How to Visualize Klipfolio 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 Klipfolio-connected Python applications and scripts for visualizing Klipfolio data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Klipfolio data, execute queries, and visualize the results.

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

Connecting to Klipfolio Data

Connecting to Klipfolio 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.

Start by setting the Profile connection property to the location of the Klipfolio Profile on disk (e.g. C:\profiles\Klipfolio.apip). Next, set the ProfileSettings connection property to the connection string for Klipfolio (see below).

Klipfolio API Profile Settings

In order to authenticate to Klipfolio, you'll need to provide your API Key. You can generate an API key from the Klipfolio Dashboard app through either the My Profile page or from Users if you are an administrator (you must have the user.manage permission). Set the API Key in the ProfileSettings property to connect.

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

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

engine = create_engine("api:///?Profile=C:\profiles\Klipfolio.apip&ProfileSettings='APIKey=your_api_key'")

Execute SQL to Klipfolio

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, Name FROM DataSources WHERE IsDynamic = 'true'", engine)

Visualize Klipfolio Data

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

df.plot(kind="bar", x="Id", y="Name")
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 Klipfolio 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\Klipfolio.apip&ProfileSettings='APIKey=your_api_key'")
df = pandas.read_sql("SELECT Id, Name FROM DataSources WHERE IsDynamic = 'true'", engine)

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