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
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())