Hi, I am new to pytorch and pandas. I come from a Matlab background.
I am trying to import a dataset in python from a .csv file and it should be quite straightforward. My .csv contains a bunch of columns (19), some of them are input features and some are output features.
What I do is the following, how can I extend this code to import multiple input and output features?
# Load the data
D = pd.read_csv("result_reorganized.csv")

x_dataset = torch.tensor(D.inputFeature1.values, dtype=torch.float)
y_dataset = torch.tensor(D.outputFeature1.values, dtype=torch.float)

In matlab I would do something like
[ x1_dataset, x2_dataset, x3_dataset] = [torch.tensor(D.inputFeature1.values, dtype=torch.float) , torch.tensor(D.inputFeature2.values, dtype=torch.float), torch.tensor(D.inputFeature3.values, dtype=torch.float)]

I can’t find so far how to do this in python/pandas.
Thanks for your help,
Fabrizio.