This lesson is in the early stages of development (Alpha version)

Python for Data Analysis

These are lessons on data analysis using Python from the Molecular Sciences Software Institute (MolSSI). This website is based on a lesson template from Software Carpentry

To see the full MolSSI’s education mission statement, please see here. You can see more resources from MolSSI here.


  • Students should be familiar with opening the Terminal window and creating and navigating files in bash.
  • Students should be familiar with Python syntax, control structures (conditional statements, for loops), parsing files, and importing packages. If you are unfamiliar with this material, please see our Python Data and Scripting Workshop


Setup Download files required for the lesson
00:00 1. Working with Numpy Arrays What are the differences between numpy arrays and lists?
How can I use NumPy to do calculations?
01:05 2. Using pandas for data analysis What is pandas?
How do I access data in a pandas dataframe?
01:05 3. Using scipy for data fitting How do I fit data to a specified function?
How do I assess the quality of my fit?
How do I determine the standard error for my fit parameters?
01:45 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.