Week 1
Exploratory Data Science in Python

Topics

• Course Logistics
• Using Jupyter Notebooks
• Introduction to Pandas

Initial Survey

Please fill out this anonymous survey for some initial feedback:

https://bit.ly/musa550-initial-feedback

Recommended Readings

• Course syllabus
• Guide for installing Python and initial set up
• Guide for mamba/conda
  • Check out this 20-minute guide on the conda docs
• Guide for Jupyter notebooks and JupyterLab
  • Good readings on the Jupyter docs include:
    • Starting JupyterLab
    • The JupyterLab interface
    • The structure of a notebook document
    • The notebook workflow
    • Working with notebooks in JupyterLab
    • Working with files
• Recommended tutorial for students with little Python background: Practical Python Programming

Python tutorials & DataCamp access

A number of Python resources are listed on the course website. In particular, DataCamp is providing 6 months of complimentary access to its courses for students in MUSA 550. Whether you have experience with Python or not, this is a great opportunity to learn the basics of Python and practice your skills.

It is strongly recommended that you watch some or all of the introductory videos below to build a stronger Python foundation for the semester. The more advanced, intermediate courses are also great — the more the merrier!

Check out the resources page for more information, including how to sign up.

Additional materials

Documentation

• Git and GitHub:
  • Setting up git
  • Managing files on GitHub
• Conda user guide
• Jupyter notebook
• Guide to Markdown in notebook cells
• Binder Documentation
• pandas documentation
• matplotlib documentation

Readings/reference

• StackOverflow: The Incredible Growth of Python
• 2015 Funding Proposal for the Jupyter Notebook
• A history of Jupyter Notebooks by its founder
• Google's Colab
• Tidy Data
• Joining Datasets
• ZIllow Data
• Introduction to writing your first Python program
• Visual Studio Code