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

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

Connecting to JobNimbus Data

Connecting to JobNimbus 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

JobNimbus uses API key authentication to control access to the API. To obtain a JobNimbus API key:

1. Log in to your JobNimbus account.
2. Navigate to Settings > Integrations > API.
3. Generate or copy your existing API key from this page.

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 JobNimbus API key.

Example Connection String

Profile=C:\profiles\JobNimbus.apip;AuthScheme=APIKey;ProfileSettings='APIKey=my_api_key';

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

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

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

Execute SQL to JobNimbus

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 AccountUsers WHERE = ''", engine)

Visualize JobNimbus Data

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

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

👁 JobNimbus 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 JobNimbus 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\JobNimbus.apip&AuthScheme=APIKey&ProfileSettings='APIKey=my_api_key'")
df = pandas.read_sql("SELECT , FROM AccountUsers WHERE = ''", engine)

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