How to assign a value to pandas dataframe column rows based on a condition

[klllmmm]

Hello,

I want to assign a value in "Value" column into a new column and up to all next empty rows until next value comes. My expected value is available in a new column 'Expected_Value'.

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import pandas as pd   df2 = pd.DataFrame({ 'Value':['Second', np.nan, np.nan, 'Fourth', np.nan],                     'Name':['John', 'Tom', 'Tom', 'Tom','One'],                     'Expected_Value':['Second', 'Second', 'Second', 'Fourth', 'Fourth']                     })

I tried this using two functions (apply lambda & assign lambda), however, there were error messages as follows.

apply lambda method

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df2['new_value'] = np.nan   df2['new_value'] = df2.apply(lambda row: row['Value'] if (~pd.isna(row['Value'])) else row['new_value'].shift(-1))   # KeyError: 'Value'

Assign lambda method

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del df2['new_value'] df2 = df2.assign(new_value=lambda x: (x['Value']) if (~(x['Value'].isna())) else x['new_value'].shift(-1)) # ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

Appreciate it if someone could help with this.