1. Wrap-up
Congratulations! You've now covered the basics of using pandas.
2. Recap
In chapter 1, you saw how to subset and sort DataFrames and how to add new columns.
In chapter 2, you saw several methods for aggregating and grouping data to calculate summary statistics.
In chapter 3, you saw how using indexing and slicing allows for simpler subsetting.
In chapter 4, you saw how to visualize a DataFrame, and how to read data from and write data to CSV files.
3. More to learn
I hope you are convinced that pandas is a powerful tool to analyze tabular data. In fact, pandas is so powerful that there are many features that we didn't get around to discussing in this course.
To begin with, everything in this course involved a single DataFrame, but sometimes you need to join or "merge" several DataFrames together.
Reading from CSV files barely scratches the surface of the options for importing data into pandas.
You can also perform very sophisticated exploratory data analysis using pandas.
4. Congratulations!
Congratulations, and have fun learning!