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

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

Connecting to Deel Data

Connecting to Deel 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 authenticate to Deel, you can use API Key (Bearer Token) authentication.

Using APIKey Authentication

You can authenticate using a Deel API Key. Create an API key in your Deel account settings under Settings > API or Developer Settings. Make sure to grant appropriate permissions based on the data you need to access (e.g., read access for invoices, timesheets, contracts, workers, etc.).

After creating your API Key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Deel API Key (Bearer token).

Example APIKey connection string

Profile=C:\profiles\Deel.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_deel_api_key';

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

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

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

Execute SQL to Deel

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 Invoices WHERE  = ''", engine)

Visualize Deel Data

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

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