1. We will be using the versatile wide_to_long function to reshape our data into tidy form. To use this function, we will need to change the column names that we are stacking, so that they end with a digit. We first create a user-defined function to change the column names:

>>> def change_col_name(col_name):
        col_name = col_name.replace('_name', '')
        if 'facebook' in col_name:
            fb_idx = col_name.find('facebook')
            col_name = col_name[:5] + col_name[fb_idx - 1:] 
                                    + col_name[5:fb_idx-1]
        return col_name

2. Pass this function to the rename method to transform all the column names:

>>> actor2 = actor.rename(columns=change_col_name)
>>> actor2.head()

3. Use the wide_to_long function to stack the actor and Facebook sets of columns simultaneously:

>>> stubs = ['actor', 'actor_facebook_likes']
>>> actor2_tidy = pd.wide_to_long(actor2, 
                                  stubnames=stubs, 
                                  i=['movie_title'], 
                                  j='actor_num', 
                                  sep='_')
>>> actor2_tidy.head()