Loading data into PostgreSQL tables

To complete the data pipeline, you need to load the transformed data into the final output locations – the PostgreSQL data tables – so that your client can easily access and use them. In this section, you will load the cleaned data into the PostgreSQL chicago_dmv schema using the psycopg2 Python module. As you may recall from the previous chapter, psycopg2 is a Python package that enables you to connect your Python (or Jupyter Notebook) script to PostgreSQL. Use the following code to establish a connection to the database from your Jupyter Notebook:

import psycopg2# Establish connection to the Postgresql database
conn = psycopg2.connect(database="your_database_name",
    user="your_username", password="your_password",
    host="your_host", port="your_port")
# Create a cursor object
cur = conn.cursor()

Using SQL statements in Python, denoted...