How to preprocess data in a data table? (e.g. change a value in each row for some feature) I Have a general question - how to preprocess data in Orange. E.g. I want to do something with each row value of some feature. How can I do this visually? And how can I do this via Python Script?

So far, I have only some ideas how to do this via python script:

Here is my code:

minimum = min(list(map(lambda row: row[0], in_data))).value

from copy import deepcopy
out_data = deepcopy(in_data)

for row in out_data:
    row[0].value = row[0].value - minimum


But it fails, because seems like the Value object is immutable... 
Is there any way to create my own Value object with new data, and then do something like:

out_data = list(map(lambda row: Value(row[0].variable, [row[0].value - minimum]) + row[1:], in_data))


I am also interested in a "Visual widget-based" alternative, if it exists...
To scale the data, you can use Preprocess widget. To construct new features, e.g.

new_feature = old_feature - some_values


you can use Feature Constructor widget.