The low-level library for making figures in Python is called matplotlib. It’s very powerful, but also a little too low-level for most social science uses, so it’s probably not your best bet. Instead, most people use either seaborn, or ggplot (meant to duplicate syntax and functionality of ggplot in R).
If you’re accustomed to using ggplot in R, then good news: the folks at yhat have duplicated it’s functionality in Python! This library is still quite young, but seems very promising.
The other very popular library for plotting is called seaborn. It’s build on top of matplotlib, and basically allows you to make common statistical plots more easily. If you come from stata, think of seaborn as your twoway; if you come from R, it’s your ggplot.
- Main page
- Gallery of example plots (with the code that made them)
- Introduction to seaborn
- Tutorial. (Note this is not the default tutorial on the seaborn site, but another one that’s hidden away I actually much prefer!)
At the time of this is being written, seaborn did not come with Anaconda by default, but can be easily added by typing conda install seaborn in your terminal window.