We can find the mean values for the numerical column in each group. This can be done using the df.mean() method.

The code for finding the mean is as follows:

# mean() will print mean of numerical column in each group
style.mean()

The output of the preceding code is as follows:

Note that we can get the average of each column by specifying a column, as follows:

# get mean of each column of specific group
style.get_group("convertible").mean()

The output of the preceding code is as follows:

Next, we can also count the number of symboling/records in each group. To do so, use the following code:

# get the number of symboling/records in each group
style['symboling'].count()

The output of the preceding code is as follows:

body-style
convertible 6
hardtop 8
hatchback 68
sedan 94
wagon 25
Name: symboling, dtype: int64

Having understood the counting part, in the next section, we are going to discuss different types of data aggregation techniques.