在每一列上执行操作

Question

How can a loop be used to iterate through columns, applying the same function to each column in a pandas dataframe?

For example, the following code normalizes the 'Cat1' Column.

s['Cat1'] = (s.Cat1-s.Cat1.min())/(s.Cat1.max()-s.Cat1.min())

How can this code be extended so that the normalization is applied to Cat1...Cat50?

Answer 1

Assuming s is a dictionary, the term s.Cat1 doesn't make any sense.

If s is a class, then now s['Cat1'] doesn't make any sense because class has no attribute __getitem__

So I am not sure what s is in your example... But if you want an easy way to generate the strings 'Cat1',...,'Cat50', you can use:

for i in range(1,51):
    name = 'Cat%s' % i
    # s[name] = ...