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Exercise

Linking them together!

In the last lesson, you've finished the bulk of the work on your effort to link restaurants and restaurants_new. You've generated the different pairs of potentially matching rows, searched for exact matches between the cuisine_type and city columns, but compared for similar strings in the rest_name column. You stored the DataFrame containing the scores in potential_matches.

Now it's finally time to link both DataFrames. You will do so by first extracting all row indices of restaurants_new that are matching across the columns mentioned above from potential_matches. Then you will subset restaurants_new on these indices, then append the non-duplicate values to restaurants. All DataFrames are in your environment, alongside pandas imported as pd.

Instructions

100 XP
  • Isolate instances of potential_matches where the row sum is above or equal to 3 by using the .sum() method.
  • Extract the second column index from matches, which represents row indices of matching record from restaurants_new by using the .get_level_values() method.
  • Subset restaurants_new for rows that are not in matching_indices.
  • Append non_dup to restaurants.