How to Visualize Sybase IQ 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 Sybase IQ, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Sybase IQ-connected Python applications and scripts for visualizing Sybase IQ data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Sybase IQ 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 IQ data in Python. When you issue complex SQL queries from Sybase IQ, the driver pushes supported SQL operations, like filters and aggregations, directly to Sybase IQ and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Sybase IQ Data

Connecting to Sybase IQ 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 connect to SybaseIQ, set User, Password, Server and Database properties. To secure connections with TLS/SSL, set UseSSL to TRUE.

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

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

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

Execute SQL to Sybase IQ

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

df = pandas.read_sql("SELECT ProductName, Price FROM Products WHERE ProductName = 'Konbu'", engine)

Visualize Sybase IQ Data

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

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

Free Trial & More Information

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

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