So far we've conducted data analysis and created data visualizations in Microsoft Excel. While Excel is useful becuase we can see our data and because it's readily accessible, Excel doesn't work well with larger datasets (it'll crash or work extremely slow) and it doesn't allow us to create a neat legacy of our work and manipulations so that we or others can check or replicate our work.
Python solves these problems for us. We'll re-create our initial data analysis with the Opportunity Insights college social mobility data that we conducted in Excel, and then we'll work with larger and more complicated datasets to characterize Python's power and complexity.
We'll first work with Python in Google Colaboratory--an integrated development environment (essentially where we can run and execute code) based in Google Drive. This is free, but you'll have to install it in your personal Google Drive.
You can view the notebooks worked on in class here:
Intro to Python and Colaboratory with College Characteristic Data
Intro to Python and Colaboratory with College Characteristic Data Starter Notebook (comments, but no code)