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Use pandas to Visualize Blackbaud FE NXT Data in Python

The CData Python Connector for Blackbaud FE NXT enables you use pandas and other modules to analyze and visualize live Blackbaud FE NXT 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 Blackbaud FE NXT, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Blackbaud FE NXT-connected Python applications and scripts for visualizing Blackbaud FE NXT data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Blackbaud FE NXT data, execute queries, and visualize the results.

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

Connecting to Blackbaud FE NXT Data

Connecting to Blackbaud FE NXT 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.

Blackbaud Financial Edge NXT uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

See the Getting Started guide in the CData driver documentation for more information.

Follow the procedure below to install the required modules and start accessing Blackbaud FE NXT 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 Blackbaud FE NXT Data in Python

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

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

Execute SQL to Blackbaud FE NXT

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

df = pandas.read_sql("SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = 'System'", engine)

Visualize Blackbaud FE NXT Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Blackbaud FE NXT Python Connector to start building Python apps and scripts with connectivity to Blackbaud FE NXT 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("financialedgenxt:///?SubscriptionKey=MySubscriptionKey&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = 'System'", engine)

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