How to Visualize Autopilot Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Autopilot-connected Python applications and scripts for visualizing Autopilot data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Autopilot data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Autopilot data in Python. When you issue complex SQL queries from Autopilot, the driver pushes supported SQL operations, like filters and aggregations, directly to Autopilot and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Autopilot Data

Connecting to Autopilot data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Start by setting the Profile connection property to the location of the Autopilot Profile on disk (e.g. C:\profiles\Autopilot.apip). Next, set the ProfileSettings connection property to the connection string for Autopilot (see below).

Autopilot API Profile Settings

Locate your Autopilot API key by navigating to My Account > Autopilot API > Generate and copying the generated key.

Follow the procedure below to install the required modules and start accessing Autopilot through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize Autopilot Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Autopilot data.

engine = create_engine("api:///?Profile=C:\profiles\Autopilot.apip&ProfileSettings='APIKey=your_api_key'")

Execute SQL to Autopilot

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT At, BusinessName FROM Account WHERE Email = '[email protected]'", engine)

Visualize Autopilot Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Autopilot data. The show method displays the chart in a new window.

df.plot(kind="bar", x="At", y="BusinessName")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Autopilot data. Reach out to our Support Team if you have any questions.

Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("api:///?Profile=C:\profiles\Autopilot.apip&ProfileSettings='APIKey=your_api_key'")
df = pandas.read_sql("SELECT At, BusinessName FROM Account WHERE Email = '[email protected]'", engine)

df.plot(kind="bar", x="At", y="BusinessName")
plt.show()