Use pandas to Visualize Plaid Data in Python

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Plaid Python Connector

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



The CData Python Connector for Plaid enables you use pandas and other modules to analyze and visualize live Plaid 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 Plaid, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Plaid-connected Python applications and scripts for visualizing Plaid data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Plaid data, execute queries, and visualize the results.

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

Connecting to Plaid Data

Connecting to Plaid 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.

You can connect to Plaid using the embedded OAuth connectivity. When you connect, the Plaid OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

Optionally set the Account Id property to return data related to a specific Account.

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

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

engine = create_engine("plaid:///?AccountId=123456789&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Plaid

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

df = pandas.read_sql("SELECT AccountId, Name FROM Transactions WHERE Name = 'Apple Store'", engine)

Visualize Plaid Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Plaid Python Connector to start building Python apps and scripts with connectivity to Plaid 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("plaid:///?AccountId=123456789&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT AccountId, Name FROM Transactions WHERE Name = 'Apple Store'", engine)

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