Use pandas to Visualize USPS Data in Python

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USPS Python Connector

Python Connector Libraries for USPS Data Connectivity. Integrate USPS with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for USPS enables you use pandas and other modules to analyze and visualize live USPS 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 USPS, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build USPS-connected Python applications and scripts for visualizing USPS data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to USPS data, execute queries, and visualize the results.

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

Connecting to USPS Data

Connecting to USPS 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 with USPS, set the following connection properties.

  • PostageProvider: The postage provider to use to process requests. Available options are ENDICIA and STAMPS. If unspecified, this property will default to ENDICIA.
  • UseSandbox: This controls whether live or test requests are sent to the production or sandbox servers. If set to true, the Password, AccountNumber, and StampsUserId properties are ignored.
  • StampsUserId: This value is used for logging into authentication to the Stamps servers. This value is not applicable for Endicia and is optional if UseSandbox is true.
  • Password: This value is used for logging into Endicia and Stamps servers. If the postage provider is Endicia, this will be the pass phrase associated with your postage account. It is optional if UseSandbox is true.
  • AccountNumber: The shipper's account number. It is optional if UseSandbox is true.
  • PrintLabelLocation: This property is required to use the GenerateLabels or GenerateReturnLabels stored procedures. This should be set to the folder location where generated labels should be stored.

The Cache Database

Many of the useful task available from USPS require a lot of data. To ensure this data is easy to input and recall later, utilize a cache database to make requests. Set the cache connection properties in order to use the cache:

  • CacheLocation: The path to the cache location, for which a connection will be configured with the default cache provider. For example, C:\users\username\documents\uspscache

As an alternative to CacheLocation, set the combination of CacheConnection and CacheProvider to configure a cache connection using a provider separate from the default.

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

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

engine = create_engine("usps:///?PostageProvider=ENDICIA& RequestId=12345& Password='abcdefghijklmnopqr'& AccountNumber='12A3B4C'")

Execute SQL to USPS

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT FirstName, Phone FROM Senders WHERE SenderID = '25'", engine)

Visualize USPS Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the USPS Python Connector to start building Python apps and scripts with connectivity to USPS 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("usps:///?PostageProvider=ENDICIA& RequestId=12345& Password='abcdefghijklmnopqr'& AccountNumber='12A3B4C'")
df = pandas.read_sql("SELECT FirstName, Phone FROM Senders WHERE SenderID = '25'", engine)

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