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Use pandas to Visualize SAP HANA Data in Python

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

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

Connecting to SAP HANA Data

Connecting to SAP HANA 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.

Set the Server, Database and Port properties to specify the address of your SAP Hana database to interact with. Set the User and the Password properties to authenticate to the server.

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

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

engine = create_engine("saphana:///?User=system&Password=mypassword&Server=localhost&Database=systemdb")

Execute SQL to SAP HANA

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

df = pandas.read_sql("SELECT Name, OwnerId FROM Buckets WHERE Name = 'TestBucket'", engine)

Visualize SAP HANA Data

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

df.plot(kind="bar", x="Name", y="OwnerId")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the SAP HANA Python Connector to start building Python apps and scripts with connectivity to SAP HANA 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("saphana:///?User=system&Password=mypassword&Server=localhost&Database=systemdb")
df = pandas.read_sql("SELECT Name, OwnerId FROM Buckets WHERE Name = 'TestBucket'", engine)

df.plot(kind="bar", x="Name", y="OwnerId")
plt.show()