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

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

Connecting to Qualaroo Data

Connecting to Qualaroo 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.

Qualaroo uses HTTP Basic Authentication to control access to the API. You will need your API Key and API Secret, which can be found under Account Details > Reporting API in the Qualaroo dashboard.

Using Basic Authentication

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to Basic.
• User: Set this to your Qualaroo API Key.
• Password: Set this to your Qualaroo API Secret.

Example connection string:

Profile=C:\profiles\Qualaroo.apip;AuthScheme=Basic;User=your_api_key;Password=your_api_secret;

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

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

engine = create_engine("api:///?Profile=C:\profiles\Qualaroo.apip&AuthScheme=Basic&User=your_api_key&Password=your_api_secret")

Execute SQL to Qualaroo

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

df = pandas.read_sql("SELECT ,  FROM SurveyResponses WHERE SurveyId = '12345'", engine)

Visualize Qualaroo Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Qualaroo 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("api:///?Profile=C:\profiles\Qualaroo.apip&AuthScheme=Basic&User=your_api_key&Password=your_api_secret")
df = pandas.read_sql("SELECT ,  FROM SurveyResponses WHERE SurveyId = '12345'", engine)

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