Textbooks
=====================

We'll be using a few inexpensive or free paperback/electronic books that will cover different aspects of the course. 
They are all well worth owning. In addition to these free textbooks, we will be using numerous free web based resources.



Textbooks for Summer 2024
------------------------------

Python Data Science Handbook (Jake VanderPlas) (PDSH)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

* There is a free online edition at `https://jakevdp.github.io/PythonDataScienceHandbook/ <https://jakevdp.github.io/PythonDataScienceHandbook/>`_.
* You can also purchase a `paperback copy from O'Reilly <http://shop.oreilly.com/product/0636920034919.do>`_ for ~$45

This is another newish book and is written by a scientist who has been a 
big contributor to the Python data science world. This books covers 
all the main essentials for doing data science work in Python including:

* IPython and Jupyter notebooks - learn to use these effectively
* numpy - the bedrock of data science libraries in Python
* pandas - provides critical data structures and tools for data analysis
* matplotlib - plotting and tool upon which some of the new plotting systems are build
* scikit-learn - statistical/machine learning

There are also Jupyter notebooks that go along with each section of the textbook. These are really well done and will be resource for us as we
explore a range of analytical techniques with Python. The `notebooks are available from this GitHub site <https://github.com/jakevdp/PythonDataScienceHandbook>`_. 
Details on obtaining these notebooks are available the :doc:`Setting up your analytical machine </setup_analytics_machine>`

A Whirlwind Tour of Python (Jake VanderPlas) (WToP)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

One of JVP's contributions is this very nice, concise, intro to programming in Python.

* https://jakevdp.github.io/WhirlwindTourOfPython/
* Free eBook

Data Analysis with Python (DAP) - Wes McKinney
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The 3rd edition of this classic book is available as an open-access online textbook
as of May 2022. The author was the original developer of pandas.

* `Python for Data Analysis <https://wesmckinney.com/book/>`_

It has up to date coverage of numpy, pandas and Jupyter. 


Reproducible and Trustworthy Workflows for Data Science (RTWDS)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Authors: Tiffany A. Timbers, Joel Ostblom, Florencia D’Andrea, Rodolfo Lourenzutti

This is a new set of course notes written entirely in Jupyter notebooks via the `Jupyter Book project <https://jupyterbook.org/intro.html>`_.

You can use it in a variety of ways:

* `read the book online <https://ubc-dsci.github.io/reproducible-and-trustworthy-workflows-for-data-science/README.html>`_
* clone the `GitHub repo <https://github.com/UBC-DSCI/reproducible-and-trustworthy-workflows-for-data-science>`_ and get all the notebooks
* download as pdf, markdown or notebook by using the Download arrow from the online site (by chapter)