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Use pandas to Visualize Data in Python

The CData Python Connector for enables you use pandas and other modules to analyze and visualize live data in Python.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for , the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build -connected Python applications and scripts for visualizing data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to data, execute queries, and visualize the results.

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

Connecting to Data

Connecting to 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.

The primary method for performing basic authentication is to provide your login credentials, as follows:

  • User: Set this to your username.
  • Password: Set this to your password.

Optionally, if you are making use of a sandbox environment, set the following:

  • UseSandbox: Set this to true if you are authenticating with a sandbox account.

Authenticating Using Account Number and License Key

Alternatively, you can authenticate using your account number and license key. Connect to data using the following:

  • AccountId: Set this to your Account Id. The Account Id is listed in the upper right hand corner of the admin console.
  • LicenseKey: Set this to your Avalara Avatax license key. You can generate a license key by logging into Avalara Avatax as an account adminstrator and navigating to Settings -> Reset License Key.

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

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

engine = create_engine("avalaraavatax:///?User=MyUser&Password=MyPassword")

Execute SQL to

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, TotalTax FROM Transactions WHERE Code = '051349'", engine)

Visualize Data

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

df.plot(kind="bar", x="Id", y="TotalTax")

Free Trial & More Information

Download a free, 30-day trial of the Python Connector to start building Python apps and scripts with connectivity to 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("avalaraavatax:///?User=MyUser&Password=MyPassword")
df = pandas.read_sql("SELECT Id, TotalTax FROM Transactions WHERE Code = '051349'", engine)

df.plot(kind="bar", x="Id", y="TotalTax")