I have two dataframes. df1 has more elements (3) in column ‘Table_name’ than df2 (2). I want a resultant dataframe that only outputs the rows where df1 and df2 share the same column names.
df1
Table_Name | Type id | int name | string position| string
df2
Table_Name | Type id | float name | string
I want this to be the result.
df_result
Table_Name | Type id | int name | string
This is what i tried but it doesn’t work:
similar_cols = df1[df1['Table_name'].isin(df2['Table_name'])].dropna()
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Answer
You need loc
here
similar_cols = df1.loc[df1['Table_name'].isin(df2['Table_name'])]