Update the info about Guide to NumPy

content/en/learn.md

@@ -7,30 +7,43 @@ For the **official NumPy documentation** visit [numpy.org/doc/stable](https://nu
 
 ***
 
-Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.
+Below is a curated collection of educational resources, both for self-learning and 
+teaching others, developed by NumPy contributors and vetted by the community.
 
 ## Beginners
 
-There's a ton of information about NumPy out there. If you are just starting, we'd strongly recommend the following:
+There's a ton of information about NumPy out there. If you are just starting, we'd 
+strongly recommend the following:
 
 <i class="fas fa-chalkboard"></i> **Tutorials**
 
 * [NumPy Quickstart Tutorial](https://numpy.org/devdocs/user/quickstart.html)
-* [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).
-* [NumPy Illustrated: The Visual Guide to NumPy *by Lev Maximov*](https://betterprogramming.pub/3b1d4976de1d?sk=57b908a77aa44075a49293fa1631dd9b)
-* [Scientific Python Lectures](https://lectures.scientific-python.org/) Besides covering NumPy, these lectures offer a broader introduction to the scientific Python ecosystem.
+* [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).
+* [NumPy Illustrated: The Visual Guide to NumPy](https://betterprogramming.pub/3b1d4976de1d?sk=57b908a77aa44075a49293fa1631dd9b)
+  *by Lev Maximov*
+* [Scientific Python Lectures](https://lectures.scientific-python.org/) Besides covering
+  NumPy, these lectures offer a broader introduction to the scientific Python ecosystem.
 * [NumPy: the absolute basics for beginners](https://numpy.org/devdocs/user/absolute_beginners.html)
-* [NumPy tutorial *by Nicolas Rougier*](https://github.com/rougier/numpy-tutorial)
-* [Stanford CS231 *by Justin Johnson*](http://cs231n.github.io/python-numpy-tutorial/)
+* [NumPy tutorial](https://github.com/rougier/numpy-tutorial) *by Nicolas Rougier*
+* [Stanford CS231](http://cs231n.github.io/python-numpy-tutorial/) *by Justin Johnson*
 * [NumPy User Guide](https://numpy.org/devdocs)
 
 <i class="fas fa-book"></i> **Books**
 
-* [Guide to NumPy *by Travis E. Oliphant*](https://web.mit.edu/dvp/Public/numpybook.pdf) This is a free version 1 from 2006. For the latest copy (2015) see [here](https://dl.acm.org/doi/10.5555/2886196).
-* [From Python to NumPy *by Nicolas P. Rougier*](https://www.labri.fr/perso/nrougier/from-python-to-numpy/)
-* [Elegant SciPy](https://www.amazon.com/Elegant-SciPy-Art-Scientific-Python/dp/1491922877) *by Juan Nunez-Iglesias, Stéfan van der Walt, and Harriet Dashnow*
+* [Guide to NumPy](https://web.mit.edu/dvp/Public/numpybook.pdf) *by Travis E. Oliphant*
+  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).
+* [From Python to NumPy](https://www.labri.fr/perso/nrougier/from-python-to-numpy/)
+  *by Nicolas P. Rougier* *(free)*
+* [Elegant SciPy](https://www.amazon.com/Elegant-SciPy-Art-Scientific-Python/dp/1491922877)
+  *by Juan Nunez-Iglesias, Stéfan van der Walt, and Harriet Dashnow*
 
-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.
+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.
 
 <i class="far fa-file-video"></i> **Videos**
 
@@ -44,20 +57,30 @@ Try these advanced resources for a better understanding of NumPy concepts like a
 
 <i class="fas fa-chalkboard"></i> **Tutorials**
 
-* [100 NumPy Exercises](http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html) *by Nicolas P. Rougier*
-* [An Introduction to NumPy and Scipy](https://engineering.ucsb.edu/~shell/che210d/numpy.pdf) *by M. Scott Shell*
-* [Numpy Medkits](http://mentat.za.net/numpy/numpy_advanced_slides/) *by Stéfan van der Walt*
-* [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).
+* [100 NumPy Exercises](http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html)
+  *by Nicolas P. Rougier*
+* [An Introduction to NumPy and Scipy](https://engineering.ucsb.edu/~shell/che210d/numpy.pdf)
+  *by M. Scott Shell*
+* [Numpy Medkits](http://mentat.za.net/numpy/numpy_advanced_slides/)
+  *by Stéfan van der Walt*
+* [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).
 
 <i class="fas fa-book"></i> **Books**
 
-* [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1098121228) *by Jake Vanderplas*
-* [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-Jupyter/dp/109810403X) *by Wes McKinney*
-* [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*
+* [Python Data Science Handbook](https://www.amazon.com/Python-Data-Science-Handbook-Essential/dp/1098121228)
+  *by Jake Vanderplas*
+* [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-Jupyter/dp/109810403X)
+  *by Wes McKinney*
+* [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*
 
 <i class="far fa-file-video"></i> **Videos**
 
-* [Advanced NumPy - broadcasting rules, strides, and advanced indexing](https://www.youtube.com/watch?v=cYugp9IN1-Q) *by Juan Nunez-Iglesias*
+* [Advanced NumPy - broadcasting rules, strides, and advanced indexing](https://www.youtube.com/watch?v=cYugp9IN1-Q)
+  *by Juan Nunez-Iglesias*
 
 ***