How can you apply functions to Pandas series and data frames? Moreover, when would you want to do so? In this class, we'll explore the map, apply, and applymap functions (among others), seeing how they work, and how to best use them with our data.
Performing complex queries in Pandas? Method chaining will likely make those queries easier to write *and* to read. In this course, we'll review the elements of method chaining, including the use of lambda, assign, and pipe. You'll come out of this course able to write more complex queries in a clear, maintainable way.
Note: This course is included in my Python+Data membership.
Read, manipulate, analyze, and plot data with ease — all within Python! This course contains 12 hours of video lessons, covering all of the aspects of Pandas you need to get up and running. Numerous exercises help to reinforce the ideas with real-world data.
Pandas is great at working with numbers, but it's also great at working with text. In this course, we'll explore text in Pandas — how to work with it, what methods are available, and techniques you can use for improving/optimizing the way you use text.
Note: This course is included in my Python+data membership.
CSV is the most common format for data. In this class, we'll learn about the "read_csv" function, and the many ways we can use it to read data into our Pandas data frames. You'll come out able to to wrangle CSV data, no matter its weird issues, into a data frame.
Note: This course is included in my Pandas+data membership.