How to Visualize Sage Intacct Data in Python with pandas via CData Connect AI
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK, the pandas and Matplotlib modules, you can build Sage Intacct-connected Python applications and scripts for visualizing Sage Intacct data. This article shows how to connect to Connect AI and use the pandas and Matplotlib built-in functions to query Sage Intacct data and visualize the results.
The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source and no SQLAlchemy engine to configure: connect with a Personal Access Token and pass the connection straight to pandas.read_sql.
About Sage Intacct Data Integration
CData provides the easiest way to access and integrate live data from Sage Intact. Customers use CData connectivity to:
- Access Sage Intacct without worrying about API updates or changes.
- Access custom objects and fields in Sage Intacct with no extra configuration steps involved.
- Write data back to Sage Intacct using embedded Web Services credentials with Basic authentication.
- Use SQL stored procedures to perform functional operations like approving or declining vendors, inserting engagements, and creating or deleting custom objects or fields.
Users frequently integrate Sage Intact with analytics tools such as Tableau, Power BI, and Excel, and leverage our tools to replicate Workday data to databases or data warehouses.
To learn about how other customers are using CData's Sage Intacct solutions, check out our blog: Drivers in Focus: Accounting Connectivity.
Getting Started
Connect to Sage Intacct in Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Sage Intacct" from the Add Connection panel
-
Enter the necessary authentication properties to connect to Sage Intacct.
To connect using the Login method, the following connection properties are required: User, Password, CompanyId, SenderId and SenderPassword.
User, Password, and CompanyId are the credentials for the account you wish to connect to.
SenderId and SenderPassword are the Web Services credentials assigned to you by Sage Intacct.
- Click Save & Test
- Navigate to the Permissions tab and update the user-based permissions.
Generate a Personal Access Token (PAT)
The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.
- Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
- Give the PAT a name and click Create.
- The PAT is only visible at creation, so copy it and store it securely.
Install Required Modules
Install the SDK (with the pandas extra) and Matplotlib using the pip utility:
pip install "cdata-connect-ai[full]" pip install matplotlib
Visualize Sage Intacct Data in Python
Import the modules, then connect to Connect AI with your account email and PAT. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, SageIntacct1).
import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
Query Sage Intacct with pandas
Use the read_sql function from pandas to execute a SQL statement and store the result set in a DataFrame. Pass the SDK connection directly, no engine required.
df = pandas.read_sql(
"SELECT Name, TotalDue "
"FROM [SageIntacct1].[SageIntacct].[Customer] "
"WHERE CustomerId = '12345'",
conn,
)
Note: pandas may print a UserWarning stating that it only officially supports SQLAlchemy connectables. This is expected when passing a DB-API connection directly—the query runs correctly and the warning is safe to ignore.
Visualize Sage Intacct Data
With the query results stored in a DataFrame, use the plot function to build a chart. The show method displays the chart in a new window.
df.plot(kind="bar", x="Name", y="TotalDue") plt.show() conn.close()
More Information and Free Trial
Now you can read live Sage Intacct data into pandas through the CData Connect AI Python SDK. For more information on connecting to Sage Intacct (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Sage Intacct data in Python.
Full Source Code
import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
df = pandas.read_sql(
"SELECT Name, TotalDue "
"FROM [SageIntacct1].[SageIntacct].[Customer] "
"WHERE CustomerId = '12345'",
conn,
)
df.plot(kind="bar", x="Name", y="TotalDue")
plt.show()
conn.close()