I stacked a dataframe using:
df.groupby(["date", "level", "key", "isUsed"]).agg({'NetSalesExVATGBP':'sum'}).unstack(fill_value=0).stack()
To get the resulting dataframe:
How to transform this dataframe to get all rows with all values?
| date | level | key | isUsed | NetSalesExVatGBP |
|---|---|---|---|---|
| 2020-08-07 | 1 | 1 | 0 | 9882.42 |
| 2020-08-07 | 1 | 1 | 1 | 174.79 |
| 2020-08-07 | 1 | 2 | 0 | 6742.23 |
and etc...
I know that it is possible to access individual elements with iterrows() method and then save it to separate lists and create dataframe from that, but it seems very bad method to do it.
