How to make current row value equal to previous row value if a column equals a value in Pandas?

Question

I have the dataframe as below: df ID val 1 0.0 2 yes 3 1.0 4 0.0 5 yes How do I match my previous value with my current value if the column val equals "yes" I tried using the code below: df['val'] = df['val'].replace('yes', np.nan).bfill().astype(str) I am getting this output which is not what I wanted to. ID val 1 yes 2 yes 3 1.0 4 yes 5 yes can we use np.where along with the bfill? Select the correct answer from above options

Answer 1

You can use the below code: df.loc[df['val'].shift(-1).eq('yes'), 'val'] = 'yes' Output: ID val 0 1 yes 1 2 yes 2 3 1.0 3 4 yes 4 5 yes If you want to know more about the Data Science then do check out the following Data Science which will help you in understanding Data Science from scratch