Real data almost never shows up in the shape you need it. In this module, you'll convert data types, clean up strings and dates, handle missing values, and apply custom functions to get any dataset ready for reliable analysis.

A single dataset rarely tells the whole story on its own. In this module, you'll group and summarize data, reshape it into the layout your analysis actually needs, combine multiple dataframes together, and organize numerical values into meaningful categories.

Numbers on their own are hard to reason about, but a chart or a well-chosen statistic can reveal a pattern instantly. In this module, you'll visualize your data directly in pandas and calculate the statistics that reveal how your variables actually behave and relate to one another.

Pandas has plenty of neighbors worth knowing. In this module, you'll accelerate your exploratory analysis with automated profiling, work with location-based data using a geospatial extension of pandas, and see how pandas' concepts translate to tools built for datasets too large for pandas alone.

You've covered a lot of ground with pandas, from setting up and navigating DataFrames through cleaning, combining, visualizing, and extending your work with tools beyond pandas itself. In this module, you'll complete a comprehensive final assessment and pick up pointers for where to go next.