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@@ -7,30 +7,42 @@ For the **official NumPy documentation** visit [numpy.org/doc/stable](https://nu
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Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.
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Below is a curated collection of educational resources, both for self-learning and
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teaching others, developed by NumPy contributors and vetted by the community.
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## Beginners
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There's a ton of information about NumPy out there. If you are just starting, we'd strongly recommend the following:
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There's a ton of information about NumPy out there. If you are just starting, we'd
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strongly recommend the following:
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<i class="fas fa-chalkboard"></i> **Tutorials**
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* [NumPy Quickstart Tutorial](https://numpy.org/devdocs/user/quickstart.html)
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* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and educational materials in the format of Jupyter Notebooks developed and maintained by the NumPy Documentation team. To submit your own content, visit the [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials).
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* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and
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educational materials in the format of Jupyter Notebooks developed and maintained by
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the NumPy Documentation team. To submit your own content, visit the
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[numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials).
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* [NumPy Illustrated: The Visual Guide to NumPy *by Lev Maximov*](https://betterprogramming.pub/3b1d4976de1d?sk=57b908a77aa44075a49293fa1631dd9b)
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* [Scientific Python Lectures](https://lectures.scientific-python.org/) Besides covering NumPy, these lectures offer a broader introduction to the scientific Python ecosystem.
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* [Scientific Python Lectures](https://lectures.scientific-python.org/) Besides covering
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NumPy, these lectures offer a broader introduction to the scientific Python ecosystem.
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* [NumPy: the absolute basics for beginners](https://numpy.org/devdocs/user/absolute_beginners.html)
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* [NumPy tutorial *by Nicolas Rougier*](https://github.com/rougier/numpy-tutorial)
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* [Stanford CS231 *by Justin Johnson*](http://cs231n.github.io/python-numpy-tutorial/)
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* [NumPy User Guide](https://numpy.org/devdocs)
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<i class="fas fa-book"></i> **Books**
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* [Guide to NumPy *by Travis E. Oliphant*](https://web.mit.edu/dvp/Public/numpybook.pdf) This is the first and *free* edition of the book. To purchase the latest edition, [click here](https://www.amazon.com/exec/obidos/ASIN/151730007X/acmorg-20).
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* [From Python to NumPy *by Nicolas P. Rougier*](https://www.labri.fr/perso/nrougier/from-python-to-numpy/) *(free)*
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* [Elegant SciPy](https://www.amazon.com/Elegant-SciPy-Art-Scientific-Python/dp/1491922877) *by Juan Nunez-Iglesias, Stefan van der Walt, and Harriet Dashnow*
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* [Guide to NumPy *by Travis E. Oliphant*](https://web.mit.edu/dvp/Public/numpybook.pdf)
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This is the first and *free* edition of the book. To purchase the latest edition,
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[click here](https://www.amazon.com/exec/obidos/ASIN/151730007X/acmorg-20).
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* [From Python to NumPy](https://www.labri.fr/perso/nrougier/from-python-to-numpy/)
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*by Nicolas P. Rougier* *(free)*
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* [Elegant SciPy](https://www.amazon.com/Elegant-SciPy-Art-Scientific-Python/dp/1491922877)
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*by Juan Nunez-Iglesias, Stefan van der Walt, and Harriet Dashnow*
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You may also want to check out the [Goodreads list](https://www.goodreads.com/shelf/show/python-scipy) on the subject of "Python+SciPy." Most books there are about the "SciPy ecosystem," which has NumPy at its core.
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You may also want to check out the [Goodreads list](https://www.goodreads.com/shelf/show/python-scipy)
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on the subject of "Python+SciPy." Most books there are about the "SciPy ecosystem,"
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which has NumPy at its core.
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<i class="far fa-file-video"></i> **Videos**
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<i class="fas fa-chalkboard"></i> **Tutorials**
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* [100 NumPy Exercises](http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html) *by Nicolas P. Rougier*
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* [An Introduction to NumPy and Scipy](https://engineering.ucsb.edu/~shell/che210d/numpy.pdf) *by M. Scott Shell*
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* [Numpy Medkits](http://mentat.za.net/numpy/numpy_advanced_slides/) *by Stéfan van der Walt*
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* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and educational materials in the format of Jupyter Notebooks developed and maintained by the NumPy Documentation team. To submit your own content, visit the [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials).
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* [100 NumPy Exercises](http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html)
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*by Nicolas P. Rougier*
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* [An Introduction to NumPy and Scipy](https://engineering.ucsb.edu/~shell/che210d/numpy.pdf)
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*by M. Scott Shell*
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* [Numpy Medkits](http://mentat.za.net/numpy/numpy_advanced_slides/)
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*by Stéfan van der Walt*
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* [NumPy Tutorials](https://numpy.org/numpy-tutorials) A collection of tutorials and educational
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materials in the format of Jupyter Notebooks developed and maintained by the NumPy Documentation team.
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To submit your own content, visit the [numpy-tutorials repository on GitHub](https://github.com/numpy/numpy-tutorials).
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<i class="fas fa-book"></i> **Books**
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* [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1098121228) *by Jake Vanderplas*
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* [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-Jupyter/dp/109810403X) *by Wes McKinney*
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* [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1098121228)
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*by Jake Vanderplas*
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* [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-Jupyter/dp/109810403X)
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*by Wes McKinney*
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* [Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy, and Matplotlib](https://www.amazon.com/Numerical-Python-Scientific-Applications-Matplotlib/dp/1484242459) *by Robert Johansson*
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<i class="far fa-file-video"></i> **Videos**
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* [Advanced NumPy - broadcasting rules, strides, and advanced indexing](https://www.youtube.com/watch?v=cYugp9IN1-Q) *by Juan Nunez-Iglesias*
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* [Advanced NumPy - broadcasting rules, strides, and advanced indexing](https://www.youtube.com/watch?v=cYugp9IN1-Q)
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*by Juan Nunez-Iglesias*
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***
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