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

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

Connecting to Salesloft Data

Connecting to Salesloft 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.

SalesLoft authenticates using the OAuth authentication standard or an API Key. OAuth requires the authenticating user to interact with SalesLoft using the browser.

Using OAuth

For OAuth authentication, create an OAuth app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the OAuth section in the Help documentation for an authentication guide.

Using APIKey

Alternatively, you can authenticate with an APIKey. Provision an API key from the SalesLoft user interface: https://accounts.salesloft.com/oauth/applications/. You will receive a Key which will be used when issuing requests.

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

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

engine = create_engine("salesloft:///?AuthScheme=OAuth&OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackUrl=http://localhost:33333&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Salesloft

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

df = pandas.read_sql("SELECT Id, Name FROM Accounts WHERE Country = 'Canada'", engine)

Visualize Salesloft Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Salesloft to start building Python apps and scripts with connectivity to Salesloft data. Reach out to our Support Team if you have any questions.

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Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("salesloft:///?AuthScheme=OAuth&OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackUrl=http://localhost:33333&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, Name FROM Accounts WHERE Country = 'Canada'", engine)

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