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

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

Connecting to PDFMonkey Data

Connecting to PDFMonkey 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.

Using API Key Authentication

PdfMonkey uses API key authentication. To obtain an API key:

1. Log in to your PdfMonkey account at https://app.pdfmonkey.io
2. Navigate to your account settings
3. Open the API Key page
4. Copy your API key

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your PdfMonkey API key.

Example Connection String

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

Connecting to PdfMonkey

Once the authentication is configured, you can connect to PdfMonkey and query data from any of the available tables such as CurrentUser, DocumentCards, Documents, DocumentTemplateCards, and DocumentTemplates.

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

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

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

Execute SQL to PDFMonkey

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 CurrentUser WHERE = ''", engine)

Visualize PDFMonkey Data

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

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

👁 PDFMonkey data in a Python plot (Salesforce is shown).

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 PDFMonkey data. Reach out to our Support Team if you have any questions.

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Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("api:///?Profile=C:\profiles\PdfMonkey.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_api_key"")
df = pandas.read_sql("SELECT , FROM CurrentUser WHERE = ''", engine)

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