Melting multiple groups of columns

When we needed to melt multiple groups of columns in the previous recipe, we used melt twice and then merged the resulting DataFrames. That worked fine, but we can accomplish the same tasks in one step with the wide_to_long function. wide_to_long has more functionality than melt, but is a bit more complicated to use.

Getting ready

We will work with the weeks worked and college enrollment data from the NLS in this recipe.

How to do it…

We will transform multiple groups of columns at once using wide_to_long:

1. Import pandas and load the NLS data:

   import pandas as pd
   nls97 = pd.read_csv("data/nls97g.csv", low_memory=False)
   nls97.set_index('personid', inplace=True)
   

2. View some of the weeks worked and college enrollment data:

   weeksworkedcols = ['weeksworked17','weeksworked18',
     'weeksworked19','weeksworked20','weeksworked21&apos...