CODEWITHSUNDEEP
pythonpandasdataframe
C.Carrel
C.Carrel

Reputation: 49

.rolling() on groupby dataframe

I grouped a data frame by week number and get a column of numbers that looks like this

0 0.0
1 0.0
2 0.0
3 0.0
4 0.0
5 0.0
6 0.0
7 0.0
8 0.0
9 0.0
10 0.0
11 0.0
12 0.0
13 0.0
14 0.0
15 0.0
16 235.0
17 849.0
18 1013.0
19 1155.0
20 1170.0
21 1247.0
22 1037.0
23 1197.0
24 1125.0
25 1106.0
26 1229.0

I used the following line of code on the column: df_group['rolling_total'] = df_group['totals'].rolling(2).sum()

This is my desired result:

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
235.0
1084.0
2097.0
3252.0
4422.0
5669.0
6706.0
7903.0
9028.0
10134.0
11363.0

I get this instead:

0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
235.0 
1084.0
1862.0 
2168.0
2325.0
2417.0
2284.0
2234.0
2322.0
2231.0
2335.0

All I want is the rolling sum of the column. Is .rolling() not the way to accomplish this? Is there something I am doing wrong?

Upvotes: 2

Views: 49

Answers (1)

Andrej Kesely
Andrej Kesely

Reputation: 195408

Use .cumsum(), not .rolling():

print(df.cumsum())

Prints:

    column1
0       0.0
1       0.0
2       0.0
3       0.0
4       0.0
5       0.0
6       0.0
7       0.0
8       0.0
9       0.0
10      0.0
11      0.0
12      0.0
13      0.0
14      0.0
15      0.0
16    235.0
17   1084.0
18   2097.0
19   3252.0
20   4422.0
21   5669.0
22   6706.0
23   7903.0
24   9028.0
25  10134.0
26  11363.0

Upvotes: 2

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