Use pandas to Visualize Exact Online Data in Python

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Exact Online Python Connector

Python Connector Libraries for Exact Online Data Connectivity. Integrate Exact Online with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

The CData Python Connector for Exact Online enables you use pandas and other modules to analyze and visualize live Exact Online data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Exact Online, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Exact Online-connected Python applications and scripts for visualizing Exact Online data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Exact 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 Exact Online data in Python. When you issue complex SQL queries from Exact Online, the driver pushes supported SQL operations, like filters and aggregations, directly to Exact Online and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Exact Online Data

Connecting to Exact 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.

Exact Online uses the OAuth authentication standard. You can use the embedded OAuth credentials or you can register an OAuth app with Exact to obtain your own. In addition to the OAuth values, provide the Region. If Division is not set, the default Division is determined.

See the "Getting Started" chapter of the help documentation for more information.

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

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

engine = create_engine("exactonline:///?Region='United States'&Division=5512&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Exact 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 Name, CreditLinePurchase FROM Accounts WHERE IsCompetitor = 'False'", engine)

Visualize Exact Online Data

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

df.plot(kind="bar", x="Name", y="CreditLinePurchase")

Free Trial & More Information

Download a free, 30-day trial of the Exact Online Python Connector to start building Python apps and scripts with connectivity to Exact 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("exactonline:///?Region='United States'&Division=5512&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Name, CreditLinePurchase FROM Accounts WHERE IsCompetitor = 'False'", engine)

df.plot(kind="bar", x="Name", y="CreditLinePurchase")