Use pandas to Visualize Twitter Ads Data in Python

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Twitter Ads Python Connector

Python Connector Libraries for Twitter Ads Data Connectivity. Integrate Twitter Ads with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for Twitter Ads enables you use pandas and other modules to analyze and visualize live Twitter Ads data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Twitter Ads, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Twitter Ads-connected Python applications and scripts for visualizing Twitter Ads data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Twitter Ads data, execute queries, and visualize the results.

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

Connecting to Twitter Ads Data

Connecting to Twitter Ads 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.

All tables require authentication. You must use OAuth to authenticate with Twitter. OAuth requires the authenticating user to interact with Twitter using the browser. For more information, refer to the OAuth section in the Help documentation.

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

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

engine = create_engine("twitterads:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Twitter Ads

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

df = pandas.read_sql("SELECT EntityId, Entity FROM AdStats WHERE Entity = 'ORGANIC_TWEET'", engine)

Visualize Twitter Ads Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Twitter Ads Python Connector to start building Python apps and scripts with connectivity to Twitter Ads 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("twitterads:///?InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT EntityId, Entity FROM AdStats WHERE Entity = 'ORGANIC_TWEET'", engine)

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