Use of groupby in a function with Pandas

[Paulman]

Hello,

I'm totally stuck with a task on using groupby in a dataframe.

I have the following df in a csv file 'athletes.csv:

,forename,surname,gender,age,100m,200m,400m,800m,1500m
0,Migdalia,Parrish,F,18,11.08,29.0,59.41,122.05,259.11
1,Valerie,Lee,F,10,17.23,46.0,100.02,232.64,480.95
2,John,Debnam,M,17,10.81,25.89,50.6,110.29,232.39
3,Roy,Miller,M,10,19.18,46.74,95.32,201.14,430.27
4,Aida,Aumiller,F,11,15.3,41.83,81.06,189.03,394.9
5,Marcia,Brown,F,19,11.13,24.62,57.59,119.13,256.37
6,Harry,Knows,M,16,12.39,25.94,49.67,106.56,237.14
7,Barry,Lennon,M,14,11.15,23.56,46.46,110.89,230.49
8,Lilia,Armstrong,F,13,8.84,25.09,59.54,128.95,258.47
9,Johnny,Casey,M,15,9.65,22.67,49.46,112.85,233.87
10,Donald,Taylor,M,15,11.74,22.42,49.22,114.62,224.63
11,Martha,Woods,F,14,9.01,24.34,55.25,118.8,254.87
12,Diane,Lauria,F,15,8.99,27.92,54.79,119.89,249.21
13,Yvonne,Pumphrey,F,16,8.84,27.29,57.63,123.13,247.41
14,Betty,Stephenson,F,14,11.04,28.73,59.05,126.29,256.44
15,Lilia,Armstrong,F,12,11.31,34.43,74.28,150.05,321.07

The task is to call (and print) from a main function another function which takes three attributes:
- The dataframe df
- The age 15
- The mean value for all events (100m,200m,400m,800m,1500m)) for the age 15
The function should be grouped by gender and should reset the index.

The output should be like the below.
Input:
age_statistics(df,15,'mean')
Output:

   gender   100m      200m     400m      800m      1500m      
            mean      mean     mean      mean      mean
0    F      8.990    27.920   54.790    119.890    249.210
1    M     10.695    22.545   49.340    113.735    229.250

I'm completely stuck with the function that groups the 15 years'old athletes in females and males and for each gender calculates the mean value for each event.

# function to groupby 
def age_statistics(df,age,mean):
# no idea how to build it  
   aggregated_dataframe = aggregated_dataframe.reset_index(drop=False)
   return aggregated_dataframe

# main function
def main(filename='athletes.csv'):
    df = pd.read_csv(filename, index_col=0)
    df['100m'] = df['100m'].astype(float)
    df['200m'] = df['200m'].astype(float)
    df['400m'] = df['400m'].astype(float)
    df['800m'] = df['800m'].astype(float)
    df['1500m'] = df['1500m'].astype(float)
    print(age_statistics(df,15,'mean'))

# Do not edit this
if __name__ == "__main__":
  main()

Anybody can help with that?