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Use pandas to Visualize NetSuite Data in Python

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

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

Connecting to NetSuite Data

Connecting to NetSuite 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.

The User and Password properties, under the Authentication section, must be set to valid NetSuite user credentials. In addition, the AccountId must be set to the ID of a company account that can be used by the specified User. The RoleId can be optionally specified to log in the user with limited permissions.

See the "Getting Started" chapter of the help documentation for more information on connecting to NetSuite.

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

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

engine = create_engine("netsuite:///?Account Id=XABC123456&Password=password&User=user&Role Id=3&Version=2013_1")

Execute SQL to NetSuite

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

df = pandas.read_sql("SELECT CustomerName, SalesOrderTotal FROM SalesOrder WHERE Class_Name = 'Furniture : Office'", engine)

Visualize NetSuite Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the NetSuite Python Connector to start building Python apps and scripts with connectivity to NetSuite 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("netsuite:///?Account Id=XABC123456&Password=password&User=user&Role Id=3&Version=2013_1")
df = pandas.read_sql("SELECT CustomerName, SalesOrderTotal FROM SalesOrder WHERE Class_Name = 'Furniture : Office'", engine)

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