Ready to get started?

Learn more about the CData Python Connector for Sybase or download a free trial:

Download Now

Use pandas to Visualize Sybase Data in Python

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

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

Connecting to Sybase Data

Connecting to Sybase 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 authenticate with Sybase, set User and Password. Additionally, set IntegratedSecurity; to true to use Windows authentication otherwise, Sybase authentication is used. Set the Server and Database properties. To secure connections with TLS/SSL, set Encrypt to true.

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

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

engine = create_engine("sybase:///?User=myuser&Password=mypassword&Server=localhost&Database=mydatabase")

Execute SQL to Sybase

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, ProductName FROM Products WHERE ProductName = 'Konbu'", engine)

Visualize Sybase Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the Sybase Python Connector to start building Python apps and scripts with connectivity to Sybase 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("sybase:///?User=myuser&Password=mypassword&Server=localhost&Database=mydatabase")
df = pandas.read_sql("SELECT Id, ProductName FROM Products WHERE ProductName = 'Konbu'", engine)

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