Other techniques for reshaping data

In this chapter, we have so far covered crucial data operations such as pivoting, unpivoting/unpivoting, joining, and concatenating. There are a few other techniques you can use to reshape your data, such as .partition_by(), .transpose(), .reshape(). We’ll cover those methods in this recipe.

Getting ready

We’ll continue to use the academic_df DataFrame that we’ve become familiar with throughout this chapter.

How to do it...

Here’s how to apply those reshaping techniques:

1. To partition the DataFrame into separate DataFrames by column values, we used the .partition_by() method:

   academic_df.partition_by('academic_year')

   The preceding code will return the following output:

Figure 8.22 – The partitioned DataFrames by values in the academic_year column

2. Use the .transpose() method to flip rows and columns:

   academic_df.transpose(include_header=True)

   The preceding...