python
/
awesome-pandas
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
awesome-pandas/README.md

262 lines
30 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters!

This file contains ambiguous Unicode characters that may be confused with others in your current locale. If your use case is intentional and legitimate, you can safely ignore this warning. Use the Escape button to highlight these characters.

![Awesome pandas logo](/img/awesome_pandas.png)
# awesome-pandas
A collection of resources for [pandas](http://pandas.pydata.org/)
([Python](https://www.python.org/)) and related subjects.
**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:
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
[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.
> Pull requests are very welcome.
--------------------------------------------------------------------------------
## (1) :panda_face: pandas resources
### (1.1) :tv: Videos
The videos below were collected in December of 2017.
They are all directly related to pandas, and the **Level** of a video is
quantified roughly as follows:
* :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.
* :star: : **Recommended video** - high quality video and audio, great presentation.
| Title | Speaker | Uploader | Time | Views | Year | Level |
| ----- | ------- | -------- | ---- | ----- | ---- | ----- |
| [Introduction Into Pandas](https://www.youtube.com/watch?v=-NR-ynQg0YM) | Daniel Chen | Python Tutorial | 1:28 | 46000 | 2017 | :smiley: |
| [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: |
| :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: |
| [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: |
| [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: |
| [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: |
| [Predicting sports winners with pandas](https://www.youtube.com/watch?v=k7hSD_-gWMw) | Robert Layton | PyCon Australia | 0:38 | 13000 | 2015 | :sweat_smile: |
| [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: |
| [Pandas](https://www.youtube.com/watch?v=Cz_u2If7KbI) [[repo](https://github.com/jorisvandenbossche/pandas-tutorial)] | Joris Van den Bossche | EuroSciPy | 1:31 | 0 | 2017 | :smiley: |
| [Advanced Pandas](https://www.youtube.com/watch?v=gS7kVg-4ZaU) [[repo](https://github.com/jorisvandenbossche/pandas-tutorial)] | Joris Van den Bossche | EuroSciPy | 1:32 | 0 | 2017 | :smiley: |
*Know of a recent, good video? Send a pull request!* :+1:
### (1.2) :exclamation: Cheat-sheets
* [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)
### (1.3) :mortar_board: Tutorials
* [10 Minutes to pandas](http://pandas.pydata.org/pandas-docs/stable/10min.html)
* [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_exercises](https://github.com/guipsamora/pandas_exercises)
* [pycon-pandas-tutorial](https://github.com/brandon-rhodes/pycon-pandas-tutorial) [Video: [Pandas From The Ground Up](https://www.youtube.com/watch?v=5JnMutdy6Fw)]
* [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)]
* [Learn-Pandas](https://github.com/tdpetrou/Learn-Pandas)
* [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)
* [pandas-cookbook](https://github.com/jvns/pandas-cookbook)
* [Learn Pandas](https://bitbucket.org/hrojas/learn-pandas)
* Modern pandas, parts:
[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).
http://tomaugspurger.github.io/modern-1-intro">Modern Pandas</a></li>
http://tomaugspurger.github.io/method-chaining">Method Chaining</a></li>
http://tomaugspurger.github.io/modern-3-indexes">Indexes</a></li>
http://tomaugspurger.github.io/modern-4-performance">Fast Pandas</a></li>
http://tomaugspurger.github.io/modern-5-tidy">Tidy Data</a></li>
http://tomaugspurger.github.io/modern-6-visualization">Visualization</a></li>
http://tomaugspurger.github.io/modern-7-timeseries">Time Series</a></li>
### (1.4) :blue_book: Books / papers
* [[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.
--------------------------------------------------------------------------------
## (2) Data analysis with Python resources
### (2.1) :tv: 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: |
| [Machine Learning](https://www.youtube.com/watch?v=OB1reY6IX-o) | Andreas Mueller & Sebastian Raschka | Enthought | 3:03 | 47000 | sklearn | 2016 | :snake: :snake: |
| [The Python Visualization Landscape](https://www.youtube.com/watch?v=FytuB8nFHPQ) | Jake VanderPlas | PyCon 2017 | 0:33 | 21000 | python | 2017 | :snake: |
| [JupyterLab: Building Blocks for Interactive Computing](https://www.youtube.com/watch?v=Ejh0ftSjk6g) | Brian Granger | Enthought | 0:29 | 28000 | jupyter | 2016 | :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: |
| [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: |
| [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: |
| [Libraries for Deep Learning with Sequences](https://www.youtube.com/watch?v=E92jDCmJNek) | Alex Rubinsteyn | PyData | 0:44 | 23000 | scipy | 2015 | :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: |
| [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 |
| [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 |
| [All About Jupyter](https://www.youtube.com/watch?v=GMKZD1Ohlzk) | Brian Granger | PyData | 0:39 | 11000 | jupyter | 2015 | 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 |
### (2.2) :exclamation: Cheat-sheets
* [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)
### (2.3) :mortar_board: Tutorials
### (2.4) :blue_book: Books / papers
* [[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.
* [[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.
--------------------------------------------------------------------------------
## (3) Miscellaneous related resources
### (3.1) :tv: Videos
| 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: |
| [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: |
| [Transforming Code into Beautiful, Idiomatic Python](https://www.youtube.com/watch?v=OSGv2VnC0go) | Raymond Hettinger | Next Day Video | 0:48 | 340000 | python | 2013 | :snake: |
| [Modern Dictionaries](https://www.youtube.com/watch?v=p33CVV29OG8) | Raymond Hettinger | SF Python | 1:07 | 44000 | python | 2016 | :snake: :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: |
| [The Fun of Reinvention](https://www.youtube.com/watch?v=js_0wjzuMfc) | David Beazley | David Beazley | 0:52 | 11000 | python | 2017 | :snake::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: |
| [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: |
| [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:|
| [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
### (3.3) :mortar_board: Tutorials
### (3.4) :blue_book: Books / papers
* [[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.
--------------------------------------------------------------------------------
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 |
Reference in New Issue View Git Blame Copy Permalink