Filtered out pandas videos
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README.md
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README.md
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@ -36,6 +36,80 @@ A collection of resources for pandas (Python) and related subjects.
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| Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
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| [Introduction Into Pandas](https://www.youtube.com/watch?v=-NR-ynQg0YM) | Daniel Chen | Python Tutorial | 1:28 | 46000 | pandas | 2017 | :snake: |
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| [Introduction To Data Analytics With Pandas](https://www.youtube.com/watch?v=5XGycFIe8qE) | Quentin Caudron | Python Tutorial | 1:51 | 25000 | pandas | 2017 | :snake: |
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| [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
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| [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: |
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| [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: |
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| [A Visual Guide To Pandas](https://www.youtube.com/watch?v=9d5-Ti6onew) | Jason Wirth | Next Day Video | 0:26 | 49000 | pandas | 2015 | :snake: |
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| [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: |
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| [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: |
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| [Pandas from the Inside](https://www.youtube.com/watch?v=CowlcrtSyME) | Stephen Simmons | PyData | 1:20 | 9000 | pandas | 2016 | :snake: :snake: :snake: |
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| [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 |
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| [Pandas from the Inside](https://www.youtube.com/watch?v=YGk09nK_xnM) | Stephen Simmons | PyData | 1:17 | 3000 | pandas | 2017 | Novice |
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* (Brandon Rhodes - Pandas From The Ground Up - PyCon 2015) https://www.youtube.com/watch?v=5JnMutdy6Fw
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* (A Visual Guide To Pandas) https://www.youtube.com/watch?v=9d5-Ti6onew
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* (Stephen Simmons | Pandas from the Inside) https://www.youtube.com/watch?v=CowlcrtSyME
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* (Stephen Simmons - Pandas from the Inside / "Big Pandas") https://www.youtube.com/watch?v=YGk09nK_xnM
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* (Pandas for Data Analysis | SciPy 2017 Tutorial | Daniel Chen) https://www.youtube.com/watch?v=oGzU688xCUs
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* (Introduction To Data Analytics With Pandas) https://www.youtube.com/watch?v=5XGycFIe8qE
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* (Introduction Into Pandas: Python Tutorial) https://www.youtube.com/watch?v=-NR-ynQg0YM
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### Cheat-sheets
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* https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf
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* https://s3.amazonaws.com/quandl-static-content/Documents/Quandl+-+Pandas,+SciPy,+NumPy+Cheat+Sheet.pdf
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* http://www.webpages.uidaho.edu/~stevel/504/Pandas%20DataFrame%20Notes.pdf
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* https://assets.datacamp.com/blog_assets/PandasPythonForDataScience.pdf
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* https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Pandas_Cheat_Sheet_2.pdf
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### Tutorials
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* https://github.com/jorisvandenbossche/pandas-tutorial
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* https://github.com/guipsamora/pandas_exercises
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* https://github.com/brandon-rhodes/pycon-pandas-tutorial
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* https://github.com/jadianes/winerama-recommender-tutorial
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* https://github.com/jonathanrocher/pandas_tutorial
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* https://github.com/chendaniely/scipy-2017-tutorial-pandas
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* https://github.com/tdpetrou/Learn-Pandas
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* https://github.com/adeshpande3/Pandas-Tutorial
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* https://github.com/GaelVaroquaux/sklearn_pandas_tutorial
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* https://github.com/vi3k6i5/pandas_basics
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* https://github.com/california-civic-data-coalition/first-python-notebook
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### Books
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## Data analysis with Python resources
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### Videos
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* (Introduction to NumPy | SciPy 2015 Tutorial | Eric Jones) https://www.youtube.com/watch?v=1zmV8lZsHF4
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### Cheat-sheets
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* http://datasciencefree.com/numpy.pdf
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* https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
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### Tutorials
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### Books
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## Data analysis resources
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### Books
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### Papers
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###
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Every video is below.
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| Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
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| Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
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| ----- | ------- | -------- | -------- | ----- | -------- | ---- | ----- |
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| ----- | ------- | -------- | -------- | ----- | -------- | ---- | ----- |
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| [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: |
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| [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: |
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@ -98,56 +172,3 @@ A collection of resources for pandas (Python) and related subjects.
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [Python Profiling & Performance](https://www.youtube.com/watch?v=Dgnp28Ijm_M) | Mahmoud Hashemi | SF Python | 0:28 | 1000 | python | 2016 | Novice |
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| [Python Profiling & Performance](https://www.youtube.com/watch?v=Dgnp28Ijm_M) | Mahmoud Hashemi | SF Python | 0:28 | 1000 | python | 2016 | Novice |
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* (Brandon Rhodes - Pandas From The Ground Up - PyCon 2015) https://www.youtube.com/watch?v=5JnMutdy6Fw
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* (A Visual Guide To Pandas) https://www.youtube.com/watch?v=9d5-Ti6onew
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* (Stephen Simmons | Pandas from the Inside) https://www.youtube.com/watch?v=CowlcrtSyME
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* (Stephen Simmons - Pandas from the Inside / "Big Pandas") https://www.youtube.com/watch?v=YGk09nK_xnM
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* (Pandas for Data Analysis | SciPy 2017 Tutorial | Daniel Chen) https://www.youtube.com/watch?v=oGzU688xCUs
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* (Introduction To Data Analytics With Pandas) https://www.youtube.com/watch?v=5XGycFIe8qE
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* (Introduction Into Pandas: Python Tutorial) https://www.youtube.com/watch?v=-NR-ynQg0YM
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### Cheat-sheets
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* https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf
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* https://s3.amazonaws.com/quandl-static-content/Documents/Quandl+-+Pandas,+SciPy,+NumPy+Cheat+Sheet.pdf
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* http://www.webpages.uidaho.edu/~stevel/504/Pandas%20DataFrame%20Notes.pdf
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* https://assets.datacamp.com/blog_assets/PandasPythonForDataScience.pdf
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* https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Pandas_Cheat_Sheet_2.pdf
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### Tutorials
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* https://github.com/jorisvandenbossche/pandas-tutorial
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* https://github.com/guipsamora/pandas_exercises
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* https://github.com/brandon-rhodes/pycon-pandas-tutorial
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* https://github.com/jadianes/winerama-recommender-tutorial
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* https://github.com/jonathanrocher/pandas_tutorial
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* https://github.com/chendaniely/scipy-2017-tutorial-pandas
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* https://github.com/tdpetrou/Learn-Pandas
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* https://github.com/adeshpande3/Pandas-Tutorial
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* https://github.com/GaelVaroquaux/sklearn_pandas_tutorial
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* https://github.com/vi3k6i5/pandas_basics
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* https://github.com/california-civic-data-coalition/first-python-notebook
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### Books
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## Data analysis with Python resources
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### Videos
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* (Introduction to NumPy | SciPy 2015 Tutorial | Eric Jones) https://www.youtube.com/watch?v=1zmV8lZsHF4
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### Cheat-sheets
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* http://datasciencefree.com/numpy.pdf
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* https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
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### Tutorials
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### Books
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## Data analysis resources
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### Books
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### Papers
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