How to Visualize Onfleet 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 Onfleet-connected Python applications and scripts for visualizing Onfleet data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Onfleet data, execute queries, and visualize the results.

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

Connecting to Onfleet Data

Connecting to Onfleet 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.

Onfleet uses HTTP ApiKey Authentication. Your Onfleet API Key is used to authenticate requests. You can generate or view your API Key in the Onfleet dashboard under Settings > API.

Using ApiKey Authentication

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Onfleet API Key.

Example connection string:

Profile=C:\profiles\Onfleet.apip;AuthScheme=APIKey;ProfileSettings="ApiKey=your_api_key";

Follow the procedure below to install the required modules and start accessing Onfleet 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 Onfleet Data in Python

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

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

Execute SQL to Onfleet

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

df = pandas.read_sql("SELECT ,  FROM Administrators WHERE  = ''", engine)

Visualize Onfleet Data

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

df.plot(kind="bar", x="", y="")
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 Onfleet 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\Onfleet.apip&AuthScheme=APIKey&ProfileSettings="ApiKey=your_api_key"")
df = pandas.read_sql("SELECT ,  FROM Administrators WHERE  = ''", engine)

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