Summary
In this chapter, we covered data cleaning, feature engineering, and data wrangling, as well as strategies to deal with missing values.
We saw how Microsoft.Analysis.DataFrame, provided by ML.NET, is capable of working with rows and columns and provides advanced filtering, grouping, and analysis capabilities that are necessary to get our data sources into a clean state.
In the next chapter, we’ll move on from data wrangling to data analysis and see some options to explore the trends and nature of our data sources, through data visualization and some additional DataFrame features.
