How group by sum and average column in python?

Question

As input I have a CSV file with times and a bunch of numbers for each time.

Time,F1,F2,F3
8:11,5,2,4
9:25,9,8,2
9:39,7,3,2
9:53,6,5,1
10:07,4,6,7
10:21,7,3,1         


        

Answer 1

The following should get you started, it uses Python's csv module to process the files and itertools.groupby to group the entries by hour:

import csv
from itertools import groupby, chain

with open('input.csv', 'rb') as f_input, open('output.csv', 'wb') as f_output:
    csv_input = csv.reader(f_input)
    csv_output = csv.writer(f_output)
    header = next(csv_input)
    csv_output.writerow(["Time","SUM F1","SUM F2","SUM F3","AVG F1","AVG F2","AVG F3"])

    for k, g in groupby(csv_input, lambda x: int(x[0].split(':')[0])):
        entries = [(int(f1), int(f2), int(f3)) for t, f1, f2, f3 in g]
        sums = [(sum(x), sum(x)/float(len(entries))) for x in zip(*entries)]
        row = ['{}:00'.format(k)] + list(chain.from_iterable(zip(*sums)))
        csv_output.writerow(row)

This would give you an output csv file looking like this:

 Time,SUM F1,SUM F2,SUM F3,AVG F1,AVG F2,AVG F3
 8:00,5,2,4,5.0,2.0,4.0
 9:00,22,16,5,7.333333333333333,5.333333333333333,1.6666666666666667
 10:00,16,15,15,5.333333333333333,5.0,5.0
 11:00,1,2,1,1.0,2.0,1.0
 12:00,3,3,1,3.0,3.0,1.0

zip is used to transpose the column entries.

Tested using Python 2.7.9

Answer 2

A pandas solution:

import pandas as pd

df = pd.read_csv('f123.csv')
df['Time'] = df['Time'].apply(lambda x: x.split(':')[0] + ':00')
by_hour = df.groupby('Time')
data = {}
for name in ['F1', 'F2', 'F3']:
    data['SUM ' + name] = by_hour[name].sum()
    data['AVG ' + name] = by_hour[name].mean()
res = pd.DataFrame(data)
print(res)

prints:

         AVG F1    AVG F2    AVG F3  SUM F1  SUM F2  SUM F3
Time                                                       
10:00  5.333333  5.000000  5.000000      16      15      15
11:00  1.000000  2.000000  1.000000       1       2       1
12:00  3.000000  3.000000  1.000000       3       3       1
8:00   5.000000  2.000000  4.000000       5       2       4
9:00   7.333333  5.333333  1.666667      22      16       5

Save as csv file:

res.to_csv('res.csv')

This is the content of res.csv:

Time,AVG F1,AVG F2,AVG F3,SUM F1,SUM F2,SUM F3
10:00,5.333333333333333,5.0,5.0,16,15,15
11:00,1.0,2.0,1.0,1,2,1
12:00,3.0,3.0,1.0,3,3,1
8:00,5.0,2.0,4.0,5,2,4
9:00,7.333333333333333,5.333333333333333,1.6666666666666667,22,16,5