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 the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.