How to Visualize Zoho Inventory 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 Python Connector for Zoho Inventory, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Zoho Inventory-connected Python applications and scripts for visualizing Zoho Inventory data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Zoho Inventory 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 Inventory data in Python. When you issue complex SQL queries from Zoho Inventory, the driver pushes supported SQL operations, like filters and aggregations, directly to Zoho Inventory and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Zoho Inventory Data

Connecting to Zoho Inventory 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.

In order to connect to Zoho Inventory, set the following connection properties:

• OrganizationId: set this to the ID associated with your specific Zoho Inventory organization
• InitiateOAuth: set the to "GETANDREFRESH"
• AccountsServer (Optional): set this full Account Server URL (only when manually refreshing the OAuth token)

The connectors use OAuth to authenticate with Zoho Inventory. For more information, refer to the Getting Started section of the Help documentation.

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

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

engine = create_engine("zohoinventory:///?OrganizationId=YourOrganizationId&AccountsServer=YourAccountServerURL&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to Zoho Inventory

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

df = pandas.read_sql("SELECT Id, CustomerName FROM Contacts WHERE FirstName = 'Katherine'", engine)

Visualize Zoho Inventory Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Zoho Inventory to start building Python apps and scripts with connectivity to Zoho Inventory 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("zohoinventory:///?OrganizationId=YourOrganizationId&AccountsServer=YourAccountServerURL&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, CustomerName FROM Contacts WHERE FirstName = 'Katherine'", engine)

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