Pandas find the mean of DataFrame based on a conditional across multiple columns

Question

I am trying to find the average weight of females under 20, I have the following DataFrame, I have already converted age to int and weight to float.

 age   weight     height   male
 39.0   88.636360   180.0   True
 64.0   75.000000   155.0  False
 17.0  100.000000   183.0  False
 35.0   63.636364   170.0  True
 18.0   70.454544   173.0  False

I've tried df.groupby(['male','age'])['weight'].mean()[False] but it just returns something like:

age    
18.0    64.225121
19.0    65.499535
20.0    67.855026
21.0    69.622658
22.0    69.376862

How can I filter it so that it aggregates the weight of all female under 20 then takes the average?

Answer 1

There's no need for groupby unless I'm misunderstanding. You can filter the dataframe based on your conditions then take the mean of the weight column.

df.loc[(~df["male"]) & (df["age"] < 20), "weight"].mean()