How to Visualize QuickBooks Online 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 Python Connector for QuickBooks Online, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build QuickBooks Online-connected Python applications and scripts for visualizing QuickBooks Online data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to QuickBooks Online data, execute queries, and visualize the results.

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

Getting Started

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Connecting to QuickBooks Online Data

Connecting to QuickBooks Online 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.

QuickBooks Online uses the OAuth authentication standard. OAuth requires the authenticating user to log in through the browser. To authenticate using OAuth, you can use the embedded OAuthClientId, OAuthClientSecret, and CallbackURL or you can obtain your own by registering an app with Intuit. Additionally, if you want to connect to sandbox data, set UseSandbox to true.

See the Getting Started chapter of the help documentation for a guide to using OAuth.

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

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

engine = create_engine("quickbooksonline:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to QuickBooks Online

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

df = pandas.read_sql("SELECT DisplayName, Balance FROM Customers WHERE FullyQualifiedName = 'Cook, Brian'", engine)

Visualize QuickBooks Online Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for QuickBooks Online to start building Python apps and scripts with connectivity to QuickBooks Online 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("quickbooksonline:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT DisplayName, Balance FROM Customers WHERE FullyQualifiedName = 'Cook, Brian'", engine)

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