Backwards Fill Dataframe Column Where Limit Of Rows Filled Is Based On Value Of Cell, Perhaps With Bfill() And Limit=x

I have a dataframe that looks like this: import pandas as pd, numpy as np df = pd.DataFrame({'Fill' : [0, 0, 0, 3, 0, 0, 0, 2, 0, 0, 1]}) df['flag'] = (df['Fill'] > 0) df = df.r

Solution 1:

You can create groups for each missing and last non missing values and replace by last values in custom function, if-else is necessaary for avoid error ValueError: Limit must be greater than 0:

m = df['Fill'].notnull() & df.flag
g = m.iloc[::-1].cumsum().iloc[::-1]

f = lambda x: x.bfill(limit=int(x.iat[-1]-1)) if x.iat[-1] > 1 else x
df['Fill'] = df.groupby(g)['Fill'].apply(f)
print (df)
    Fill   flag
0    NaN  False
1    3.0  False
2    3.0  False
3    3.0   True
4    NaN  False
5    NaN  False
6    2.0  False
7    2.0   True
8    NaN  False
9    NaN  False
10   1.0   True