Python Data Science Tools

Workshop focused on Python's data science tools such as NumPy, Matplotlib, SymPy and Pandas libraries, using Jupyter Notebooks.

Content

1. IPython - Notebook / Webpage
2. NumPy - Notebook / Webpage
3. Matplotlib - Notebook / Webpage
   1. Simple Plots - Notebook / Webpage
   2. Other Plots - Notebook / Webpage
   3. Sub Plots - Notebook / Webpage
4. SymPy - Notebook / Webpage
5. Pandas ~ To be released

Exercises and Solutions

1. Exercises
2. Challenges

Required Resources

An IDE, text editor or shell for Python development.

• Anaconda: Installs python and all the required modules for you, recommended for an easier setup.
• Google Collab: Virtual environment with everything setup.
• VS Code: Requires the manual installation of the most recent version of Python 3. Please refer to Python in VS Code for more detailed instructions. We recommend the Code Runner extension (present on the website listed above).

If you use your own custom editor (eg: VS Code) If you are familiar with Python and pip, please use the following command to install the required libraries: Or, in a 'simple' command, pip install numpy pandas scipy matplotlib seaborn jupyter notebook

Note: If running Windows, you may want to open the shell with administrator privileges to install the libraries for all users. Also don't forget to add the Python folder to the PATH if not present already.

Sources

• Python Data Science Handbook
• Python NumPy Tutorial
• Python Pandas for your grandma

Authors

• Eduardo Correia (@educorreia932)
• Tiago Silva (@tiagodusilva)