Concatenate dataframes

In this exercise, you’ll practice concatenating records by creating a dataset of the 100 highest-rated cafes in New York City according to Yelp.

APIs often limit the amount of data returned, since sending large datasets can be time- and resource-intensive. The Yelp Business Search API limits the results returned in a call to 50 records. However, the offset parameter lets a user retrieve results starting after a specified number. By modifying the offset, we can get results 1-50 in one call and 51-100 in another. Then, we can append the dataframes.

pandas (as pd), requests, and json_normalize() have been imported. The 50 top-rated cafes are already in a dataframe, top_50_cafes.

This exercise is part of the course

Streamlined Data Ingestion with pandas

View Course

Exercise instructions

Add an "offset" parameter to params so that the Yelp API call will get cafes 51-100.
Concatenate the results of the API call to top_50_cafes, setting ignore_index so rows will be renumbered.
Print the shape of the resulting dataframe, cafes, to confirm there are 100 records.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Add an offset parameter to get cafes 51-100
params = {"term": "cafe", 
          "location": "NYC",
          "sort_by": "rating", 
          "limit": 50,
          ____}

result = requests.get(api_url, headers=headers, params=params)
next_50_cafes = json_normalize(result.json()["businesses"])

# Concatenate the results, setting ignore_index to renumber rows
cafes = ____

# Print shape of cafes
____

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