I was trying to divide the month into two weeks. Basically for each month i am trying to create week numbers like 1,2,3,4 and repeat them.
How to create the required column like below:
JavaScript
x
31
31
1
import numpy as np2
import pandas as pd3
4
5
df = pd.DataFrame({'Year_Month':['2020-jan']*6+['2020-feb']+['2021-jan']*2+['2021-jan']+['2021-mar']*5})6
df['B'] = [1]*6+[5]+[1]*2+[1]+[10]*57
df['groubyA_repeatB'] = [1,2,3,4,1,2,8
5,9
1,2,3,10
10,11,12,13,10] # groupby column A and repeat [i,i+1,i+2,i+3] 11
12
# e.g. for group A: we have 8 'a' and value of a is 1, so we need to repeat [1,2,3,4] until we get 8 elements.13
df14
15
Year_Month B groubyA_repeatB # how to create this column16
0 2020-jan 1 117
1 2020-jan 1 218
2 2020-jan 1 319
3 2020-jan 1 420
4 2020-jan 1 121
5 2020-jan 1 222
6 2020-feb 5 523
7 2021-jan 1 124
8 2021-jan 1 225
9 2021-jan 1 326
10 2021-mar 10 1027
11 2021-mar 10 1128
12 2021-mar 10 1229
13 2021-mar 10 1330
14 2021-mar 10 1031
Advertisement
Answer
You can utilize cycle to create cycle for list and slice to get specific count
JavaScript
1
6
1
from itertools import cycle, islice2
3
out = (df4
.groupby(['Year_Month', 'B'])5
.apply(lambda g: g.assign(groubyA_repeatB_=list(islice(cycle(range(g.iloc[0]['B'], g.iloc[0]['B']+4)), len(g))))))6
JavaScript
1
19
19
1
print(out)2
3
Year_Month B groubyA_repeatB groubyA_repeatB_4
0 2020-jan 1 1 15
1 2020-jan 1 2 26
2 2020-jan 1 3 37
3 2020-jan 1 4 48
4 2020-jan 1 1 19
5 2020-jan 1 2 210
6 2020-feb 5 5 511
7 2021-jan 1 1 112
8 2021-jan 1 2 213
9 2021-jan 1 3 314
10 2021-mar 10 10 1015
11 2021-mar 10 11 1116
12 2021-mar 10 12 1217
13 2021-mar 10 13 1318
14 2021-mar 10 10 1019