2017-12-31 02:03:32 +08:00
![Awesome pandas logo ](/img/awesome_pandas.png )
2017-12-30 04:24:30 +08:00
# awesome-pandas
2017-12-31 01:17:54 +08:00
A collection of resources for [pandas ](http://pandas.pydata.org/ )
2017-12-31 20:59:14 +08:00
([Python](https://www.python.org/)) and related subjects.
**Pull requests are very welcome.**
2017-12-31 01:17:54 +08:00
2017-12-31 02:13:00 +08:00
**Contents:** This is an unofficial collection of resources for learning pandas,
an open source Python library for data analysis. Here you will find videos,
cheat-sheets, tutorials and books / papers. The curated list is divided into
three parts:
2017-12-31 01:17:54 +08:00
2017-12-31 02:13:00 +08:00
1. **pandas resources** - A collection of videos, cheat-sheets, tutorials and
books *directly related* to pandas.
2. **Data analysis with Python resources** - Material related to *adjacent
Python libraries and software* such as
2017-12-31 01:17:54 +08:00
[NumPy ](http://www.numpy.org/ ),
[scipy ](https://www.scipy.org/ ),
[matplotlib ](https://matplotlib.org/ ),
2017-12-31 01:34:36 +08:00
[seaborn ](https://seaborn.pydata.org/ ),
2017-12-31 01:17:54 +08:00
[statsmodels ](http://www.statsmodels.org/stable/ ) and
[Jupyter ](http://jupyter.org/ ).
2017-12-31 02:13:00 +08:00
3. **Miscellaneous related resources** - Resources related to *general* data
2017-12-31 20:59:14 +08:00
analysis, Python programming, algorithms, computer science, machine learning,
statistics, etc.
2017-12-31 02:13:00 +08:00
2017-12-30 06:39:09 +08:00
--------------------------------------------------------------------------------
2017-12-31 01:34:36 +08:00
## (1) :panda_face: pandas resources
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (1.1) :tv: Videos
2017-12-30 06:39:09 +08:00
2017-12-30 22:03:27 +08:00
The videos below were collected in December of 2017.
2017-12-31 01:34:36 +08:00
They are all directly related to pandas, and the **Level** of a video is
quantified roughly as follows:
2017-12-30 15:47:56 +08:00
2017-12-31 00:59:48 +08:00
* :smiley: : **Beginner** - requires little knowledge to jump into, elementary topics.
* :sweat_smile: : **Intermediate** - some prior knowledge needed, more technical.
* :scream: : **Advanced** - very technical, or discusses advanced topics.
2017-12-31 16:11:04 +08:00
* :star: : **Recommended video** - high quality video and audio, great presentation.
2017-12-30 21:54:58 +08:00
2017-12-31 00:59:48 +08:00
| Title | Speaker | Uploader | Time | Views | Year | Level |
2017-12-31 01:00:15 +08:00
| ----- | ------- | -------- | ---- | ----- | ---- | ----- |
2017-12-31 20:59:14 +08:00
| :star: [Pandas From The Ground Up ](https://www.youtube.com/watch?v=5JnMutdy6Fw ) [[repo ](https://github.com/brandon-rhodes/pycon-pandas-tutorial )] | Brandon Rhodes | PyCon 2015 | 2:24 | 91000 | 2015 | :smiley: |
2017-12-31 00:59:48 +08:00
| [Introduction Into Pandas ](https://www.youtube.com/watch?v=-NR-ynQg0YM ) | Daniel Chen | Python Tutorial | 1:28 | 46000 | 2017 | :smiley: |
2017-12-31 15:32:15 +08:00
| [Introduction To Data Analytics With Pandas ](https://www.youtube.com/watch?v=5XGycFIe8qE ) [[repo ](https://github.com/QCaudron/pydata_pandas )] | Quentin Caudron | Python Tutorial | 1:51 | 25000 | 2017 | :smiley: |
2017-12-31 00:59:48 +08:00
| [Pandas for Data Analysis ](https://www.youtube.com/watch?v=oGzU688xCUs ) [[repo ](https://github.com/chendaniely/scipy-2017-tutorial-pandas )] | Daniel Chen | Enthought | 3:45 | 13000 | 2017 | :sweat_smile: |
2017-12-31 15:32:15 +08:00
| [Optimizing Pandas Code ](https://www.youtube.com/watch?v=HN5d490_KKk ) [[repo ](https://github.com/sversh/pycon2017-optimizing-pandas )] | Sofia Heisler | PyCon 2017 | 0:29 | 12000 | 2017 | :sweat_smile: |
2017-12-31 00:59:48 +08:00
| [A Visual Guide To Pandas ](https://www.youtube.com/watch?v=9d5-Ti6onew ) | Jason Wirth | Next Day Video | 0:26 | 49000 | 2015 | :smiley: |
| [Analyzing and Manipulating Data with Pandas ](https://www.youtube.com/watch?v=6ohWS7J1hVA ) [[repo ](https://github.com/jonathanrocher/pandas_tutorial )] | Jonathan Rocher | Enthought | 3:33 | 22000 | 2016 | :smiley: |
| [Time Series Analysis ](https://www.youtube.com/watch?v=zmfe2RaX-14 ) [[repo ](https://github.com/ikding/pycon_time_series )] | Aileen Nielsen | PyCon 2017 | 3:11 | 9000 | 2017 | :sweat_smile: |
2017-12-31 01:34:36 +08:00
| [Predicting sports winners with pandas ](https://www.youtube.com/watch?v=k7hSD_-gWMw ) | Robert Layton | PyCon Australia | 0:38 | 13000 | 2015 | :sweat_smile: |
2017-12-31 15:32:15 +08:00
| [Pandas from the Inside ](https://www.youtube.com/watch?v=YGk09nK_xnM ) [[repo ](https://github.com/stevesimmons/pydata-berlin2017-pandas-and-dask-from-the-inside )] [[2016 talk ](https://www.youtube.com/watch?v=CowlcrtSyME )] | Stephen Simmons | PyData | 1:17 | 3000 | 2017 | :scream: |
2017-12-31 20:59:14 +08:00
| Pandas [part 1 ](https://www.youtube.com/watch?v=Cz_u2If7KbI ) & [part 2 ](https://www.youtube.com/watch?v=gS7kVg-4ZaU ) [[repo ](https://github.com/jorisvandenbossche/pandas-tutorial )] | Joris Van den Bossche | EuroSciPy | 3:03 | 1000 | 2017 | :smiley: |
2017-12-31 23:48:50 +08:00
| [Pandas: .head() to .tail() ](https://www.youtube.com/watch?v=7vuO9QXDN50 ) [[repo ](https://github.com/TomAugspurger/pydata-chi-h2t )] | Tom Augspurger | PyData | 1:26 | 3000 | 2016 | :sweat_smile: |
2017-12-30 06:49:10 +08:00
2017-12-31 02:13:00 +08:00
*Know of a recent, good video? Send a pull request!* :+1:
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (1.2) :exclamation: Cheat-sheets
2017-12-30 06:39:09 +08:00
2017-12-31 01:48:53 +08:00
* [Data Wrangling with pandas ](https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf )
* [The pandas DataFrame Object ](http://www.webpages.uidaho.edu/~stevel/504/Pandas%20DataFrame%20Notes.pdf )
* [Python For Data Science - pandas Basics ](https://assets.datacamp.com/blog_assets/PandasPythonForDataScience.pdf )
* [Python For Data Science - pandas ](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Pandas_Cheat_Sheet_2.pdf )
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (1.3) :mortar_board: Tutorials
2017-12-31 16:19:53 +08:00
2017-12-31 16:27:56 +08:00
* :star: [10 Minutes to pandas ](http://pandas.pydata.org/pandas-docs/stable/10min.html )
* :star: [pandas_exercises ](https://github.com/guipsamora/pandas_exercises )
* :star: [pycon-pandas-tutorial ](https://github.com/brandon-rhodes/pycon-pandas-tutorial ) [Video: [Pandas From The Ground Up ](https://www.youtube.com/watch?v=5JnMutdy6Fw )]
* :star: [Learn-Pandas ](https://github.com/tdpetrou/Learn-Pandas )
* :star: [pandas-cookbook ](https://github.com/jvns/pandas-cookbook )
* :star: Modern pandas. Parts:
2017-12-31 16:19:53 +08:00
[1 ](http://tomaugspurger.github.io/modern-1-intro.html ),
[2 ](http://tomaugspurger.github.io/method-chaining.html ),
[3 ](http://tomaugspurger.github.io/modern-3-indexes.html ),
[4 ](http://tomaugspurger.github.io/modern-4-performance.html ),
[5 ](http://tomaugspurger.github.io/modern-5-tidy.html ),
[6 ](http://tomaugspurger.github.io/modern-6-visualization.html ) and
[7 ](http://tomaugspurger.github.io/modern-7-timeseries.html ).
2017-12-31 20:59:14 +08:00
* [pandas-tutorial ](https://github.com/jorisvandenbossche/pandas-tutorial ) [Video: [Pandas ](https://www.youtube.com/watch?v=Cz_u2If7KbI ) & [Advanced Pandas ](https://www.youtube.com/watch?v=gS7kVg-4ZaU )]
* [pandas_tutorial ](https://github.com/jonathanrocher/pandas_tutorial ) [Video: [Analyzing and Manipulating Data with Pandas ](https://www.youtube.com/watch?v=6ohWS7J1hVA )]
* [scipy-2017-tutorial-pandas ](https://github.com/chendaniely/scipy-2017-tutorial-pandas ) [Video: [Pandas for Data Analysis ](https://www.youtube.com/watch?v=oGzU688xCUs )]
* [Pandas-Tutorial ](https://github.com/adeshpande3/Pandas-Tutorial )
* [sklearn_pandas_tutorial ](https://github.com/GaelVaroquaux/sklearn_pandas_tutorial )
* [pandas_basics ](https://github.com/vi3k6i5/pandas_basics )
* [first-python-notebook ](https://github.com/california-civic-data-coalition/first-python-notebook )
* [Learn Pandas ](https://bitbucket.org/hrojas/learn-pandas )
2017-12-31 16:19:53 +08:00
2017-12-31 01:34:36 +08:00
### (1.4) :blue_book: Books / papers
2017-12-31 01:17:54 +08:00
2017-12-31 01:57:14 +08:00
* [[amazon ](https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1491957662/ )] McKinney, Wes. *Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython* . 2 edition. O’ Reilly Media, 2017.
* [[amazon ](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1491912057/ )] VanderPlas, Jake. *Python Data Science Handbook: Essential Tools for Working with Data* . 1 edition. O’ Reilly Media, 2016.
2017-12-31 01:48:53 +08:00
2017-12-31 01:17:54 +08:00
--------------------------------------------------------------------------------
2017-12-30 06:39:09 +08:00
2017-12-31 01:17:54 +08:00
## (2) Data analysis with Python resources
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (2.1) :tv: Videos
2017-12-31 01:06:59 +08:00
| Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
| ----- | ------- | -------- | -------- | ----- | -------- | ---- | ----- |
2017-12-31 21:23:06 +08:00
| [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 | :sweat_smile: |
| [Machine Learning ](https://www.youtube.com/watch?v=OB1reY6IX-o ) | Andreas Mueller & Sebastian Raschka | Enthought | 3:03 | 47000 | sklearn | 2016 | :sweat_smile: |
| [The Python Visualization Landscape ](https://www.youtube.com/watch?v=FytuB8nFHPQ ) | Jake VanderPlas | PyCon 2017 | 0:33 | 21000 | python | 2017 | :smiley: |
| [JupyterLab: Building Blocks for Interactive Computing ](https://www.youtube.com/watch?v=Ejh0ftSjk6g ) | Brian Granger | Enthought | 0:29 | 28000 | jupyter | 2016 | :smiley: |
| [Machine Learning with Scikit Learn ](https://www.youtube.com/watch?v=80fZrVMurPM ) [[repo ](https://github.com/amueller/scipy_2015_sklearn_tutorial )] | Andreas Mueller & Kyle Kastner | Enthought | 3:22 | 48000 | sklearn | 2015 | :sweat_smile: |
| [Machine Learning for Time Series Data in Python ](https://www.youtube.com/watch?v=ZgHGCfwExw0 ) | Brett Naul | Enthought | 0:24 | 24000 | cesium | 2016 | :smiley: |
| [Computational Statistics ](https://www.youtube.com/watch?v=He9MCbs1wgE ) [[repo ](https://github.com/AllenDowney/CompStats )] | Allen Downey | Enthought | 2:05 | 10000 | scipy | 2017 | :sweat_smile: |
| [Time Series Analysis ](https://www.youtube.com/watch?v=zmfe2RaX-14 ) [[repo ](https://github.com/ikding/pycon_time_series )] | Aileen Nielsen | PyCon 2017 | 3:11 | 9000 | pandas | 2017 | :sweat_smile: |
| [Learning TensorFlow ](https://www.youtube.com/watch?v=bvHgESVuS6Q ) | Robert Layton | PyCon Australia | 0:40 | 18000 | tensorflow | 2016 | :sweat_smile: |
| [JupyterHub: Deploying Jupyter Notebooks ](https://www.youtube.com/watch?v=gSVvxOchT8Y ) | Min Ragan Kelley & Thomas Kluyver | PyData | 1:36 | 17000 | jupyter | 2016 | :smiley: |
| [Applied Time Series Econometrics ](https://www.youtube.com/watch?v=tJ-O3hk1vRw ) | Jeffrey Yau | PyData | 1:39 | 17000 | statsmodels | 2016 | :sweat_smile: |
| [Machine Learning with scikit learn ](https://www.youtube.com/watch?v=2kT6QOVSgSg ) [[repo ](https://github.com/amueller/scipy-2017-sklearn )] | Andreas Mueller & Alexandre Gram | Enthought | 3:10 | 8000 | sklearn | 2017 | :sweat_smile: |
| [Introduction to Numerical Computing with NumPy ](https://www.youtube.com/watch?v=lKcwuPnSHIQ ) | Dillon Niederhut | Enthought | 2:27 | 8000 | NumPy | 2017 | :smiley: |
| [Dask - A Pythonic Distributed Data Science Framework ](https://www.youtube.com/watch?v=RA_2qdipVng ) | Matthew Rocklin | PyCon 2017 | 0:46 | 7000 | dask | 2017 | :sweat_smile: |
| [Introduction to Statistical Modeling with Python ](https://www.youtube.com/watch?v=TMmSESkhRtI ) [[repo ](https://github.com/fonnesbeck/intro_stat_modeling_2017 )] | Christopher Fonnesbeck | PyCon 2017 | 3:19 | 7000 | scipy | 2017 | :sweat_smile: |
| [Fully Convolutional Networks for Image Segmentation ](https://www.youtube.com/watch?v=-lXfsWP7DJ8 ) | Daniil Pakhomov | Enthought | 0:20 | 7000 | scipy | 2017 | :smiley: |
| [Exploratory data analysis in python ](https://www.youtube.com/watch?v=W5WE9Db2RLU ) [[repo ](https://github.com/cmawer/pycon-2017-eda-tutorial )] | Chloe Mawer & Jonathan Whitmore | PyCon 2017 | 2:54 | 7000 | scipy | 2017 | :smiley: |
| [Libraries for Deep Learning with Sequences ](https://www.youtube.com/watch?v=E92jDCmJNek ) | Alex Rubinsteyn | PyData | 0:44 | 23000 | scipy | 2015 | :sweat_smile: |
| [Numba - Tell Those C++ Bullies to Get Lost ](https://www.youtube.com/watch?v=1AwG0T4gaO0 ) [[repo ](https://github.com/gforsyth/numba_tutorial_scipy2017 )] | Gil Forsyth & Lorena Barba | Enthought | 2:25 | 5000 | numba | 2017 | :sweat_smile: |
| [Deploying Interactive Jupyter Dashboards ](https://www.youtube.com/watch?v=8Jktm-Imt-I ) | Philipp Rudiger | Enthought | 0:18 | 5000 | jupyter | 2017 | :sweat_smile: |
| [Data Science Using Functional Python ](https://www.youtube.com/watch?v=ThS4juptJjQ ) | Joel Grus | PyData | 0:44 | 18000 | python | 2015 | :sweat_smile: |
| [Anatomy of matplotlib ](https://www.youtube.com/watch?v=MKucn8NtVeI ) [[repo ](https://github.com/matplotlib/AnatomyOfMatplotlib )] | Benjamin Root & Joe Kington | Enthought | 3:18 | 18000 | matplotlib | 2015 | :sweat_smile: |
| [Anatomy of matplotlib ](https://www.youtube.com/watch?v=rARMKS8jE9g ) [[repo ](https://github.com/matplotlib/AnatomyOfMatplotlib )] | Benjamin Root | Enthought | 3:02 | 4000 | matplotlib | 2017 | :sweat_smile: |
| [Data Science is Software ](https://www.youtube.com/watch?v=EKUy0TSLg04 ) [[repo ](https://github.com/drivendata/data-science-is-software )] | Peter Bull & Isaac Slavitt | Enthought | 2:12 | 9000 | jupyter | 2016 | :smiley: |
| [Machine Learning with Scikit Learn ](https://www.youtube.com/watch?v=HC0J_SPm9co ) [[repo ](https://github.com/jakevdp/sklearn_pydata2015 )] | Jake VanderPlas | PyData | 1:34 | 16000 | sklearn | 2015 | :sweat_smile: |
| [Using Jupyter notebooks ](https://www.youtube.com/watch?v=aXR2d9k9-h4 ) [[repo ](https://github.com/ch41rmn/PyConAU2016_-_Interactive_Data_Displays_With_Jupyter_Notebooks )] | Ioanna Ioannou | PyCon Australia | 0:28 | 8000 | jupyter | 2016 | :sweat_smile: |
| [Parallel Python: Analyzing Large Datasets ](https://www.youtube.com/watch?v=5Md_sSsN51k ) [[repo ](https://github.com/pydata/parallel-tutorial )] | Matthew Rocklin | Enthought | 3:05 | 7000 | scipy | 2016 | :scream: |
| [Keynote: Project Jupyter ](https://www.youtube.com/watch?v=v5mrwq7yJc4 ) | Brian Granger | Enthought | 0:48 | 7000 | jupyter | 2016 | :sweat_smile: |
| [matplotlib beginner tutorial ](https://www.youtube.com/watch?v=p7Mj-4kASmI ) [[repo ](https://github.com/rougier/matplotlib-tutorial )] | Nicolas Rougier | Enthought | 2:59 | 6000 | matplotlib | 2016 | :sweat_smile: |
| [Awesome Big Data Algorithms ](https://www.youtube.com/watch?v=jKBwGlYb13w ) | Titus Brown | Next Day Video | 0:39 | 41000 | python | 2013 | :scream: |
| [All About Jupyter ](https://www.youtube.com/watch?v=GMKZD1Ohlzk ) | Brian Granger | PyData | 0:39 | 11000 | jupyter | 2015 | :sweat_smile: |
| [PyMC: Markov Chain Monte Carlo ](https://www.youtube.com/watch?v=XbxIo7ScVzc ) | Chris Fonnesbeck | Enthought | 0:20 | 9000 | pyMC | 2014 | :sweat_smile: |
| [Jupyter Advanced Topics Tutorial ](https://www.youtube.com/watch?v=38R7jiCspkw ) [[repo ](https://github.com/jupyter/scipy-advanced-tutorial )] | Jonathan Frederic & Matthias Bussonier | Enthought | 2:48 | 4000 | jupyter | 2015 | :scream: |
| [Using randomness to make code much faster ](https://www.youtube.com/watch?v=7i6kBz1kZ-A ) | Rachel Thomas | SF Python | 0:54 | 1000 | scipy | 2017 | :sweat_smile: |
| [Python Profiling & Performance ](https://www.youtube.com/watch?v=Dgnp28Ijm_M ) | Mahmoud Hashemi | SF Python | 0:28 | 1000 | python | 2016 | :sweat_smile: |
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (2.2) :exclamation: Cheat-sheets
2017-12-31 02:13:00 +08:00
* [Numpy Cheat Sheet ](http://datasciencefree.com/numpy.pdf )
* [Python For Data Science - Scikit-Learn ](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf )
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (2.3) :mortar_board: Tutorials
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (2.4) :blue_book: Books / papers
2017-12-31 01:17:54 +08:00
2017-12-31 01:48:53 +08:00
* [[amazon ](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1491962291/ )] Géron, Aurélien. *Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems* . 1 edition. O’ Reilly Media, 2017.
2017-12-31 01:17:54 +08:00
--------------------------------------------------------------------------------
2017-12-30 06:39:09 +08:00
2017-12-31 01:17:54 +08:00
## (3) Miscellaneous related resources
2017-12-30 06:39:09 +08:00
2017-12-31 01:34:36 +08:00
### (3.1) :tv: Videos
2017-12-30 21:57:31 +08:00
2017-12-31 01:34:36 +08:00
| Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
| ----- | ------- | -------- | -------- | ----- | -------- | ---- | ----- |
2017-12-31 21:23:06 +08:00
| :star: [So you want to be a Python expert? ](https://www.youtube.com/watch?v=cKPlPJyQrt4 ) | James Powell | PyData | 1:54 | 28000 | python | 2017 | :scream: |
| :star: [Transforming Code into Beautiful, Idiomatic Python ](https://www.youtube.com/watch?v=OSGv2VnC0go ) | Raymond Hettinger | Next Day Video | 0:48 | 340000 | python | 2013 | :smiley: |
| :star: [Builtin Superheroes ](https://www.youtube.com/watch?v=j6VSAsKAj98 ) | David Beazley | David Beazley | 0:44 | 12000 | python | 2016 | :sweat_smile: |
| [How to become a Data Scientist in 6 months ](https://www.youtube.com/watch?v=rIofV14c0tc ) | Tetiana Ivanova | PyData | 0:56 | 148000 | misc | 2016 | :smiley: |
| [Modern Dictionaries ](https://www.youtube.com/watch?v=p33CVV29OG8 ) | Raymond Hettinger | SF Python | 1:07 | 44000 | python | 2016 | :sweat_smile: |
| [Keynote on Concurrency ](https://www.youtube.com/watch?v=9zinZmE3Ogk ) | Raymond Hettinger | SF Python | 1:13 | 15000 | python | 2017 | :sweat_smile: |
| [The Fun of Reinvention ](https://www.youtube.com/watch?v=js_0wjzuMfc ) | David Beazley | David Beazley | 0:52 | 11000 | python | 2017 | :scream: |
| [Being a Core Developer in Python ](https://www.youtube.com/watch?v=voXVTjwnn-U ) | Raymond Hettinger | SF Python | 1:02 | 19000 | python | 2016 | :smiley: |
| [Visualizing Geographic Data ](https://www.youtube.com/watch?v=ZIEyHdvF474 ) | Christopher Roach | PyData | 0:31 | 14000 | python | 2016 | :smiley: |
| [Python's Class Development Toolkit ](https://www.youtube.com/watch?v=HTLu2DFOdTg ) | Raymond Hettinger | Next Day Video | 0:45 | 80000 | python | 2013 | :sweat_smile: |
| [The Other Async (Threads + Async = ❤️) - YouTube ](https://www.youtube.com/watch?v=x1ndXuw7S0s ) | David Beazley | David Beazley | 0:47 | 5000 | python | 2017 | :scream:|
2017-12-31 01:34:36 +08:00
| [Functional Programming with Python ](https://www.youtube.com/watch?v=Ta1bAMOMFOI ) | Mike Müller | Next Day Video | 0:27 | 44000 | python | 2013 | Novice |
| [Building a Recommendation Engine using Python ](https://www.youtube.com/watch?v=E9XTOnEgqRY ) | Anusua Trivedi | PyData | 0:37 | 11000 | python | 2015 | Novice |
| [Iterations of Evolution ](https://www.youtube.com/watch?v=2AXuhgid7E4 ) | David Beazley | David Beazley | 0:34 | 2000 | python | 2017 | Novice |
| ["Good Enough" IS Good Enough! ](https://www.youtube.com/watch?v=_Ek3A2b-nHU ) | Alex Martelli | SF Python | 0:53 | 4000 | python | 2016 | Novice |
### (3.2) :exclamation: Cheat-sheets
2017-12-31 16:40:15 +08:00
* [Python 3 Cheat Sheet ](https://perso.limsi.fr/pointal/_media/python:cours:mementopython3-english.pdf )
* [Python Cheat Sheet ](http://datasciencefree.com/python.pdf )
2017-12-31 01:34:36 +08:00
### (3.3) :mortar_board: Tutorials
### (3.4) :blue_book: Books / papers
2017-12-30 21:57:31 +08:00
2017-12-31 23:48:50 +08:00
* [[amazon ](https://www.amazon.com/Effective-Python-Specific-Software-Development/dp/0134034287/ )] Slatkin, Brett. *Effective Python: 59 Specific Ways to Write Better Python* . 1 edition. Addison-Wesley Professional, 2015.
* [[amazon ](https://www.amazon.com/Fluent-Python-Concise-Effective-Programming/dp/1491946008/ )] Ramalho, Luciano. *Fluent Python* . 1st edition. O’ Reilly, 2015.
* [[pdf ](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4161295/pdf/pcbi.1003833.pdf )] P Rougier, Nicolas, Michael Droettboom, and Philip Bourne. "*Ten Simple Rules for Better Figures.*" PLoS Computational Biology 10 (September 1, 2014): e1003833. https://doi.org/10.1371/journal.pcbi.1003833.
* [[pdf ](http://vita.had.co.nz/papers/tidy-data.pdf )] *Tidy Data* | Wickham | Journal of Statistical Software. Accessed December 31, 2017. https://doi.org/10.18637/jss.v059.i10.
The books below are perhaps of an even more general nature.
2017-12-31 01:57:14 +08:00
* [[amazon ](https://www.amazon.com/Algorithms-Sanjoy-Dasgupta/dp/0073523402/ )] Dasgupta, Sanjoy, Christos H. . Papadimitriou, and Umesh Virkumar. Vazirani. *Algorithms* . Boston, Mass: McGraw Hill, 2008.
* [[amazon ](https://www.amazon.com/Numerical-Linear-Algebra-Lloyd-Trefethen/dp/0898713617/ )] Lloyd N. Trefethen. *Numerical Linear Algebra* . Society for Industrial and Applied Mathematics, 1997.
* [[amazon ](https://www.amazon.com/Computations-Hopkins-Studies-Mathematical-Sciences/dp/1421407949/ )] Gene H. Golub. *Matrix Computations* . 4th ed. Johns Hopkins Studies in the Mathematical Sciences. Baltimore: Johns Hopkins University Press, 2013.
2017-12-30 21:57:31 +08:00
--------------------------------------------------------------------------------
Every video is below.
| Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
| ----- | ------- | -------- | -------- | ----- | -------- | ---- | ----- |
| [How to become a Data Scientist in 6 months ](https://www.youtube.com/watch?v=rIofV14c0tc ) | Tetiana Ivanova | PyData | 0:56 | 148000 | misc | 2016 | :snake: |
| [Introduction Into Pandas ](https://www.youtube.com/watch?v=-NR-ynQg0YM ) | Daniel Chen | Python Tutorial | 1:28 | 46000 | pandas | 2017 | :snake: |
| [So you want to be a Python expert? ](https://www.youtube.com/watch?v=cKPlPJyQrt4 ) | James Powell | PyData | 1:54 | 28000 | python | 2017 | :snake::snake::snake: |
| [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: |
| [Introduction To Data Analytics With Pandas ](https://www.youtube.com/watch?v=5XGycFIe8qE ) | Quentin Caudron | Python Tutorial | 1:51 | 25000 | pandas | 2017 | :snake: |
| [Transforming Code into Beautiful, Idiomatic Python ](https://www.youtube.com/watch?v=OSGv2VnC0go ) | Raymond Hettinger | Next Day Video | 0:48 | 340000 | python | 2013 | :snake: |
| [Machine Learning ](https://www.youtube.com/watch?v=OB1reY6IX-o ) | Andreas Mueller & Sebastian Raschka | Enthought | 3:03 | 47000 | sklearn | 2016 | :snake: :snake: |
| [Pandas From The Ground Up ](https://www.youtube.com/watch?v=5JnMutdy6Fw ) [[repo ](https://github.com/brandon-rhodes/pycon-pandas-tutorial )] | Brandon Rhodes | PyCon 2015 | 2:24 | 91000 | pandas | 2015 | :snake: :snake: |
| [Modern Dictionaries ](https://www.youtube.com/watch?v=p33CVV29OG8 ) | Raymond Hettinger | SF Python | 1:07 | 44000 | python | 2016 | :snake: :snake: |
| [The Python Visualization Landscape ](https://www.youtube.com/watch?v=FytuB8nFHPQ ) | Jake VanderPlas | PyCon 2017 | 0:33 | 21000 | python | 2017 | :snake: |
| [Keynote on Concurrency ](https://www.youtube.com/watch?v=9zinZmE3Ogk ) | Raymond Hettinger | SF Python | 1:13 | 15000 | python | 2017 | :snake::snake: |
| [Pandas for Data Analysis ](https://www.youtube.com/watch?v=oGzU688xCUs ) [[repo ](https://github.com/chendaniely/scipy-2017-tutorial-pandas )] | Daniel Chen | Enthought | 3:45 | 13000 | pandas | 2017 | :snake::snake: |
| [JupyterLab: Building Blocks for Interactive Computing ](https://www.youtube.com/watch?v=Ejh0ftSjk6g ) | Brian Granger | Enthought | 0:29 | 28000 | jupyter | 2016 | :snake: |
| [Optimizing Pandas Code for Speed and Efficiency ](https://www.youtube.com/watch?v=HN5d490_KKk ) | Sofia Heisler | PyCon 2017 | 0:29 | 12000 | pandas | 2017 | :snake: :snake: |
| [A Visual Guide To Pandas ](https://www.youtube.com/watch?v=9d5-Ti6onew ) | Jason Wirth | Next Day Video | 0:26 | 49000 | pandas | 2015 | :snake: |
| [Machine Learning with Scikit Learn ](https://www.youtube.com/watch?v=80fZrVMurPM ) [[repo ](https://github.com/amueller/scipy_2015_sklearn_tutorial )] | Andreas Mueller & Kyle Kastner | Enthought | 3:22 | 48000 | sklearn | 2015 | :snake: :snake: |
| [Machine Learning for Time Series Data in Python ](https://www.youtube.com/watch?v=ZgHGCfwExw0 ) | Brett Naul | Enthought | 0:24 | 24000 | cesium | 2016 | :snake: |
| [The Fun of Reinvention ](https://www.youtube.com/watch?v=js_0wjzuMfc ) | David Beazley | David Beazley | 0:52 | 11000 | python | 2017 | :snake::snake::snake: |
| [Analyzing and Manipulating Data with Pandas ](https://www.youtube.com/watch?v=6ohWS7J1hVA ) [[repo ](https://github.com/jonathanrocher/pandas_tutorial )] | Jonathan Rocher | Enthought | 3:33 | 22000 | pandas | 2016 | :snake: |
| [Computational Statistics ](https://www.youtube.com/watch?v=He9MCbs1wgE ) [[repo ](https://github.com/AllenDowney/CompStats )] | Allen Downey | Enthought | 2:05 | 10000 | scipy | 2017 | :snake: :snake: |
| [Being a Core Developer in Python ](https://www.youtube.com/watch?v=voXVTjwnn-U ) | Raymond Hettinger | SF Python | 1:02 | 19000 | python | 2016 | :snake: |
| [Time Series Analysis ](https://www.youtube.com/watch?v=zmfe2RaX-14 ) [[repo ](https://github.com/ikding/pycon_time_series )] | Aileen Nielsen | PyCon 2017 | 3:11 | 9000 | pandas | 2017 | :snake: :snake: |
| [Learning TensorFlow ](https://www.youtube.com/watch?v=bvHgESVuS6Q ) | Robert Layton | PyCon Australia | 0:40 | 18000 | tensorflow | 2016 | :snake: :snake: |
| [JupyterHub: Deploying Jupyter Notebooks ](https://www.youtube.com/watch?v=gSVvxOchT8Y ) | Min Ragan Kelley & Thomas Kluyver | PyData | 1:36 | 17000 | jupyter | 2016 | :snake: |
| [Applied Time Series Econometrics ](https://www.youtube.com/watch?v=tJ-O3hk1vRw ) | Jeffrey Yau | PyData | 1:39 | 17000 | statsmodels | 2016 | :snake: :snake: |
| [Machine Learning with scikit learn ](https://www.youtube.com/watch?v=2kT6QOVSgSg ) [[repo ](https://github.com/amueller/scipy-2017-sklearn )] | Andreas Mueller & Alexandre Gram | Enthought | 3:10 | 8000 | sklearn | 2017 | :snake: :snake: |
| [Introduction to Numerical Computing with NumPy ](https://www.youtube.com/watch?v=lKcwuPnSHIQ ) | Dillon Niederhut | Enthought | 2:27 | 8000 | NumPy | 2017 | :snake: |
| [Dask - A Pythonic Distributed Data Science Framework ](https://www.youtube.com/watch?v=RA_2qdipVng ) | Matthew Rocklin | PyCon 2017 | 0:46 | 7000 | dask | 2017 | :snake: :snake: |
| [Introduction to Statistical Modeling with Python ](https://www.youtube.com/watch?v=TMmSESkhRtI ) [[repo ](https://github.com/fonnesbeck/intro_stat_modeling_2017 )] | Christopher Fonnesbeck | PyCon 2017 | 3:19 | 7000 | scipy | 2017 | :snake: :snake: |
| [Fully Convolutional Networks for Image Segmentation ](https://www.youtube.com/watch?v=-lXfsWP7DJ8 ) | Daniil Pakhomov | Enthought | 0:20 | 7000 | scipy | 2017 | :snake: |
| [Exploratory data analysis in python ](https://www.youtube.com/watch?v=W5WE9Db2RLU ) [[repo ](https://github.com/cmawer/pycon-2017-eda-tutorial )] | Chloe Mawer & Jonathan Whitmore | PyCon 2017 | 2:54 | 7000 | scipy | 2017 | :snake: |
| [Visualizing Geographic Data ](https://www.youtube.com/watch?v=ZIEyHdvF474 ) | Christopher Roach | PyData | 0:31 | 14000 | python | 2016 | :snake: |
| [Builtin Superheroes ](https://www.youtube.com/watch?v=j6VSAsKAj98 ) | David Beazley | David Beazley | 0:44 | 12000 | python | 2016 | :snake: :snake: |
| [Python's Class Development Toolkit ](https://www.youtube.com/watch?v=HTLu2DFOdTg ) | Raymond Hettinger | Next Day Video | 0:45 | 80000 | python | 2013 | :snake: :snake: |
| [Libraries for Deep Learning with Sequences ](https://www.youtube.com/watch?v=E92jDCmJNek ) | Alex Rubinsteyn | PyData | 0:44 | 23000 | scipy | 2015 | :snake: :snake: |
| [The Other Async (Threads + Async = ❤️) - YouTube ](https://www.youtube.com/watch?v=x1ndXuw7S0s ) | David Beazley | David Beazley | 0:47 | 5000 | python | 2017 | :snake: :snake: :snake:|
| [Numba - Tell Those C++ Bullies to Get Lost ](https://www.youtube.com/watch?v=1AwG0T4gaO0 ) [[repo ](https://github.com/gforsyth/numba_tutorial_scipy2017 )] | Gil Forsyth & Lorena Barba | Enthought | 2:25 | 5000 | numba | 2017 | :snake: :snake: |
| [Deploying Interactive Jupyter Dashboards ](https://www.youtube.com/watch?v=8Jktm-Imt-I ) | Philipp Rudiger | Enthought | 0:18 | 5000 | jupyter | 2017 | :snake: :snake: |
| [Data Science Using Functional Python ](https://www.youtube.com/watch?v=ThS4juptJjQ ) | Joel Grus | PyData | 0:44 | 18000 | python | 2015 | :snake: :snake: |
| [Pandas from the Inside ](https://www.youtube.com/watch?v=CowlcrtSyME ) | Stephen Simmons | PyData | 1:20 | 9000 | pandas | 2016 | :snake: :snake: :snake: |
| [Anatomy of matplotlib ](https://www.youtube.com/watch?v=MKucn8NtVeI ) [[repo ](https://github.com/matplotlib/AnatomyOfMatplotlib )] | Benjamin Root & Joe Kington | Enthought | 3:18 | 18000 | matplotlib | 2015 | :snake: :snake: |
| [Anatomy of matplotlib ](https://www.youtube.com/watch?v=rARMKS8jE9g ) [[repo ](https://github.com/matplotlib/AnatomyOfMatplotlib )] | Benjamin Root | Enthought | 3:02 | 4000 | matplotlib | 2017 | :snake: :snake: |
| [Data Science is Software ](https://www.youtube.com/watch?v=EKUy0TSLg04 ) [[repo ](https://github.com/drivendata/data-science-is-software )] | Peter Bull & Isaac Slavitt | Enthought | 2:12 | 9000 | jupyter | 2016 | :snake: |
| [Machine Learning with Scikit Learn ](https://www.youtube.com/watch?v=HC0J_SPm9co ) [[repo ](https://github.com/jakevdp/sklearn_pydata2015 )] | Jake VanderPlas | PyData | 1:34 | 16000 | sklearn | 2015 | Novice |
| [Using Jupyter notebooks ](https://www.youtube.com/watch?v=aXR2d9k9-h4 ) | Ioanna Ioannou | PyCon Australia | 0:28 | 8000 | jupyter | 2016 | Novice |
| [Parallel Python: Analyzing Large Datasets ](https://www.youtube.com/watch?v=5Md_sSsN51k ) [[repo ](https://github.com/pydata/parallel-tutorial )] | Matthew Rocklin | Enthought | 3:05 | 7000 | scipy | 2016 | Novice |
| [Functional Programming with Python ](https://www.youtube.com/watch?v=Ta1bAMOMFOI ) | Mike Müller | Next Day Video | 0:27 | 44000 | python | 2013 | Novice |
| [Predicting sports winners with pandas and scikit-learn ](https://www.youtube.com/watch?v=k7hSD_-gWMw ) | Robert Layton | PyCon Australia | 0:38 | 13000 | pandas | 2015 | Novice |
| [Keynote: Project Jupyter ](https://www.youtube.com/watch?v=v5mrwq7yJc4 ) | Brian Granger | Enthought | 0:48 | 7000 | jupyter | 2016 | Novice |
| [matplotlib beginner tutorial ](https://www.youtube.com/watch?v=p7Mj-4kASmI ) [[repo ](https://github.com/rougier/matplotlib-tutorial )] | Nicolas Rougier | Enthought | 2:59 | 6000 | matplotlib | 2016 | Novice |
| [Awesome Big Data Algorithms ](https://www.youtube.com/watch?v=jKBwGlYb13w ) | Titus Brown | Next Day Video | 0:39 | 41000 | python | 2013 | Novice |
| [Pandas from the Inside ](https://www.youtube.com/watch?v=YGk09nK_xnM ) | Stephen Simmons | PyData | 1:17 | 3000 | pandas | 2017 | Novice |
| [All About Jupyter ](https://www.youtube.com/watch?v=GMKZD1Ohlzk ) | Brian Granger | PyData | 0:39 | 11000 | jupyter | 2015 | Novice |
| [Building a Recommendation Engine using Python ](https://www.youtube.com/watch?v=E9XTOnEgqRY ) | Anusua Trivedi | PyData | 0:37 | 11000 | python | 2015 | Novice |
| [Iterations of Evolution ](https://www.youtube.com/watch?v=2AXuhgid7E4 ) | David Beazley | David Beazley | 0:34 | 2000 | python | 2017 | Novice |
| ["Good Enough" IS Good Enough! ](https://www.youtube.com/watch?v=_Ek3A2b-nHU ) | Alex Martelli | SF Python | 0:53 | 4000 | python | 2016 | Novice |
| [PyMC: Markov Chain Monte Carlo ](https://www.youtube.com/watch?v=XbxIo7ScVzc ) | Chris Fonnesbeck | Enthought | 0:20 | 9000 | pyMC | 2014 | Novice |
| [Jupyter Advanced Topics Tutorial ](https://www.youtube.com/watch?v=38R7jiCspkw ) [[repo ](https://github.com/jupyter/scipy-advanced-tutorial )] | Jonathan Frederic & Matthias Bussonier | Enthought | 2:48 | 4000 | jupyter | 2015 | Novice |
| [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 |