Python is a curious animal (no pun intended) in that it wasn’t exactly designed for data analysis, but with its many free packages this constraint is easily overcome.
In particular, the pandas package has become a mainstay for anything in Python having to do with a table of data in rows and columns… you know, the type of data you’re probably used to working with…
Sign up below for the checklist and access to my resource library: 👇
If you’re already subscribed, you’ll find this resource in the learning-guides-and-checklists folder of the library.
With this free 30 Days to Pandas checklist, you’ll read, watch and download your way across some of the best free content on the web for this fantastic package. After completing, you’ll be able to:
- Sort, filter and aggregate rows
- Calculate, drop and select columns
- Combine data from multiple datasets (think
XLOOKUP(), but far more powerful) - Summarize and explore a dataframe, checking for missing values, descriptive statistics and so forth
Before getting started with this checklist, it would be a good idea to be familiar with basic Python concepts such as variable assignments, lists and so forth. If you would like a resource for that, check out my book Advancing into Analytics. Note that while the book does cover Pandas, this checklist goes into much more detail and would be great supplemental content.
What questions do you have about Pandas or Python for data analysis in general? Do you have other favorite Pandas resources to share? Let me know in the comments.
Leave a Reply