pandas,Replace Values in a dataframe, depending on other Column

Question

I have A dataframe like below,

df = pd.Dataframe({'Col1' : pd.Series(['Abc','Cde','Efg','Abc'], index=['a', 'b', 'c','d']),
 'Col2' : pd.Series([10, 20, 30, 40], index=['a', 'b', 'c', 'd']),
 'Col3' : pd.Series([1, 2., 3., 4.], index=['a', 'b', 'c', 'd'])})

By Depending on the value of the column value in Col1, I want to replace Col3 Value by Col2,

In this case where Col1 value is "Abc" I want to update Col3 value with Col2 value , expecting output like

pd.Dataframe({'Col1' : pd.Series(['Abc','Cde','Efg','Abc'], index=['a', 'b', 'c','d']),
 'Col2' : pd.Series([10, 20, 30, 40], index=['a', 'b', 'c', 'd']),
 'Col3' : pd.Series([10, 2., 3., 40], index=['a', 'b', 'c', 'd'])})

Tried by filter , that aint generic, so any proper method to do same !!

Answer 1

This should work:

import pandas as pd

df = pd.DataFrame({'Col1' : pd.Series(['Abc','Cde','Efg','Abc'], index=['a', 'b', 'c','d']),
                   'Col2' : pd.Series([10, 20, 30, 40], index=['a', 'b', 'c', 'd']),
                   'Col3' : pd.Series([1, 2., 3., 4.], index=['a', 'b', 'c', 'd'])})

df.loc[df['Col1'] == 'Abc', 'Col3'] = df['Col2']