How to Visualize Amazon DynamoDB 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 Python Connector for Amazon DynamoDB, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Amazon DynamoDB-connected Python applications and scripts for visualizing Amazon DynamoDB data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Amazon DynamoDB data, execute queries, and visualize the results.

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

Connecting to Amazon DynamoDB Data

Connecting to Amazon DynamoDB 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 connection to Amazon DynamoDB is made using your AccessKey, SecretKey, and optionally your Domain and Region. Your AccessKey and SecretKey can be obtained on the security credentials page for your Amazon Web Services account. Your Region will be displayed in the upper left-hand corner when you are logged into DynamoDB.

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

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

engine = create_engine("amazondynamodb:///?Access Key=xxx&Secret Key=xxx&Domain=amazonaws.com&Region=OREGON")

Execute SQL to Amazon DynamoDB

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

df = pandas.read_sql("SELECT Industry, Revenue FROM Lead WHERE FirstName = 'Bob'", engine)

Visualize Amazon DynamoDB Data

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

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

👁 Amazon DynamoDB data in a Python plot (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Amazon DynamoDB to start building Python apps and scripts with connectivity to Amazon DynamoDB 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("amazondynamodb:///?Access Key=xxx&Secret Key=xxx&Domain=amazonaws.com&Region=OREGON")
df = pandas.read_sql("SELECT Industry, Revenue FROM Lead WHERE FirstName = 'Bob'", engine)

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