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

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

Connecting to ConvertAPI Data

Connecting to ConvertAPI 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.

ConvertAPI uses API Secret Key authentication. Your ConvertAPI Secret is used to authenticate requests. You can find your API Secret in the ConvertAPI dashboard under your account settings.

Using APIKey Authentication

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

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your ConvertAPI API secret key.

Example connection string:

Profile=C:\profiles\ConvertAPI.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key";

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

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

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

Execute SQL to ConvertAPI

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 User WHERE  = ''", engine)

Visualize ConvertAPI Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the ConvertAPI 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 ConvertAPI 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\ConvertAPI.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_api_key"")
df = pandas.read_sql("SELECT ,  FROM User WHERE  = ''", engine)

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