How to Visualize Cvent 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 Cvent-connected Python applications and scripts for visualizing Cvent data. This article shows how to connect to Connect AI and use the pandas and Matplotlib built-in functions to query Cvent 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.

Connect to Cvent in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Cvent" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Cvent.

   Before you can authenticate to Cvent, you must create a workspace and an OAuth application.

   Creating a Workspace

   To create a workspace:

   1. Sign into Cvent and navigate to App Switcher (the blue button in the upper right corner of the page) >> Admin.
   2. In the Admin menu, navigate to Integrations >> REST API.
   3. A new tab launches for Developer Management. Click on Manage API Access in the new tab.
   4. Create a Workspace and name it. Select the scopes you would like your developers to have access to. Scopes control what data domains the developer can access.
      • Choose All to allow developers to choose any scope, and any future scopes added to the REST API.
      • Choose Custom to limit the scopes developers can choose for their OAuth apps to selected scopes. To access all tables exposed by the driver, you need to set the following scopes:

        event/attendees:read	event/attendees:write	event/contacts:read
        event/contacts:write	event/custom-fields:read	event/custom-fields:write
        event/events:read	event/events:write	event/sessions:delete
        event/sessions:read	event/sessions:write	event/speakers:delete
        event/speakers:read	event/speakers:write	budget/budget-items:read
        budget/budget-items:write	exhibitor/exhibitors:read	exhibitor/exhibitors:write
        survey/surveys:read	survey/surveys:write

   Creating an OAuth Application

   After you have set up a Workspace and invited them, developers can sign up and create a custom OAuth app. See the Creating a Custom OAuth Application section in the Help documentation for more information.

   Connecting to Cvent

   After creating an OAuth application, set the following connection properties to connect to Cvent:

   • InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
   • OAuthClientId: The Client ID associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
   • OAuthClientSecret: The Client secret associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
   
4. Click Save & Test
5. 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.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. 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 Cvent 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, Cvent1).

import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

Query Cvent 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 Id, Title "
    "FROM [Cvent1].[Cvent].[Events] "
    "WHERE Virtual = 'true'",
    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 Cvent 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="Id", y="Title")
plt.show()

conn.close()

More Information and Free Trial

Now you can read live Cvent data into pandas through the CData Connect AI Python SDK. For more information on connecting to Cvent (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Cvent 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 Id, Title "
    "FROM [Cvent1].[Cvent].[Events] "
    "WHERE Virtual = 'true'",
    conn,
)

df.plot(kind="bar", x="Id", y="Title")
plt.show()

conn.close()