Getting raw GC-MS data (abundance matrix) from .D folders into python

I'm in a startup working with a research institution and they have given me .D folders, which is the 'raw data' from an Agilent GC-MS machines.
I want to run Deep learning models on the raw data. First, I will take the 2D vector and create a 3D plot (RT, M/Z, intensity). Then, I will use image classification techniques to try to classify the sample. 
I have a few questions:  
  • Do .D folders contain the raw GC-MS data (RT, M/Z), also known as an abundance matrix?
    • If so, which sub-folder is it?
    • I want the raw 2D vector of data.
  • How do I import these files into python?
    • Could you direct me to any resources or explain how to extract the data from the .D file and bring it into python?
    • I want to run Deep Learning models on
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