pandas ffill based on condition in another column

Question

I have a pandas DataFrame as shown below.

df = pd.DataFrame({
    \'date\': [\'2011-01-01\', \'2011-01-01\', \'2011-02-01\', \'2011-02-01\', \'2011-03-01\',         


        

Answer 1

Use groupby:

df.groupby('category').ffill()

Output:

   category        date  rate
0         1  2011-01-01  0.50
1         2  2011-01-01  0.75
2         1  2011-02-01  0.50
3         2  2011-02-01  0.75
4         1  2011-03-01  1.00
5         2  2011-03-01  1.25
6         1  2011-04-01  1.00
7         2  2011-04-01  1.25

If you have other columns with NaN that you don't want fill, then you can use this to just ffill NaN in rate column:

df['rate'] = df.groupby('category')['rate'].ffill()