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

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

Connecting to Sage Cloud Accounting Data

Connecting to Sage Cloud Accounting 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.

You can connect to Sage Business Cloud Accounting using the embedded OAuth connectivity. When you connect, the OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

Follow the procedure below to install the required modules and start accessing Sage Cloud Accounting 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 Sage Cloud Accounting Data in Python

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

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

Execute SQL to Sage Cloud Accounting

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

df = pandas.read_sql("SELECT contact_name, total_amount FROM SalesInvoices WHERE sent = 'TRUE'", engine)

Visualize Sage Cloud Accounting Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Sage Cloud Accounting to start building Python apps and scripts with connectivity to Sage Cloud Accounting 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("sagebcaccounting:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT contact_name, total_amount FROM SalesInvoices WHERE sent = 'TRUE'", engine)

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