4ggSxAEwUuE6kMBRMbEwwRqAh1Blvi5CGcRQZYgCIKX0Cg1BPgEiOlCD+OcLhSZLOEsIsgSBEHwIqG6UNHCwcP07l8oMlnC2USQJQiC4EVC9CGihYOHMWgMAKJHltDPmIMsSZKUkiQdlCTpw9NfJ0qSlCNJUoEkSW9KkuQz9mEKgiAIAGG6MDFd6GECNYEAIvgV+hmPTNY9QF6fr38L/EGW5RSgCbhtHO4hCIIgAJcnXc7SqKVTPQyhD5HJEgYypiBLkqQY4HLg76e/loALgY2nT3kRuGYs9xAEQRDOWBG9gozgjKkehtCHXqVHJalEhlHoZ6yZrD8CDwH2018HA82yLNtOf10BRI/xHoIgCILgsSRJwqAxiCBL6GfUQZYkSVcAdbIs7+972M2p8gDPv0OSpH2SJO2rr68f7TAEQRAEYcoZNAb81GK6UHA1lkzWCuAqSZJKgTdwTBP+EQiUJEl1+pwYoMrdk2VZfl6W5UxZljNDQ0PHMAxBEARBmFqBmkDRWkPoZ9RBlizLP5FlOUaW5QTgRuBLWZa/DWwF1p8+7WZg85hHKQiCIAge7Dvp32Fe6LypHobgYSaiT9bDwP2SJBXiqNH6xwTcQxAEQRA8xkXxFxGiC5nqYQgeRjX0KUOTZfkr4KvT/18MLB6P6wqCIAiCIHgr0fFdEARBEARhAoggSxAEQRAEYQKIIEsQBEEQBGECiCBLEARBEIRpoaPbNvRJk0gEWYIgCIIgeL3mTgvrnt7OiZrWqR6KkwiyBEEQBEHwaj12mbvfOMQl6eHMigiY6uE4jUsLB0EQBEEQhIm2Lb+exBBfYo2O7vr/OV7DgfImShs6sNrsPLJu1hSP0JXIZAmCIAiC4PEOlDdx24t7eedApfPYU5/mY7fLLIoP4plvL0Sl9KywRmSyBEEQBEGYdHa7jEIhuRyTZZnWLkfxur9W5Xy8vq2bu149wFXzojla2QJAl6WHssYOHrx0JT4qzwquennmqARBEARBmLY+PlrNHS/vczkmyzL3v3WYZY9/wfLHv+D7r+7Hbpex9ti569UDfDMzlnvWpHDsdJCVW91KcpifxwZYIDJZgiAIgiBMss9za/k8r45yUydxwY76qn/sKKGgro0Dv7gYhSRx4/O7+evWQkwdFvy0Ku5dk4IkQafFRn1bN8erWpgTbZjiVzI4zw3/BEEQBEHwSGZrD898VYjZ2jPi58qyzI7CBi5KC+eNveUA7Cpq4Lmvi3luwyK0aiU+KgXPbljEKzllfHWyjj/cMB+FQkKSJGZHGzhW1cLRihZmiyBLEARBEITpQpZlfvHeMZ79qoj/ef/4iJ9fVN+Oj0rBI+tmsnF/BeWmTu554xB/vGE+MUF653nhAVpevX0JL9+2BINO7Tw+J9rAsYoWjlaKTJYgCIIgCNNAS6eVU42d/GNHCYcrmvnix6vYX9bEaznlI7rOjoIGVswIITnMnzijnmuf2cntKxNZmRLS79zkMH9nu4Zes6MN7CtrotTUQWq4/5he00QTNVmCIAiCIAyqzWxl9e+3ovdR4adR8bfvZBLmr+Vv31nElX/ewfpFMcMuQN9RaOKq+VEAfG/VDLaerOOO85OGPZbZ0QbueeMgsyIC0KqVo3o9k0UEWYIgCIIgDGrzoSqWJgXz7IZFLseTQv2IDNSRX9s2rPooW4+dnBITj183B4CL0sO5KD18RGOJN+rx9VF5/FQhiCBLEARBELza3tJGSuo7uD4r1u3jW0/WEaBVsyg+aMBryLLMM18VcaKmDR+lgofXzSTMX4u9sxOFXs8be8t58FL33dTnRBs4XuVahN7SaeWVnDK+v2oGCoVEYV0bf/mykDazjehAHSF+mlG/XoVCIiM6gNkxIsgSBEEQBGGCVDR18v1XDgAyoQEaLpgZ5vK4LMs8+mEuoX4a3rxz2YDXeSW7jE9zirgr1kbp9n0cfa+C+IZyehoasLz7GU0dVs5L7l8zBY7pu6OVLdyQdebYFydq+d1/TtJjl7l5eQLffWk/V82LIinUl5SwsddR/fraOYQHaMd8nYkmgixBEARB8EJmaw/fe2U/d56fxPy4QL7/yn42fX858cG+znP2lDQiAUX1HRTXt5MU6ud8rKmmnuqvd9O2Zw8hu7J5vLkKZJnefJj19H8/3pLDjVnJ/bqz95oTbeD9w1Uux3YWmvjhBcm8mlPGf47XcF5KCPddnDpur31Gn9fhyUSQJQiCIAheaNOBCkL9NNx+XiKSJHHzsgT+/GUhv//mPOc5b+w9xbcWx1Hf3s07Xx7lDkMrnXv30rl3L935+UhAwOk/7sgqFQUH8/j1TRcMOI70qADya9qw9thRKxXIsszOwgZe++4SLpgVyivZ5fz88vRxfe3eQgRZgiAIguCFdhQ0cOW8KCTJkWFaNTOUB98+4nzcVF5Fx3+2cFGUGfO+vcilJVQOdDEAhQJNaira2Rkc94tiiyWI/UojD181d9CpOT+NishALYV17aRFBlDc0IEkQWKIL0mSH4vijeP0ir2PCLIEQRAEwQMV17fzmy0nsPbYSQ7146eXpTmn7HrsMruLTfzPVRnO82fQQfzBbZz62WdY9u/DUlrKfUDXANe3KxT4zpmDfnEW+qwsdAsXovRzTMMZum3c99gXbMiK57I5kUOOdU60gWOVLaRFBrCzsIEVySHO4O9cJoIsQRAEQfAw7d027nx5P5fPjWReTCB/2VrIX7YWcveaFAByq1pJkdvRfPkJVXv30rl3H9bycu4D2ve4v6asUpEfFEfyxefx22o9v/nFt4mJCnZ7rq9GxUd3r3TpwD6Y3iDrm5mx7CxsYN3soQOzc4EIsgRBEATBg8iyzEMbD7MwLoh71qQgSRLpUQHc+vj7LD6xk7hTJ7Fu382vTLVUvz7wdSwKFX7z5xGwdDH6xYvRzZvH8eMNfHPzcZYsNg4YYPXqW0A/lNnRBt45UElOsYndRSYevXr2sJ87nYkgSxAEQRA8yHNfF1PZ1MXrN82g/Ysv6Ni1i46du3iyrAyAFkDn5nmSRkNLUhqFkSnMvPR8fl2s5N37XAvWv5kZS22rmSVJgwdYIzUn2kCwnw+///Qkl2ZEEOYF7RUmgwiyBEEQBMEDyDYb2R9vo+mVD/mdXEXZs8egp2fA8yWtFv3Chc6aKu2cORyp7eSVd45ysT6cJbPsbp/3wwtTxn3svhoVL9+2ZNyv6+1EkCUIgiAIQ3jvYCW+GhUXj3ALGHD0s/rx24epaTH3e0xr7iC17Bgziw+TUnaUwO5OrgXchVaSVos+M5OvdLHsC0zg6f/+FpJa7XLOrAglJQ3tfHkCHlmbNuKxCuNLBFmCIAiCMISPj1ZT22oecZAlyzI/fecoEvCTdbNAlpFOlaHK2Ylyzy4Ux48i2QfIVkkS2rQ0fFeswHfFcnQLFqDQaLipx84VZlu/AAtAq1aSGOJHfm07mQkDb6MjTA4RZAmCIAjnvDazlT0ljYCjuWakwbXqqbC+narmLo5XtZARNfw9817cVUp+ZRMvZaqxvPYc7Vu/wnrq1IDnq8LD8V25Ar8VK9AvW4YqqH+gpFIqMPr6DHiN2VEBBOnVaNXKYY9TmBgiyBIEQRDOadYeO7e/uA9rjx1fjYqShg4++OFKgk4HMtYeOxVNXdy+MpE39pzi0WuGDrJsDQ20fvU1/O0tfmcqovb5DvcnShLauXPwX70av9Wr0cyaNeb+UtcuiKat2zamawjjQwRZgiAIwjntNx+fQKtW8tp3l6JUSPzm4zzufuMg/751MUqFRJmpgyiDlg1L41n39HZ+ctks9D6ub5897R2Yjx6hc/8B2rdtw3zE0XndXSm4Qq/Hd+VK/Favxu/881CFuN94ebSWD7CRszD5RJAlCIIgnLM2H6rk87xaPvjhSpSnu6k/eOlMbv7XHv65o4Tvnp9EYV0HM0L9iArUkZVgZO0fviK+o567Iy3EVBfTdfgw3QUFYHe/mg9AHRuL36pV+F2wGn1WFgqfgaf7hOlDBFmCIAjCOel4VQv/+0Eur96+BIP+TBG5Sqnge6tm8PTnBXz3/CTKiytZUX+Cuqd38bODhzAfPQodjum/5oEurlRSFplM4IUXsODGK/FJTBTbzJyDRJAlCIIgTDvWHjvHKltYEOdaON5psfF5Xh09djtPfZbP/1yVQVpkgPNx2WLBfOIEqfsPcvG7n5K/6ZecV1EBgGmwG57eXFk3bx76xVmolixj/Z/2kH3/GjTa/qsAhXODCLIEQRCEaeexj/P4965S/nFzJhfOcrRdsNtl7n3jEI0dFqKDdNy2PIG1wXZaPvqIrsOHMR8+gjk3F9lqBeB83PerAlAGB7NHF8Wyy88nYlkm2tlzUPqd2YZmZ2EDMyP88RcB1jlNBFmCIAjCtPLuwQq+PFHHP2/O4oG3D7Px+8tJDPHlb1uOEJB3iF/FWrF+fZSuI0coMg2anwLAqlCiz8jAf+F8tHPnops3H3V0FH998xCqpGBuXBzX7zk7ChtYKQrQz3kiyBIEQRA8XlOHhbvfOMhT188n1F8z4Hmm9m7+94NcXv+vTBLb6/i1uoiPvvMaM5vKOL+5htXINA1xL3VcHLp58zDFpfB/RRLlQdFk/3Jdv/NWJIewLb/ebZCVXWzioUsgb9lBAAAgAElEQVRnjfRlCtOMCLIEQRAEj9Zjl7n7jYPsK21iR2E91y6IcXlclmWslVWYjx7hxOe7+f3hw0jvlFNiNhMPxA9ybYWfH7q5c9HOm4tu3jx0c+eiMhoBiLDL5P3qUzL61Gz1tSI5hMe3nMBul1EozhS1y7JMQW076QM8Tzh3iCBLEARBmFT5tW0EaNVEGLRuH88pNpEeFeCsZ3ry05P02GUeXjuT7GOVrFU20l1QQHd+Ad0F+ZhPnKSn0dGt3Xj6GrK7C/cpTtfNnYtu/jzHqj+Fwu04lAqJZUnBA2bOogN1GHRq8mpaXbrA17Sa0aqVLisWhXOTCLIEQRCESXX/W4ew2mTe+cFyfDWub0O7ihq4+Z97WDXDyJ9XGNm7dQ+KL/fxaGA31tcLWFJVSekw76OKjEQ3Zw7aObMdgVVGBgpf36Gf2Mcd5yc5+2e5Mz82kNwq1yCrqK6D5LCR3UeYnkSQJQiCIEyaoxUtNHdaWZIYzEObjvCXby0Am43uoiKq9x5k/9tb2YgJ6b0CSp+wEgpcDliGuK7C3x9mprG5O5Dvfe8qdHPmoA4LG/N4MxOMgz4eadBS3WJ2OVZY10ZymN+Y7y14v1EHWZIkxQIvARGAHXheluWnJUkyAm8CCUApcL0sy0PVGQqCIAgeauuJOv70ZQH/vnUxBt3YpsBe21POhvRArtc18Po/P+TAW4/jW5KP3N0NwEVDPN+uUNAdEU3YvAw0KSloUlLQpqSgjovj1T2nqClvImDN/DGNcSQiA3XkVrW4HCusb2dGqAiyhLFlsmzAj2VZPiBJkj+wX5Kkz4BbgC9kWX5ckqRHgEeAh8c+VEEQBGGylTZ08MDbh5kfG8iP3zrE89/JdCnyHoqjKL2Szn37aN27jws/20FMay21wIW95wzwXFVEBNpZsxzBVGoKmtRU/tPiw0cnTDz//zL7nb+zsIGL0sJH/BrHIsqg5fPcWpdjRXUdXJoRManjEDzTqIMsWZargerT/98mSVIeEA1cDaw+fdqLwFeIIEsQBMHrdHTbuPPl/dx7cSo3ZMZy0wvZ/PjtwySH+ZEW6e9s8lnZ3MWpxk6WJgUj9/TQXVBA5779dB3YT+e+/djq6pzXjBngXp1BoTTFzGD+miVoMzLQpqejCg7ud96yNjO/+Dgfi82Oj0pBj13mtZwyWs02dhY28MsrMybiWzGgSIOO6pYul2MikyX0GpeaLEmSEoAFQA4QfjoAQ5blakmS3E6KS5J0B3AHQFxc/x4jgiAIwtSRZZmHNh1hToyBDUvikCSJZzcs4qXdpbSZbTy08ShP36hkXpiO/3vsDYJL8gjQNaLMO4a9rW3wi6tUaNPT0S9YwGeKcMoik3m33Mxbdy4jZIjgJMxfy7IZwTz6YS6PXjOb3/3nJLuLTSyfEcw9F6UOuGJxokQFaqluPlOT1dJlpbPbRuQkj0PwTGMOsiRJ8gM2AffKstw63A0wZVl+HngeIDMzc6BssSAIgjAFXtheTLmpk7e/t8y5sXGov4Z7ssLoOniQSzt3UX7rU5Q0nuLuHpvzeXY315J8fckNiidgcRbLrrkQ3Zw5KHQ6AFY1drL691+RGR9E0jCzP7/75jyu+ctOfvzWYbKLTXzwo5UYfX3G/JpHw6BTY7PLtJmt+GvVFNW3kxTqJzaDFoAxBlmSJKlxBFivyrL8zunDtZIkRZ7OYkUCdQNfQRAEQZhoda1mbnw+m59fkcaFs8Ipaehg/bO7MHVYCNSr+fz+VYT4nekFtbOwgRe2l/DeXStQNTfSkp1N5549dB44iKWoCAAtkDrA/ZShIegXZaJftAjdwgU8eLALnUbNE+vn9gs+Yo161s6O4Kp5UcN+PQFaNX/7ziJu/fdentuwaMoCLABJkogMdKww9NeqKaxrFysLBaexrC6UgH8AebIsP9XnofeBm4HHT/9385hGKAiCIIyaxWbn+68eYG6MgQffPsJLty3mvjcPce/FqXxnaTwPvH2YTfsruHPVDABOVZn4x5Ov8nxAI93/788U5OcPeQ+fxER0CxfAnPn8v70W3vrf9RhPB23PbyuivLmJt+5cMGB25683LRzx60oJ92fHwxcOfeIkiDLoqGruIjXcn6L6dmaEih5ZgsNYMlkrgO8ARyVJOnT62E9xBFdvSZJ0G1AOfHNsQxQEQRBG6zdb8gjS+/DU9fN5dU85V/9lJ9cuiGbDEkct7LeyYvjjcx/zjdxPad+5i/YDB3nQ3gNAt7sLqlToMjLQLVqEfuECdAsXOrehAZgjHeLdQ1XctjLRJSOmVSsn4dVOjb69sorq2lm/aKDyfuFcM5bVhTuAgSad14z2uoIgCML4qG/rZuP+CrY/dAEKhcSGJXEE+/pwQVIgHTt20r71SwK+3MpPa2poOP2cfm8KajX6efPQL1uKPivLpZ7KnRuzYvnZe8e4NCOce944xJ++NZ/owIHPnw4iA3VUN3dht8scLG/mf6+ePdVDEjyE6PguCIIwjfTdrHjTgQrWZkQQqPfB3tVF+9dfM/eT/1C+fTv2jo4Br6FJScF3+XJ8ly9Dn5k5oq1oFicascsy1z+3mzvPT2L5jJAxvyZPF2XQsq+siRM1bQTo1NM+qBSGTwRZgiAI08gNz+/mkvQIbj8vkY27i/h9YjeVD7xC25dfInd2un2OFBDA/og0lt54BfEXr0IVGjrq+0uS9P/bu/Pwtqo74ePfo8W2ZFuy48R2HDt2nNjOBoQkBEhC2FMCDITylvWlZShLW2jpQtsZZsr78pbO074DnXZgoAOhENKSNMNSaEvZhkADgZCFBJw4i+1sjhMvcSzLiyxZOvPHlRc53i3Jivz7PI/iu5x7zrk6uvYv9xydy90XFLLjSCN3XjBtxPmcTian2Tj2eTUfldezZMapc3uJ8UuCLCGEiBOlR11U1bv56A/byf/tHn6x/WMSva009ZHWmpdH6iWXkHLJJdjnn81M6+gel9PTTYumctOi8TP/YY7TmCvro4p6blyYN9bVETFEgiwhhDjN6UCAtu3bqXhiDb8p3UxCs6vPdAmFhTiuuhLH8uUkzJghczmFyeQ0G9WuNmrd7fzqxug9N1HEPgmyhBDiNKQDAdp27MT91ls0vfkmHTU1fc5bZc3NxXHllTiuupLE4mIJrCIgJdGC1Wxi2sRk0uxjN2eXiD0SZAkhxBjSWuP1B0i0hE5x4A9ojjcZ0wJkpiZiNZvQXi8tW7bgfvdd3O++i7+uvq8ssWRm4lixAsdVV5J0xhkSWEVBjtM2Lgb5i+GRIEsIIcbQv7xRxs4qF+vvOb9rm9aab6/dzubKBtLamriipYIb/Udo27SJQD+D191JKZgvvoxZt3wZ24IFKJMpWqcggKVFE7libvZYV0PEGAmyhBBijLy24yhv7jpOuy/Avho3xVmp6ECA36/+K7Pfe58ftFTi3b0bgL4mXDBPmEDKpZfyDPmoBefw0Mozo3sCostPrp491lUQMUiCLCGEGANlx5p4+E+7+d3Xz+WdT/by4TPrSGmu5OSG91ngagTA28dx1rw8Ui6+CMfll2ObP5+nNh5g9946fvd3MgGmELFGgiwhhIiyRlcrj/7rOv49sQbb/c+wvLQUtMYFnNLJZ7FgX7CAsvwz+Dx3Dj+860shY6xe2X6Uf7thHlazdA8KEWskyBJCiAg7UNeMp7ICtm+FrZtp37KFB7zGoHZPH+nNGRmkLFtGyoUXkrxkMebUVA7vr2P7hvKQAOu4y0N9cztzchxROhMhxHBIkCWEEGGmOzrwlO2hddtWqj7YhGf7dhzt3aOqEnsfYDLRUTybfXmzWXHX9djmzj1l4Pr0SSlU1IWOzNpUUc/i6Rldj9ERQsQWCbKEEGIUtNb4jhzBU1pKW+kuPKWleEpLu74FmBB89WbNySF56VKSlywh+bxzMTudnDFAOZOdSbS2d+Bq8+G0GbOzf1heL9MGCBHDJMgSQsSd9/fWsnrTQQBWzJ3MDeeE51EnHQ0NeCsqaK+opL2yAm95OW27dhNw9T3Dek/mtDRsCxaQvPh8UpYswZqfP6z5q5RSFE5Koby2mQX56Wit+ai8nu9cUjSaUxJCRJAEWUKIuFJe6+YH63fy4JWzSE608JPXSslJs7G0aOA7PtrrpaOuDl9NLR21NXTU1OA73vnzON7KSvyNjUOuR7Mzg9aSM9iXVchX77mOhMLCUc9dNSMzhYo6I8iqqGvGYjKRn2EfVZ5CiMiRIEsIEXO01hxzechJs3Wt17nbyXQkhaTz+QOcbPF2bXd7fNy9Zhs/XjGT6xfkAuC0WXlgzSe8eE0BEz0uI3CqrcFXU0Nr1TGor8NfV4v/xAnQemT1TXXgL5pJmWMK+9Nzufcb13DTq5UcOtHKmq8vIrFgwijejW4zMlOoqG0G4KPyEyyZkSGzuQsRwyTIEkLEnBc/PcxP/ljK6jsWcUHRJJ54r5ynN1by6YOXYUswHj+jteafXy3l/c8PsX5lIRNaG3n21c3c7XVxgWsDh58+RsfxGiYcP86qpiZa18HhUdbLY07ANyWPKWfN5qgji1WHAwSmF9PomAhKkWZP4LGvnIXTbuXp2ybw9MYKFuSnj/4NCZo+KZmXtlUB8GbpcW47Pz9seQshwk+CLCFETNl26CS/fHsfP7vuDL63bgcPnJvJpr9u4XrtZvMjOymhBd/xY9RXHuGG2lpu97bSuh5agS8F8xh6p163AAqvI43aRAepuTkUzirAkpmFJTuLltQJ3PNeDTdetZDHN1Rw/2VF/Ns7+3jywQUsmtb3XaqpGXYeWTnQUPbhm5FpjMk6WN/Cvho3l87KDGv+QojwkiBLCDEqT7y3n+KsVJbP6f+5bT5/gIde28XtiwsoyU6l1dvBT/64i+9eVsQUuwlfVRXeqioayg/w4V+28Eyql7QtdTx/6Ajm37dxVo+8OgMo2zDqqKxWzFlZ7PHbcKemc9KWhnfCRG6/5hzanBnc+ZdDFJbk8fhtizjc0Mr1T23iyVuNAMrnD3D3M5u55MIzuW3xNIqyHdy6ajM/uWpWvwFWpEydkEy1y8MLHx/iy/OnnPJQaSFEbFF6hGMQwmnhwoV669atY10NIcQwvbK9isfe3kebz8/au86jJDu1z3T/949fsOvzcjIajvHQmSls3LCNhOrDZLlqSG8+ObpKWK1YsrJgUib2KTlYJ2djycoO+WlOT0eZTLhafeytcQMwd4oDe4Lx/8w6dzsOm6UraHl/by0/fvlzXrt3Kb/5oIJDJ1p49mvndM1HVd3YxmRn0piMh7rksfepOtnGX++/gOmTUqJevhAClFLbtNYLB0snd7KEECNSetTFI38pY+1d57Gr2sU9a7byz1fOwuJqwHKoAuuhSiwHK/FXlLPyWBU3dhhP4nO9CcN5jLHJbseal4c1L5fPO5L575Mm5p8zi+uvWIA1OwvzhAlD/tae027t8+7TpNTQ6UEvKsnktvPyuf6pTVjMitfvXRoy4WfngPyxMH1SChNTEiXAEuI0IEGWEGLYGlq8fOe5Tfz/OYlkbnwT5779TN68g4QXD2Bvax5WXgGTiabUDJonZFI8r4TkgnwS8nKx5uZizcvDnJbWdcfI6vJQ+vFBblleEvFZzr910QxavX6unTcFp90a0bKG47qzp3RNRiqEiG3SXSiEGJDWmo6aGjxlZbTv3Utb2R4OfbqTCY01qGH8/jA7nSQUFpIwbRoJ0wpInDbNWM/NRSX0NSe6EELEJukuFEIMi/b78VVX4z14CO+hQ3gPHqR9/37a9+zB32tG84wB8jHZ7SQWFxuvkmKSiotJmDEDS3r4pjIQQojTgQRZQowjAY8HX3U1vqNHjW/0HT7SFVD5jhxB+3xDz8xkIqGgoCuQSiwpIbG4GGtOzqhnNhdCiHggQZYQMWR/jZtMR9Kwx9xsO3SSs3MdBBoa8NXUsG3rPjpqj+NwnySr9aQRUB09ir++fkT1arUmkVhSwsSz5pI4s4SkmTNJLCrClJQ0+MFCCDFOSZAlRIw4UN/Cl5/axBlTnLxwxyLMCgLNzfib3ASaXPibmvA3NRFoasLvctFRW4uvppaaisO4q6opa3djCviB0O68pmHUwWVzkD27iISCfOMu1bRpPFoeYFJRAfddWhzW8xVCiHgnQZYQEaR9PvxuN36Xi4Dbjd/VhL/JZQRKTe6u5fZGFzt3H+E5SwfeRhe7nmwjob0VAoFBy7AHX0Oqj8lEvS0NnZ3D4QQnl11yNvbCAhIKCrBOncqKZ7bz05VzOa/QCNNcrT5e+fA9PritYMTvgRBCjFcSZAkxgLJjLv7llR08tmIaTn87pXur+MumfXxjfiaW1mbjzpK7KRg8NVFbXUdDzQns7a3Yva0kBeeGGoqS4M/kUdTXnWDHnjMZR14OlqxMrFnZfOG385u9rTzyjeUUzSnkuU+O8OT75bx+31Im95rv6aZFU1n36eGuIOvVz6q4qCSTCcny7T8hhBgumcJBjAva68XvcoW+GjuXG4NdcE343U0EggFTR1MT7SddWAMdY1dxu51mqw1PUjJZOZNQqSmQ6kClOlAZGSROziZ96hSsWVlYMjPxWhJIsp76qBWPzx+yvfd6p5MtXpb96wb+9sOLSbNbWfHrjTx09WwWz5gY0dMUQojTiUzhIE5b9c3tVDe2cWZuGmA8wqTJ42NmtoOAx8OBymo+23UYc4sbS4sbS7O7e7nFjbnZjaWl2Vju3OZpG1FdRj3lo8kEKanUBKy0JNiYNi0bx6QMzA4HdVh5aa8LT1Iy37p6HhMnT8LsdGB2ODA5HPypoomH/ryHKWk2XvnW4q5HwAykv2HovQOqvgIsgPTkBC6dmcnP3igjL92Ox+fvuqslhBBieCTIElEX8HoJuIIDuV3B7rbgsrexkT99uBevy4V1io1ETwuVlceweZop6/CAtx2AOVGsr7JaUQ4HzVYbE7InYnY68CYls9ut8STa8dqS8dqSycnN5IL50zE7Uo1AyenEZLejTCaaDzag2zuYXZLZle9k4Piu42Q6kijISzul3OsWptMeUCyZMXFIAVa43H9ZMc9+WEmt28NPV86N+MzqQggRr6S7UAyJ9vsJtLYSaG4m0NLS9fL3WA60nLq/O11zVzecbm+P/gmYzZidztBXmhOT04nZ0bnNgSk11Vh2ODClOoxtMk2BEEKIHqS7MAxWbzrIY2/vRWM8MPbXN87r93/1gYDme+t3MDPbwTcvmo7PH+CeNdu4fHYWNy+aSqu3gzue38Ltiwu4Yu7kIZWvAwE66uvB50P7fOiODnZW1rPu4wr+35UlKL/f2O7z8en+47y8+SDK30FhWiJfPWcKZn8HH++rYfO+GiwBP5ZAB5ZAgKKMRM7Lc6C9PnR7OwFvO9rT3r3c7jWWPR4aXS1Y2j0k+Yc+gDuS/CYzCelpmNPSegVMaZjTutdNTidmZ/c2U3KyTJAphBAiqiTI6seminoef6+cV761mIzkRO56YSuPv1fO/ZcV9Zn+iQ3lHDzRyieVJyjJTuFv++pp9Xbw6Ft7KcpMYfXHh0iwmHnw1VIKJ6VQnJU6aB38Lhflyy4M2ZYK3AUcWRuaNgf4do/1+reMn4XBV2+Ng5ZuSBliumExm/Ek2WlNsJOTm4nZ6aTJnMiGag/Lzy1i4uSJxh0lhxOVmop1QroRKDkcYLNjNkuwJIQQIvZJkNWHo41t3L9uB7+6cR4zMo1g6Mlb53PNEx/R5vPjsIW+bW5PB69sr+L1+5ZypKGVv39+CxnJCbx231K2Hmzgq7/9lMJJybz0jcX8+fNj3P3CVm44J2/QepjbWlkWkTMcAaXwJ9lo1Ba0zc6UnAzMKSmYkpODL3vIurLbWVt6go1HW7h8QSG3XDwLs8MY1K3sdjoCmluf2UxOWhLF2ams+fgQD39nDiVzssf6TIUQQoiwkDFZvXh8fm74z4+56ozJ3HPh9JB9u6ubeH1ndZ/H/d1Zk5mT4wRgw55a8jPsFE4y7gO98cUx5uWlkROck2j9liNU1rcMWheTz8vlP72HgNlCwGLBZLWS7rATMFsorW1lTn4G+054sNkSKc5NNwZoW61gsdDsV7h8MDXLibJYuvZ1vo40edlV14bfmkDAmoDfaiVgScBvNV7aauWqBQXkZgUHb9tsKJOJVz+rYlnRJDJSEof0Xr68vYqbzpmKuY9u1vrmdlZvOojPr5k1OZVr500ZNE8hhBBirA11TJYEWT1orfnRS5/T6vPzxM1no1Tsfqvqh/+1k22HT5LtSOKFOxZhkS40IYQQIipk4HsPrjYfZz389pDSzslxsP6e8/sPsLSGP38Ptj1nrC+4Ha7+FQw3IHPXwLOXQeNhsNjg5rUw/eIhH37b+fnsrGrk8ZvPHlqA9dY/wcmDcMMaY+6meBHww7pbYd9fjfWL/wku/NHQj284AGtWwrVPQsGS8NfvnYegvhxuXAOmvuemwu+DF2+AivcABZc/DEvuD39dhBCDi9fflWJMjIs7WcM9xwHvYG1ZBZ+ugjvfARQ8ezksvAMW3TX0Ajq88MI1MG0ZXPSPcOBv8PKdcOe7kJ7flczr6eAPP9uCwiiqs15KGf90VlN1JaDHtu79tDWg3NVgsqCSHKi0XOiRrjvPPsoIZg0KZepc7JGmZ1md6TqXg2+78fbr7vXO1R7t0rUYXOhO05WiO4vONBpoqER73JB9Bvg7oPoz9ITpYM8IpunR9rq7LloDOgC1ZWiLHdrdkDkTTFZCDulZVo+KhabpmaB7UXvc0HYClBVtSQJbOiE639/WelTAC44cCPhRjYcgNRsSU3q1sfH+9m7nHtl159vjI6x6t0tfx/VME7I99DPQM31fn4WuvBXDO06BovdxoeV3Hae6Dul7f8h6d770Std9XRGys/f1NiIDHDpgrgOUOarqDFzoEHPp43rtL2Xv/T2vj/6z7Sev0Gt4wEMH2HBqnfpYrS2Dqk/BagdnHuSdO7RyTslrGHXu5ZTW6Hlt9d6r+kvXOw/V977e2fWz86xL87A75NFaPY1pd6FS6grg14AZWKW1/vlA6SPeXehrgw9+Mfp8/D7YuQ6+/jZkBMdrnaiAZ5fDWTeBeYjzg9eWGT9vWtv9P6VNj8OOF6H4S13J2n1mVr0WgbsrQgghxBDdvHwrExytY12NoTvnTnDmRrSIMesuVEqZgf8ALgeqgC1Kqde11rvDXdYwagWJg0+ZMCS3/KE7wAJj+Zb1cOD9oeeRvwQWfC30VvT590GSE1rqurepfrqXhBBCiGhJSIbE0+jvUQz97YzEmKxFQLnWuhJAKbUOuBYYuyDLmgQX/CBy+ecuMF6joRTM/2rIJmtAc+tc45l7Id1WOng7+pTuL7rS9k7Xfazu6nLrTtNze7Csru09btfrHnlzaj1C0qFDu2nou4vq1DR03bMO6TbqPL5Xd1LX8X11IQU3qNADutP0utWueqbpq94hXXf9HN+rey+ky6lHvr3bq1O/7WYsDeu47u3dbRvS1dlH23d36fbzGeh9XM8b4ad8Lvs6LnR/ZyVDu4dP7aI9pdu2V/mnHDfk9/bU/b27g4drwGMH2DlgkZ07j2yGuj3G3fnCi2FSyRDqM0DOg+wasOtqsP7LAXq2evdfDprVgH1cA6XtvW+4de6/D27wOo+gz3ig9hjos9PrOgzNsv+uy6Hmb1u6FFKku3AkIhFkTQGO9FivAs7tnUgpdTdwN8DUqVMjUI3Tn8mkSMuyj3U1hBCxQk+D1+41ukIuXjHWtRFCDCISQVZfMfqp4wa1fhp4GowxWRGohxBCxBelYOWTY10LIcQQReL7qVVAz+nMc4G+Z/AUQgghhIhTkQiytgBFSqlpSqkE4Cbg9QiUI4QQQggRs8LeXai17lBK3Qe8hTGFw2+11rvCXY4QQgghRCyLyIzvWus3gDcikbcQQgghxOlAnhkghBBCCBEBEmQJIYQQQkSABFlCCCGEEBEgQZYQQgghRARIkCWEEEIIEQESZAkhhBBCRIAEWUIIIYQQEaAGfEJ7tCqhlBvY22OTE3BFuNiJQH2Ey4DonEs0yohWOdIusVmOtEvslQHRaZd4+hxH61w6RbJ94qldol3WaNql89h8rfWkQVNrrcf8BWzttf50tMuMYDnROJeIlyHtEptlSLuM3zKi1S5x9jmOyrlEo33iqV3G4JxG3C7DPTZWuwv/NNYVCKNonEu03i9pl9grI5rlREO8tIu0SWyWI+0Su+VEu6yoiJXuwq1a64XxXqYYnLRLbJJ2iU3SLrFN2ic2jaZdhntsrNzJenqclCkGJ+0Sm6RdYpO0S2yT9olNo2mXYR0bE3eyhBBCCCHiTazcyRJCCCGEiCsSZAkhhBBCREDcBFlKqTyl1AalVJlSapdS6v7g9glKqXeUUvuDP9OD22cqpT5WSrUrpR7oIz+zUuozpdSfo30u8SSc7aKUOqiU+kIptUMptXUszidehLld0pRSLyml9gTzO38szikehKtdlFIlweuk89WklPruWJ1XvAjzdfO9YB6lSqm1SqmksTineBDmdrk/2Ca7wnHNxM2YLKXUZGCy1nq7UioV2AasBG4HGrTWP1dK/QOQrrX+sVIqE8gPpjmptX60V37fBxYCDq311dE8l3gSznZRSh0EFmqtozEpZlwLc7usBjZqrVcppRIAu9a6MdrnFA/C/XssmKcZOAqcq7U+FK1ziUfhah+l1BTgQ2C21rpNKbUeeENr/Xz0z+r0F8Z2mQusAxYBXuBN4Jta6/0jrVvc3MnSWh/TWm8PLruBMmAKcC2wOphsNcabita6Vmu9BfD1zksplQtcBayKQtXjWjjbRYRPuNpFKeUAlgHPBtN5JcAauQhdL5cCFRJgjV6Y28cC2JRSFsAOVEe4+nErjO0yC/hEa92qte4APgCuG03d4ibI6kkpVQCcDWwGsrTWx8BoCCBzCFn8CvgREIhQFcelMLSLBt5WSoN68VUAAARESURBVG1TSt0dqXqON6Nsl0KgDnhOGd3rq5RSyRGs7rgRhuul003A2nDXb7wbTftorY8CjwKHgWOAS2v9diTrO16M8ropBZYppTKUUnbgSiBvNPWJuyBLKZUCvAx8V2vdNILjrwZqtdbbwl65cWy07RK0RGs9H1gB3KuUWha2Co5TYWgXCzAfeEprfTbQAvxDGKs4LoXpeiHYfXsN8F/hqpsIy9+ZdIy7LNOAHCBZKfW/w1vL8We07aK1LgN+AbyD0VW4E+gYTZ3iKshSSlkx3uDfa61fCW6uCfbXdvbb1g6SzRLgmuD4n3XAJUqp30WoyuNCmNoFrXV18Gct8CpGv7kYoTC1SxVQpbXeHFx/CSPoEiMUruslaAWwXWtdE/6ajk9hap/LgANa6zqttQ94BVgcqTqPB2H8O/Os1nq+1noZ0ACMeDwWxFGQpZRSGONCyrTWv+yx63Xga8HlrwGvDZSP1voftda5WusCjNvs72mt5X8YIxSudlFKJQcHNBLsjlqOcWtXjEAYr5fjwBGlVElw06XA7jBXd9wIV7v0cDPSVRg2YWyfw8B5Sil7MM9LMcYRiREI53UTHBSPUmoq8GVGef3E07cLlwIbgS/oHkv1IEa/7HpgKsYH+yta6walVDawFXAE0zdjfNOjqUeeFwEPyLcLRy5c7QJMxLh7BUYX1Yta659F6zziTTivF6XUPIwviSQAlcDfa61PRvN84kWY28UOHAEKtdau6J5JfApz+zwM3IjRHfUZcKfWuj2a5xMvwtwuG4EMjEHx39da//eo6hYvQZYQQgghRCyJm+5CIYQQQohYIkGWEEIIIUQESJAlhBBCCBEBEmQJIYQQQkSABFlCCCGEEBEgQZYQ4rSilPIrpXYopXYppXYqpb6vlBrwd5lSqkApdUu06iiEECBBlhDi9NOmtZ6ntZ4DXI7xfLH/M8gxBYAEWUKIqJJ5soQQpxWlVLPWOqXHeiGwBWPC2nxgDdD5kOr7tNablFKfALOAA8Bq4N+BnwMXAYnAf2it/zNqJyGEGBckyBJCnFZ6B1nBbSeBmYAbCGitPUqpImCt1nph76c3KKXuBjK11o8opRKBjzBmgz4Q1ZMRQsQ1y1hXQAghwkAFf1qBJ4KP+vEDxf2kXw6cqZT6X8F1J1CEcadLCCHCQoIsIcRpLdhd6AdqMcZm1QBnYYw59fR3GPBtrfVbUamkEGJckoHvQojTllJqEvAb4AltjH1wAse01gHgNsAcTOoGUnsc+hbwTaWUNZhPsVIqGSGECCO5kyWEON3YlFI7MLoGOzAGuv8yuO9J4GWl1FeADUBLcPvnQIdSaifwPPBrjG8cbldKKaAOWBmtExBCjA8y8F0IIYQQIgKku1AIIYQQIgIkyBJCCCGEiAAJsoQQQgghIkCCLCGEEEKICJAgSwghhBAiAiTIEkIIIYSIAAmyhBBCCCEi4H8AT3DvZRhJRtQAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "window = 48\n", - "fig, ax = plt.subplots(figsize=(10, 5))\n", - "ax = df_trends.plot(legend=False, lw=1, ax=ax);\n", - "df_trends.rolling(window, win_type='triang', center=True).mean().plot(ax=ax, lw=3);" - ] - }, - { - "cell_type": "code", - "execution_count": 106, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 5))\n", - "window = 12\n", - "\n", - "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']\n", - "\n", - "for column, color in zip(df_trends.columns, colors):\n", - " ax = df_trends[column].plot(ax=ax, lw=1, color=color, alpha=0.5);\n", - " avg = df_trends[column].rolling(window, center=True).mean()\n", - " std = df_trends[column].rolling(window, center=True).agg(pd.Series.std)\n", - " ax = avg.plot(ax=ax, lw=3, color=color, alpha=1);\n", - " ax = (avg + std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');\n", - " ax = (avg - std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (8.3) Resampling" - ] - }, - { - "cell_type": "code", - "execution_count": 107, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ax = df_trends.resample('d').pad().plot(figsize=(10, 5))\n", - "df_trends.resample('M').mean().plot(ax=ax);" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 108, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 5))\n", - "window = 12\n", - "\n", - "agg_func = lambda ser: ser.max() - ser.min()\n", - "\n", - "colors = plt.rcParams['axes.prop_cycle'].by_key()['color']\n", - "\n", - "for column, color in zip(df_trends.columns, colors):\n", - " ax = df_trends[column].plot(ax=ax, lw=1, color=color, alpha=0.5);\n", - " avg = df_trends[column].rolling(window, center=True).mean()\n", - " std = df_trends[column].rolling(window, center=True).agg(agg_func)\n", - " ax = avg.plot(ax=ax, lw=3, color=color, alpha=1);\n", - " ax = (avg + std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');\n", - " ax = (avg - std).plot(ax=ax, lw=2, color=color, alpha=0.75, ls='--');" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (9) Modeling and Machine Learning" - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "metadata": {}, - "outputs": [], - "source": [ - "pd.set_option('display.max_rows', 2**6)\n", - "pd.set_option('display.max_columns', 2**6)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (9.1) Dummy variables for categorical data" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loaded data of size (5043, 6) into memory.\n" - ] - } - ], - "source": [ - "cols_to_use = ['movie_title', 'duration', 'genres', 'content_rating', 'budget', 'gross']\n", - "df_model = pd.read_csv(r'data/movie_metadata.csv', sep=',', usecols=cols_to_use)\n", - "print(f'Loaded data of size {df_model.shape} into memory.')" - ] - }, - { - "cell_type": "code", - "execution_count": 111, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(3840, 6)" - ] - }, - "execution_count": 111, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Drop any row with missing information\n", - "df_model = df_model.dropna(how='any')\n", - "df_model.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 112, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " duration gross genres \\\n", - "0 178.0 760505847.0 Action|Adventure|Fantasy|Sci-Fi \n", - "1 169.0 309404152.0 Action|Adventure|Fantasy \n", - "\n", - " movie_title budget Approved G GP M \\\n", - "0 Avatar  237000000.0 0 0 0 0 \n", - "1 Pirates of the Caribbean: At World's End  300000000.0 0 0 0 0 \n", - "\n", - " NC-17 Not Rated PG PG-13 Passed R Unrated X \n", - "0 0 0 0 1 0 0 0 0 \n", - "1 0 0 0 1 0 0 0 0 " - ] - }, - "execution_count": 113, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_model = df_model.merge(dummies, how='left', left_index=True, right_index=True)\n", - "df_model = df_model.drop(columns='content_rating', errors='ignore')\n", - "df_model.head(2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "-----------------\n", - "\n", - "A more advanced example follows." - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "metadata": {}, - "outputs": [], - "source": [ - "from functools import reduce\n", - "\n", - "# Split the genres, take the union over every set to get every genre in the data set\n", - "genres_sets = df_model.genres.str.split('|').apply(set)\n", - "genres = reduce(set.union, genres_sets)" - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "metadata": {}, - "outputs": [], - "source": [ - "# For every genre, add a dummy column\n", - "for genre in genres:\n", - " df_model[genre] = np.where(df_model.genres.str.contains(genre), 1, 0)\n", - " \n", - "df_model = df_model.drop(columns='genres', errors='ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 116, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " duration gross movie_title \\\n", - "0 178.0 760505847.0 Avatar  \n", - "1 169.0 309404152.0 Pirates of the Caribbean: At World's End  \n", - "\n", - " budget Approved G GP M NC-17 Not Rated PG PG-13 Passed R \\\n", - "0 237000000.0 0 0 0 0 0 0 0 1 0 0 \n", - "1 300000000.0 0 0 0 0 0 0 0 1 0 0 \n", - "\n", - " Unrated X History Action Western Documentary Fantasy Romance \\\n", - "0 0 0 0 1 0 0 1 0 \n", - "1 0 0 0 1 0 0 1 0 \n", - "\n", - " Animation Sport Sci-Fi Crime Drama Comedy Mystery Thriller War \\\n", - "0 0 0 1 0 0 0 0 0 0 \n", - "1 0 0 0 0 0 0 0 0 0 \n", - "\n", - " Family Musical Music Adventure Biography Horror Film-Noir \n", - "0 0 0 0 1 0 0 0 \n", - "1 0 0 0 1 0 0 0 " - ] - }, - "execution_count": 116, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_model.head(2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (9.2) Training a model" - ] - }, - { - "cell_type": "code", - "execution_count": 117, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.linear_model import LinearRegression\n", - "from sklearn.model_selection import train_test_split" - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "metadata": {}, - "outputs": [], - "source": [ - "df_model['gross_log'] = df_model['gross'].apply(np.log1p)\n", - "df_model['budget_log'] = df_model['budget'].apply(np.log1p)" - ] - }, - { - "cell_type": "code", - "execution_count": 119, - "metadata": {}, - "outputs": [], - "source": [ - "linreg = LinearRegression()\n", - "X = df_model.drop(columns=['movie_title', 'gross', 'budget', 'gross_log']).values\n", - "y = df_model.gross_log.values\n", - "\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=123)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "linreg.fit(X_train, y_train)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "y_pred = linreg.predict(X_test)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.Series(y_test.mean() - y_test).abs().mean()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.Series(y_pred - y_test).abs().mean()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.Series(y_test.mean() - y_test).plot(figsize=(10, 5))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.Series(y_pred - y_test).plot(figsize=(10, 5))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (10) Misc tips and tricks" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## (10.1) Performance" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " ### Finding the n-largest" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "There might exists built in methods which are optimal for your use case. Finding the maximum is an $\\mathcal{O}(n)$ operation, while sorting is $\\mathcal{O}(n \\log n)$. Finding the top $k$ rows can be done in $\\mathcal{O}(k + n \\log k)$ time." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Create a series with a million entries\n", - "ser = pd.Series(np.random.randn(1000000))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "(ser.nlargest(50) == ser.sort_values(ascending=False).head(50)).all()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "ser.max()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "ser.nlargest(50)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "ser.sort_values(ascending=False).head(50)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Filter *before* computing\n", - "\n", - "It's generally better to apply filters *before* computations, especially if the computations are expensive." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "df.mean().imdb_score" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "df.imdb_score.mean()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "-----------------" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "df = df.sort_values('gross').dropna(how='any')\n", - "temp = df.set_index('director_name').sort_index()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "temp.loc[lambda df:df.index > 'o', :]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "df.loc[lambda df:df.director_name > 'o', :]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "temp.loc[slice('o', None), :]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "temp.index.dropna().is_monotonic" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Vectorize everything (if you can)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import math\n", - "\n", - "temp = df.gross.dropna()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "temp.map(math.log)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "temp.apply(np.log)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Another vectorization example" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import statistics\n", - "\n", - "vector = np.arange(1000000)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "np.mean(vector[1:] - vector[:-1])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "vector = list(vector)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "statistics.mean((i - j for (i, j) in zip(vector[1:], vector[:-1])))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "----------------" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "df_countries = df.country.sample(5_000_000, replace=True).to_frame().reset_index(drop=True)\n", - "df_countries.head(3)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "df_countries.assign(USA=lambda df:np.where(df.country == 'USA', 1, 0))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%%timeit\n", - "\n", - "def is_USA(string):\n", - " if string == 'USA':\n", - " return 1\n", - " return 0\n", - "\n", - "df_countries.assign(USA=lambda df:df.country.apply(is_USA))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# (11) Problems and answers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# References\n", - "\n", - "- [Official Pandas Documentation](https://pandas.pydata.org/pandas-docs/stable/index.html)\n", - "- Videos at [awesome-pandas](https://github.com/tommyod/awesome-pandas), especially" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/tutorial/pandas_vs_excel_vs_sas.png b/tutorial/pandas_vs_excel_vs_sas.png index 6e03196..6c3667c 100644 Binary files a/tutorial/pandas_vs_excel_vs_sas.png and b/tutorial/pandas_vs_excel_vs_sas.png differ