Azure ML Studio offers predictive analytics solutions through a drag and drop interface. It features the capability to add a Python script that would read a dataset, perform data manipulation, and then deliver the output dataset. pandas could play a crucial role in this data processing module of the Azure ML Studio:

From the flow diagram, you can see that data is fed to the Execute Python Script module. This module can receive datasets in two of the three input ports and gives a DataFrame as output in one of the two output ports.

The following diagram shows the Execute Python Script module. This module accepts only DataFrames at the input ports. It allows for further data processing steps to take place before a single DataFrame is produced as the result at the output port. This is where pandas and its numerous wonderful functions play a role: