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

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

Connecting to Reply.io Data

Connecting to Reply.io 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 Reply.io API uses API Key authentication via the x-api-key request header.

Using API Key Authentication

Your Reply.io API key is required to create a connection. To obtain your API key:

1. Log into your Reply.io account.
2. Click your profile icon and select Settings.
3. Navigate to the API section.
4. Copy your API Key.

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Reply.io API key.
• UserEmail (optional): Set this to the email address of the Reply.io user on whose behalf requests are made.

Example connection string:

Profile=C:\profiles\ReplyIO.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';

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

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

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

Execute SQL to Reply.io

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 BillingInfo WHERE = ''", engine)

Visualize Reply.io Data

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

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

👁 Reply.io 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 Reply.io 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\ReplyIO.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_api_key'")
df = pandas.read_sql("SELECT , FROM BillingInfo WHERE = ''", engine)

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