How to Visualize Freshteam Data in Python with pandas

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use pandas and other modules to analyze and visualize live Freshteam data in Python.

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

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

Connecting to Freshteam Data

Connecting to Freshteam 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 Freshteam Profile on disk (e.g. C:\profiles\Freshteam.apip). Next, set the ProfileSettings connection property to the connection string for Freshteam (see below).

Freshteam API Profile Settings

Find your API Key in the top-right corner of your Freshteam account under the API Key section. Your AccountName is the subdomain of your Freshteam URL.

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

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

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

Execute SQL to Freshteam

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 Branches WHERE MainOffice = 'true'", engine)

Visualize Freshteam Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Freshteam 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 Freshteam 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\Freshteam.apip&ProfileSettings='APIKey=your_api_key&AccountName=your_account_name'")
df = pandas.read_sql("SELECT Id, Name FROM Branches WHERE MainOffice = 'true'", engine)

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

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