Comparing continuous values across categories

The previous sections discussed looking at a single column. This section will show how to compare continuous variables in different categories. We will look at mileage numbers in different brands: Ford, Honda, Tesla, and BMW.

How to do it…

1. Make a mask for the brands we want and then use a group by operation to look at the mean and standard deviation for the city08 column for each group of cars:

   >>> mask = fueleco.make.isin(
   ...     ["Ford", "Honda", "Tesla", "BMW"]
   ... )
   >>> fueleco[mask].groupby("make").city08.agg(
   ...     ["mean", "std"]
   ... )
               mean       std
   make
   BMW    17.817377  7.372907
   Ford   16.853803  6.701029
   Honda  24.372973  9.154064
   Tesla  92.826087  5.538970
   

2. Visualize the city08 values for each make with seaborn:

   >>> g = sns.catplot(
   ...     x="make", y=...