If you want to check equals values on a certain column let's say Name you can merge both Dataframes to a new one:

mergedStuff = pd.merge(df1, df2, on=['Name'], how='inner')
mergedStuff.head()

I think this is more efficient and faster then whereif you have a big data set

If you want to check equal values on a certain column, let's say Name, you can merge both DataFrames to a new one:

mergedStuff = pd.merge(df1, df2, on=['Name'], how='inner')
mergedStuff.head()

I think this is more efficient and faster than where if you have a big data set.

If you want to check equals values on a certain column let's say Name you can merge both Dataframes to a new one:

mergedStuff = pd.merge(df1, df2, on=['Name'], how='outer')
mergedStuff.head()

I think this is more efficient and faster then whereif you have a big data set

If you want to check equals values on a certain column let's say Name you can merge both Dataframes to a new one:

mergedStuff = pd.merge(df1, df2, on=['Name'], how='inner')
mergedStuff.head()

I think this is more efficient and faster then whereif you have a big data set