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

How to Visualize Epicor Kinetic Data in Python with pandas

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

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

Connecting to Epicor Kinetic Data

Connecting to Epicor Kinetic 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.

To successfully connect to your ERP instance, you must specify the following connection properties:

  • Url:the URL of the server hosting your ERP instance. For example,
  • ERPInstance: the name of your ERP instance.
  • User: the username of your account.
  • Password: the password of your account.
  • Service: the service you want to retrieve data from. For example, BaqSvc.

In addition, you may also set the optional connection properties:

  • ApiKey: An optional key that may be required for connection to some services depending on your account configuration.
  • ApiVersion: Defaults to v1. May be set to v2 to use the newer Epicor API.
  • Company: Required if you set the ApiVersion to v2.

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

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

engine = create_engine("epicorkinetic:///?Service=Erp.BO.CustomerSvc&ERPInstance=MyInstance&URL=")

Execute SQL to Epicor Kinetic

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

df = pandas.read_sql("SELECT CustNum, Company FROM Customers WHERE CompanyName = 'CompanyName'", engine)

Visualize Epicor Kinetic Data

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

df.plot(kind="bar", x="CustNum", y="Company")

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Epicor Kinetic to start building Python apps and scripts with connectivity to Epicor Kinetic 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("epicorkinetic:///?Service=Erp.BO.CustomerSvc&ERPInstance=MyInstance&URL=")
df = pandas.read_sql("SELECT CustNum, Company FROM Customers WHERE CompanyName = 'CompanyName'", engine)

df.plot(kind="bar", x="CustNum", y="Company")