Use pandas to Visualize SAP Concur Data in Python

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

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

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

Connecting to SAP Concur Data

Connecting to SAP Concur 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.

SAP Concur uses the OAuth 2 authentication standard. You will need to obtain the OAuthClientId and OAuthClientSecret by registering an app with SAP Concur. See the Getting Started section of the help documentation for an authentication guide.

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

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

engine = create_engine("sapconcur:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to SAP Concur

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, OfficeId FROM Departments WHERE Id = '1668776136772254'", engine)

Visualize SAP Concur Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the SAP Concur Python Connector to start building Python apps and scripts with connectivity to SAP Concur 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("sapconcur:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, OfficeId FROM Departments WHERE Id = '1668776136772254'", engine)

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