Introduction to Python for Data Science
This is a four-day workshop that will introduce students to Python as a data science language. We teach the basics of programming and logic in the context of Python and go on to show the tools that use Python for modern data analysis. This assumes no prior knowledge of Python, but will move at a quick pace to cover all the content. The workshop meets for 3 hours for 4 sessions.
Getting started
These workshops are Jupyter notebooks, which are interactive Python code blocks interleaved with formatted text. You can participate in this workshop by downloading the appropriate student notebook below and then simply uploading it to Google Colab . That's it! The notebook should load and be able to run without any additional setup.
Workshop content
Day 1: Programming basics and intro to logic and control
- Functions and data types
- Operators as functions
- Logical oprations
- Control flow (if/else statements; loops)
Download the student jupyter notebook - View completed jupyter notebook
Day 2: Iterables and writing functions
- Lists and dictionaries
- More on loops
- Importing libraries
- Writing functions
Download the student jupyter notebook - View completed jupyter notebook
Day 3: Metaprogramming tips and more advanced function writing
- Debugging strategies
- Exception handling
- More function writing
Download the student jupyter notebook - View completed jupyter notebook
Day 4: Numpy arrays, reading and writing files
- Python review
- Reading and writing files
- Introduction to Numpy
Download the student jupyter notebook - View completed jupyter notebook
Day 5: Pandas dataframes and plotting
Download the student jupyter notebook - View completed jupyter notebook
Day 6: Analyzing a real dataset: Indiana storms
- Introduction to the Indiana storms dataset
- Exercises to practice the skills learned in the previous days
Download the student jupyter notebook - View completed jupyter notebook