In this chapter, we take a deep dive into the DataFrames.jl
package ecosystem, which allows you to conveniently perform the most common data transformation tasks. In particular, we cover the following topics:
- Converting between
DataFrame
andMatrix
- Investigating the contents of
DataFrame
- Reading CSV data from the internet into
DataFrame
- Working with categorical data
- Handling missing data
- Applying the split-apply-combine pattern to
DataFrame
- Converting
DataFrame
between wide and narrow formats - Comparing two data frames for identity
- Applying complex transformations to rows of
DataFrame
- Creating pivot tables by chaining operations on data frames