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Filtering your database records using SQL's WHERE

You can now execute a basic SQL query to select records from any table in your database and you can also perform simple query customizations to select particular columns and numbers of rows.

There are a couple more standard SQL query chops that will aid you in your journey to becoming an SQL ninja.

Let's say, for example that you wanted to get all records from the Customer table of the Chinook database for which the Country is 'Canada'. You can do this very easily in SQL using a SELECT statement followed by a WHERE clause as follows:

SELECT * FROM Customer WHERE Country = 'Canada'

In fact, you can filter any SELECT statement by any condition using a WHERE clause. This is called filtering your records.

In this interactive exercise, you'll select all records of the Employee table for which 'EmployeeId' is greater than or equal to 6.

Packages are already imported as follows:

import pandas as pd
from sqlalchemy import create_engine

Query away!

This is a part of the course

“Introduction to Importing Data in Python”

View Course

Exercise instructions

  • Complete the argument of create_engine() so that the engine for the SQLite database 'Chinook.sqlite' is created.
  • Execute the query that selects all records from the Employee table where 'EmployeeId' is greater than or equal to 6. Use the >= operator and assign the results to rs.
  • Apply the method fetchall() to rs in order to fetch all records in rs. Store them in the DataFrame df.
  • Using the rs object, set the DataFrame's column names to the corresponding names of the table columns.

Hands-on interactive exercise

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

# Create engine: engine
engine = create_engine(____)

# Open engine in context manager
# Perform query and save results to DataFrame: df
with engine.connect() as con:
    rs = con.execute(____)
    df = pd.DataFrame(____)
    df.columns = ____

# Print the head of the DataFrame df
print(df.head())
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