Tidying variable values as column names with melt

Like most large Python libraries, pandas has many different ways to accomplish the same task, the differences usually being readability and performance. A DataFrame has a method named .melt that is similar to the .stack method described in the previous recipe but gives a bit more flexibility.

In this recipe, we use the .melt method to tidy a DataFrame with variable values as column names.

How to do it…

1. Read in the state_fruit2.csv dataset:

   >>> state_fruit2 = pd.read_csv('data/state_fruit2.csv')
   >>> state_fruit2
        State  Apple  Orange  Banana
   0    Texas     12      10      40
   1  Arizona      9       7      12
   2  Florida      0      14     190
   

2. Use the .melt method by passing the appropriate columns to the id_vars and value_vars parameters:

   >>> state_fruit2.melt(id_vars=['State'],
   ...     value_vars=['Apple', &apos...