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

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

Connecting to Superchat Data

Connecting to Superchat 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.

Superchat uses API Key authentication. The API key is passed via the X-API-KEY request header on every call.

Authentication

To authenticate to Superchat, you need to obtain your API key from the Superchat workspace settings.

Using API Key Authentication

You can obtain your API key from Settings > Integrations > API Key in your Superchat workspace.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Superchat API key.

Example connection string:

Profile=C:\profiles\Superchat.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';

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

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

engine = create_engine("api:///?Profile=C:\profiles\Superchat.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_api_key'")

Execute SQL to Superchat

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

df = pandas.read_sql("SELECT ,  FROM Channels WHERE  = ''", engine)

Visualize Superchat Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Superchat 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("api:///?Profile=C:\profiles\Superchat.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_api_key'")
df = pandas.read_sql("SELECT ,  FROM Channels WHERE  = ''", engine)

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