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  3. Streamlined Data Ingestion with pandas

Exercise

Joining, filtering, and aggregating

In this exercise, you'll use what you've learned to assemble a dataset to investigate how the number of heating complaints to New York City's 311 line varies with temperature.

In addition to the hpd311calls table, data.db has a weather table with daily high and low temperature readings for NYC. We want to get each day's count of heat/hot water calls with temperatures joined in. This can be done in one query, which we'll build in parts.

In part one, we'll get just the data we want from hpd311calls. Then, in part two, we'll modify the query to join in weather data.

pandas has been imported as pd, and the database engine has been created as engine.

Instructions 1/2

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  • Complete the query to get created_date and counts of records whose complaint_type is HEAT/HOT WATER from hpd311calls by date.
  • Create a dataframe,df, containing the results of the query.