From 58c1e94a4205f95303d77577ae15e95331a623b4 Mon Sep 17 00:00:00 2001 From: tommyod Date: Sat, 30 Dec 2017 18:17:54 +0100 Subject: [PATCH] Updated description --- README.md | 66 ++++++++++++++++++++++++++----------------------------- 1 file changed, 31 insertions(+), 35 deletions(-) diff --git a/README.md b/README.md index aab43c2..93868d9 100644 --- a/README.md +++ b/README.md @@ -1,34 +1,26 @@ # awesome-pandas -A collection of resources for pandas (Python) and related subjects. +A collection of resources for [pandas](http://pandas.pydata.org/) +([Python](https://www.python.org/)) and related subjects. -**Table of contents** +**Contents:** This page is divided into three parts. -* pandas resources - - * Videos - * Cheat-sheets - * Tutorials - * Books - -* Data analysis with Python resources - - * Videos - * Cheat-sheets - * Tutorials - * Books - -* Miscellaneous related resources - - * Videos - * Cheat-sheets - * Tutorials - * Books +* (1) **pandas resources** - A collection of videos, cheat-sheets, tutorials and books related directly to pandas. +* (2) **Data analysis with Python resources** - Material related to adjacent + Python libraries such as + [NumPy](http://www.numpy.org/), + [scipy](https://www.scipy.org/), + [matplotlib](https://matplotlib.org/), + [seaborn](https://seaborn.pydata.org/) + [statsmodels](http://www.statsmodels.org/stable/) and + [Jupyter](http://jupyter.org/). +* (3) **Miscellaneous related resources** - Resources related to general data + analysis, algorithms, computer science, machine learning, statistics, etc. -------------------------------------------------------------------------------- -## pandas resources +## (1) pandas resources -### Videos +### (1.1) Videos The videos below were collected in December of 2017. They are all related to pandas, and the **Level** of a video is quantified roughly as follows: @@ -60,7 +52,7 @@ They are all related to pandas, and the **Level** of a video is quantified rough * (Introduction To Data Analytics With Pandas) https://www.youtube.com/watch?v=5XGycFIe8qE * (Introduction Into Pandas: Python Tutorial) https://www.youtube.com/watch?v=-NR-ynQg0YM -### Cheat-sheets +### (1.2) Cheat-sheets * https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf * https://s3.amazonaws.com/quandl-static-content/Documents/Quandl+-+Pandas,+SciPy,+NumPy+Cheat+Sheet.pdf @@ -68,7 +60,7 @@ They are all related to pandas, and the **Level** of a video is quantified rough * https://assets.datacamp.com/blog_assets/PandasPythonForDataScience.pdf * https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Pandas_Cheat_Sheet_2.pdf -### Tutorials +### (1.3) Tutorials * https://github.com/jorisvandenbossche/pandas-tutorial * https://github.com/guipsamora/pandas_exercises * https://github.com/brandon-rhodes/pycon-pandas-tutorial @@ -81,11 +73,13 @@ They are all related to pandas, and the **Level** of a video is quantified rough * https://github.com/vi3k6i5/pandas_basics * https://github.com/california-civic-data-coalition/first-python-notebook -### Books +### (1.4) Books -## Data analysis with Python resources +-------------------------------------------------------------------------------- -### Videos +## (2) Data analysis with Python resources + +### (2.1) Videos | Title | Speaker | Uploader | Time | Views | Keyword | Year | Level | | ----- | ------- | -------- | -------- | ----- | -------- | ---- | ----- | | [NumPy Beginner](https://www.youtube.com/watch?v=gtejJ3RCddE) [[repo](https://github.com/enthought/Numpy-Tutorial-SciPyConf-2016)] | Alexandre Chabot LeClerc | Enthought | 2:47 | 56000 | NumPy | 2016 | :snake: :snake: | @@ -124,19 +118,21 @@ They are all related to pandas, and the **Level** of a video is quantified rough | [Using randomness to make code much faster](https://www.youtube.com/watch?v=7i6kBz1kZ-A) | Rachel Thomas | SF Python | 0:54 | 1000 | scipy | 2017 | Novice | | [Python Profiling & Performance](https://www.youtube.com/watch?v=Dgnp28Ijm_M) | Mahmoud Hashemi | SF Python | 0:28 | 1000 | python | 2016 | Novice | -### Cheat-sheets +### (2.2) Cheat-sheets * http://datasciencefree.com/numpy.pdf * https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf -### Tutorials +### (2.3) Tutorials -### Books +### (2.4) Books -## Data analysis resources +-------------------------------------------------------------------------------- -### Books +## (3) Miscellaneous related resources -### Papers +### (3.1) Books + +### (3.2) Papers ###