Congratulations, you have now increased your data literacy skills by workingwith data as both a consumer and producer of analytics. We covered some important topics, including essential skills to manipulate data by creating views of data, sorting, and querying tabular data from a SQL source. You now have a repeatable workflow for combining multiple data sources into one refined dataset.
We explored additional features of working with pandas DataFrames, showing how to restrict and sift data. We walked through real-world practical examples using the concept of user churn
to answer key business questions about usage patterns by isolating specific users and dealing with missing values from the source data.
Our next chapter is Chapter 8, Understanding Joins, Relationships, and Data Aggregates. Along with creating a summary analysis using a concept called aggregation, we will also go into detail on how to join data with defined relationships.
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