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Use pandas to Visualize Zoho Books Data in Python

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

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

Connecting to Zoho Books Data

Connecting to Zoho Books 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.

Zoho Books uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the OAuth section of the Getting Started guide in the Help documentation for an authentication guide.

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

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

engine = create_engine("zohobooks:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=myOAuthClientSecret&CallbackURL=https://localhost:33333&OrganizationId=MyOrganizationId&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Zoho Books

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

df = pandas.read_sql("SELECT InvoiceId, InvoiceNumber FROM INVOICES WHERE CustomerName = 'NewTech Industries'", engine)

Visualize Zoho Books Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Zoho Books Python Connector to start building Python apps and scripts with connectivity to Zoho Books 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("zohobooks:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=myOAuthClientSecret&CallbackURL=https://localhost:33333&OrganizationId=MyOrganizationId&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT InvoiceId, InvoiceNumber FROM INVOICES WHERE CustomerName = 'NewTech Industries'", engine)

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