Joining and filtering

Just as you might not always want all the data in a single table, you might not want all columns and rows that result from a JOIN. In this exercise, you'll use SQL to refine a data import.

Weather exacerbates some housing problems more than others. Your task is to focus on water leak reports in hpd311calls and assemble a dataset that includes the day's precipitation levels from weather to see if there is any relationship between the two. The provided SQL gets all columns in hpd311calls, but you'll need to modify it to get the necessary weather column and filter rows with a WHERE clause.

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

This exercise is part of the course

Streamlined Data Ingestion with pandas

View Course

Hands-on interactive exercise

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

# Query to get hpd311calls and precipitation values
query = """
SELECT hpd311calls.*, ____
  FROM hpd311calls
  ____ weather
  ____ hpd311calls.____ = ____;"""

# Load query results into the leak_calls dataframe
leak_calls = ____

# View the dataframe
print(leak_calls.head())

Edit and Run Code