Filter dataframe A based on columns from dataframe B

Question

I have two dataframes where dataframe A has much more columns than dataframe B, what i would like to do is filter dataframe A by using dataframe B as reference and obtain a new dataframe A with the same amount of columns that dataframe A has. For example:

df_A = pd.DataFrame(np.random.randn(150, 17), columns=list('ABCDEFGHIJKLMONPQ'))
df_B = pd.DataFrame(np.random.randn(150, 8), columns=list('ABCDEFGH'))

I would like to filter out the extra columns in df_A and have a df_A with the same columns that df_B has.

So df_A as output would have columns 'ABCDEFGH'

Answer 1

Use filter.

df_A.filter(df_B.columns)

Or

df_A[df_B.columns]