Previously, I summarized Information gathering on machine learning and statistics. Today, as a continuation or supplement, I've put together a free-to-read Python E-book to help you analyze your data.
It's a good idea to poke the PDF here into your tablet or PC for reference whenever you need it. You can do a Google search every time, but it's safer to have the basic knowledge you want to make sure you understand in a book.
First is Python 3 itself.
Free Python Books http://www.onlineprogrammingbooks.com/python/
From the above, you can browse various Python books for free. Some of them are a little older Python 2 books, so it's a good idea to be aware of which version of Python you're targeting.
By the way, my recommendation is
Dive Into Python 3 http://www.onlineprogrammingbooks.com/free-book-dive-into-python-3/
You can read the Japanese version of the above on the web page. http://diveintopython3-ja.rdy.jp/index.html
An Introduction to Python http://www.onlineprogrammingbooks.com/read-online-or-download-pdf-an-introduction-to-python/
Become a Code Breaker with Python http://www.onlineprogrammingbooks.com/become-a-code-breaker-with-python/
Programming Computer Vision with Python http://www.onlineprogrammingbooks.com/download-free-pdf-programming-computer-vision-with-python/
It is around.
Programming in Python 3, 2nd Edition http://www.ebooks-it.net/ebook/programming-in-python-3-2nd-edition
This is not free, but I think it's okay if you keep this book for programming in Python 3 series.
You may want to refer to the official SciPy and NumPy documentation.
SciPy Reference Guide http://docs.scipy.org/doc/scipy/scipy-ref-0.14.0.pdf
NumPy User Guide http://docs.scipy.org/doc/numpy-1.8.0/numpy-user-1.8.0.pdf
This is a huge volume, but it is useful as a reference because it covers the entire range.
This is the official document of the pandas head family.
Python Data Analysis Library http://pandas.pydata.org/pandas-docs/stable/pandas.pdf
This is also an official example, and the content is huge, so it is good to refer to it as a reference.
This is also the official Matplotlib documentation.
Matplotlib http://matplotlib.org/1.4.0/Matplotlib.pdf
It's a huge amount of over 1,000 pages, but I think it's rare that you need everything, so it's a good idea to refer to the necessary parts as appropriate.
This is the original work of a Japanese book, Introduction to Natural Language Processing. This can also be read for free with a free license.
Natural Language Processing with Python (UPDATED FOR PYTHON 3) --- Analyzing Text with the Natural Language Toolkit http://www.nltk.org/book/
However, of course, the Japanese handling part in Chapter 12 of the above Japanese translation is not included.
However, the Japanese part can also be read here for free.
Japanese natural language processing with Python http://www.nltk.org/book-jp/ch12.html
If you combine these, you can read all chapters as an electronic book for free.
You can read most books for free if you are comfortable with English. There are good articles on the web, but it's still safest to read a well-organized book. It's a very good time.
If you have any other useful books, please let us know.
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