Pulling data from SQL databases

SQL databases are one of the most used data storage tools in the world. Many companies have teams of several individuals responsible for creating and maintaining these databases, which typically store data crucial for day-to-day operations. These SQL databases are commonly used as source systems for a wide range of data pipelines.

For this exercise, pandas has been imported as pd. Best of luck!

This exercise is part of the course

ETL and ELT in Python

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Exercise instructions

Update the connection URI to create a connection engine for the sales database, using sqlalchemy.
Query all rows and columns of the sales table and output the results.

Hands-on interactive exercise

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

import sqlalchemy

# Create a connection to the sales database
db_engine = sqlalchemy.____("postgresql+psycopg2://repl:password@localhost:5432/____")

# Query the sales table
raw_sales_data = pd.____("____", db_engine)
print(raw_sales_data)

Edit and Run Code