Find maximum of column for each business quarter pandas

Question

Assume that I have the following data set

import pandas as pd, numpy, datetime

start, end = datetime.datetime(2015, 1, 1), datetime.datetime(2015, 12, 31)
date_list = pd.date_range(start, end, freq='B')
numdays = len(date_list) 

value = numpy.random.normal(loc=1e3, scale=50, size=numdays)
ids = numpy.repeat([1], numdays)

test_df = pd.DataFrame({'Id': ids,
               'Date': date_list,
               'Value': value})

I would now like to calculate the maximum within each business quarter for test_df . One possiblity is to use resample using rule='BQ', how='max' . However, I'd like to keep the structure of the array and just generate another column with the maximum for each BQ, have you guys got any suggestions on how to do this?

Answer 1

I think the following should work for you, this groups on the quarter and calls transform on the 'Value' column and returns the maximum value as a Series with it's index aligned to the original df:

In [26]:
test_df['max'] = test_df.groupby(test_df['Date'].dt.quarter)['Value'].transform('max')
test_df
Out[26]:
          Date  Id        Value          max
0   2015-01-01   1  1005.498555  1100.197059
1   2015-01-02   1  1032.235987  1100.197059
2   2015-01-05   1   986.906171  1100.197059
3   2015-01-06   1   984.473338  1100.197059
........
256 2015-12-25   1   997.965285  1145.215837
257 2015-12-28   1   929.652812  1145.215837
258 2015-12-29   1  1086.128017  1145.215837
259 2015-12-30   1   921.663949  1145.215837
260 2015-12-31   1   938.189566  1145.215837

[261 rows x 4 columns]