Pandas Dataframe Assign Value Using Previous N Row Value

Question

This is my pandas dataframe.

                     Status   
index                                    
2011-01-10 16:00:00  Active
2011-01-11 16:00:00  
2011-01-12 16:00:00  Inactive
2011-01-13 16:00:00  
2011-01-14 16:00:00     
2011-01-18 16:00:00

I would like to fill the blank value of the column 'Status' using previous N row value. The result look like following.

                     Status   
index                                    
2011-01-10 16:00:00  Active
2011-01-11 16:00:00  Active
2011-01-12 16:00:00  Inactive
2011-01-13 16:00:00  Inactive
2011-01-14 16:00:00  Inactive   
2011-01-18 16:00:00  Inactive

What's the best way to do?

are those empty rows? if they are, you can convert to null values (np.nan) and downward fill using fillna — sammywemmy, Mar 13 '20 at 05:38
Does this answer your question? [Pandas(Python) : Fill empty cells with with previous row value?](https://stackoverflow.com/questions/41212273/pandaspython-fill-empty-cells-with-with-previous-row-value) — Shaido, Mar 13 '20 at 05:48

score 3 · Accepted Answer · answered Mar 13 '20 at 05:45

if the rows are already null, then forward fill should be sufficient:

  df.ffill()

if the rows are empty string, then replace with np.nan, and forward fill:

  df.replace('',np.nan).ffill()


                       status
 index  
2011-01-10 16:00:00    Active
2011-01-11 16:00:00    Active
2011-01-12 16:00:00    Inactive
2011-01-13 16:00:00    Inactive
2011-01-14 16:00:00    Inactive
2011-01-18 16:00:00    Inactive

Pandas Dataframe Assign Value Using Previous N Row Value

1 Answers1