6 Summarizing and analyzing DataFrames

This chapter covers

  • Producing descriptive statistics for a Dask Series
  • Aggregating/grouping data using Dask’s built-in aggregate functions
  • Creating your own custom aggregation functions
  • Analyzing time series data with rolling window functions

At the end of the previous chapter we arrived at a dataset ready for us to start digging in and analyzing. However, we didn’t perform an exhaustive search for every possible issue with the data. In reality, the data cleaning and preparation process can take a far longer time to complete. It’s a common adage among data scientists that data cleaning can take 80% or more of the total time spent on a project. With the skills you learned in the previous chapter, you ...

Get Data Science with Python and Dask now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.