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Use pandas to Visualize SAP Fieldglass Data in Python

The CData Python Connector for SAP Fieldglass enables you use pandas and other modules to analyze and visualize live SAP Fieldglass 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 Fieldglass, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build SAP Fieldglass-connected Python applications and scripts for visualizing SAP Fieldglass data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to SAP Fieldglass 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 Fieldglass data in Python. When you issue complex SQL queries from SAP Fieldglass, the driver pushes supported SQL operations, like filters and aggregations, directly to SAP Fieldglass and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to SAP Fieldglass Data

Connecting to SAP Fieldglass 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, you will need to specify the Username, Password, APIKey, and EnvironmentURL connection properties.

To obtain an APIKey, log in to the SAP API Business Hub and click on Get API Key.

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

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

engine = create_engine("sapfieldglass:///?EnvironmentURL='https://myinstance.com'&Username=myuser&Password=mypassword&APIKey=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

Execute SQL to SAP Fieldglass

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, Category FROM AuditTrails WHERE Company = 'CData'", engine)

Visualize SAP Fieldglass Data

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

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

Free Trial & More Information

Download a free, 30-day trial of the SAP Fieldglass Python Connector to start building Python apps and scripts with connectivity to SAP Fieldglass 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("sapfieldglass:///?EnvironmentURL='https://myinstance.com'&Username=myuser&Password=mypassword&APIKey=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx&InitiateOAuth=GETANDREFRESH&OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")
df = pandas.read_sql("SELECT Id, Category FROM AuditTrails WHERE Company = 'CData'", engine)

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