How to Visualize ElevenLabs 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 ElevenLabs-connected Python applications and scripts for visualizing ElevenLabs data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to ElevenLabs data, execute queries, and visualize the results.

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

Connecting to ElevenLabs Data

Connecting to ElevenLabs 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.

To authenticate to ElevenLabs, and connect to your own data or to allow other users to connect to their data, you can use API Key authentication.

Authentication

To authenticate to ElevenLabs, and connect to your own data or to allow other users to connect to their data, you can use API Key authentication.

Using API Key Authentication

To authenticate using an API Key, you need to obtain your API Key from your ElevenLabs account settings.

You can then connect by setting the AuthScheme to APIKey and providing your API key:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your API key from ElevenLabs.

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

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

engine = create_engine("api:///?Profile=C:\profiles\Elevenlabs.apip&AuthScheme=APIKey&APIKey=your_api_key_here")

Execute SQL to ElevenLabs

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 AgentBranches WHERE AgentId = 'agent_01234567890'", engine)

Visualize ElevenLabs Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the ElevenLabs 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 ElevenLabs 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\Elevenlabs.apip&AuthScheme=APIKey&APIKey=your_api_key_here")
df = pandas.read_sql("SELECT ,  FROM AgentBranches WHERE AgentId = 'agent_01234567890'", engine)

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