9 Practical data analysis

This chapter covers

  • Using statistical tools: sum, average, standard deviation, and frequency distributions
  • Grouping and summarizing a data set to make sense of it
  • Using tools for working with time series data: rolling average, linear regression, and more
  • Using data analysis techniques for comparing data and making predictions
  • Using correlation to understand the relationship between data variables

Congratulations, you made it to the data analysis chapter. It took much work to get here. We’ve had to fetch our data from somewhere, and we had to clean and prepare it. Then it turned out that we had more data than we could deal with, so we had to move it to our database to deal with it. It’s been a long road.

Data analysis ...

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