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

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

Connecting to Deepgram Data

Connecting to Deepgram 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.

Start by setting the Profile connection property to the location of the Deepgram Profile on disk (e.g. C:\profiles\Deepgram.apip). Next, set the ProfileSettings connection property to the connection string for Deepgram (see below).

Deepgram API Profile Settings

Deepgram uses API key authentication for all endpoints. API keys are scoped to a project and carry permission scopes (member, administrator, or owner). Create and manage API keys in the Deepgram console.

After obtaining your API key, set the following connection properties:

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

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

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

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

Execute SQL to Deepgram

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

df = pandas.read_sql("SELECT ApiKeyId, MemberEmail FROM Keys WHERE ProjectId = 'your-project-id'", engine)

Visualize Deepgram Data

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

df.plot(kind="bar", x="ApiKeyId", y="MemberEmail")
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 Deepgram 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\Deepgram.apip&AuthScheme=APIKey&ProfileSettings='APIKey=YOUR_DEEPGRAM_API_KEY'")
df = pandas.read_sql("SELECT ApiKeyId, MemberEmail FROM Keys WHERE ProjectId = 'your-project-id'", engine)

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