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Description
LOVE this function. Would love even more if there was an option to do nway=True so that it would add all combinations. For example:
CURRENT:
df.groupby(['sex', 'class','city']).agg({'fare': ['sum']}).stb.subtotal(nway=True)
| sex | class | city | Count |
|---|---|---|---|
| Female | First | Melbourne | 5 |
| Female | First | Burbank | 10 |
| Female | First | Female/First Subtotal | 15 |
| Female | Second | Melbourne | 3 |
| Female | Second | Burbank | 6 |
| Female | Second | Female/Second Subtotal | 9 |
| Female | Female Subtotal | 24 | |
| Male | First | Melbourne | 10 |
| Male | First | Burbank | 15 |
| Male | First | Male/First Subtotal | 25 |
| Male | Second | Melbourne | 9 |
| Male | Second | Burbank | 3 |
| Male | Second | Male/Second Subtotal | 12 |
| Male | Male Subtotal | 37 |
NEW ROWS:
| sex | class | city | Count |
|---|---|---|---|
| Female | Female/City Subtotal | Melbourne | 8 |
| Female | Female/City Subtotal | Burbank | 16 |
| Male | Male/City Subtotal | Melbourne | 19 |
| Male | Male/City Subtotal | Burbank | 18 |
| First/Burbank Subtotal | First | Burbank | 25 |
| First/Burbank Subtotal | Second | Burbank | 9 |
and so on ...
Proc Means in SAS does this and it's such a headache to code in Python. WOULD love if you added it!!!
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