Once the missing data is handled, various operations can be performed on the data.
There are a number of aggregation operations, such as average, sum, and so on, which you would like to perform on a numerical field. These are the methods used to perform it:
ELEMENTARYschool who are obese, we'll first filter the
ELEMENTARYdata with the following command:
>>> data = d[d['GRADE LEVEL'] == 'ELEMENTARY'] 213.41593780369291
Now, we'll find the mean using the following command:
>>> data['NO. OBESE'].mean()
The elementary grade level data is filtered and stored in the data object. The
NO. OBESE column is selected, which contains the number of obese students ...