How to Visualize Oracle SCM 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 Oracle SCM, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Oracle SCM-connected Python applications and scripts for visualizing Oracle SCM data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Oracle SCM data, execute queries, and visualize the results.

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

Connecting to Oracle SCM Data

Connecting to Oracle SCM 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 following connection properties are required to connect to Oracle SCM data.

• Url: The URL of the account that you want to connect to. Typically, this will be the URL of your Oracle Cloud service. For example, https://servername.fa.us2.oraclecloud.com.
• User: The username of your Oracle Cloud service account.
• Password: The password of your Oracle Cloud service account.

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

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

engine = create_engine("oraclescm:///?Url=https://myinstance.oraclecloud.com&User=user&Password=password")

Execute SQL to Oracle SCM

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

df = pandas.read_sql("SELECT CarrierId, CarrierName FROM Carriers WHERE ActiveFlag = 'false'", engine)

Visualize Oracle SCM Data

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

df.plot(kind="bar", x="CarrierId", y="CarrierName")
plt.show()

👁 Oracle SCM data in a Python plot (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Oracle SCM to start building Python apps and scripts with connectivity to Oracle SCM data. Reach out to our Support Team if you have any questions.

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Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("oraclescm:///?Url=https://myinstance.oraclecloud.com&User=user&Password=password")
df = pandas.read_sql("SELECT CarrierId, CarrierName FROM Carriers WHERE ActiveFlag = 'false'", engine)

df.plot(kind="bar", x="CarrierId", y="CarrierName")
plt.show()