Greetings so I have a pandas DataFrame which looks like this:
Product_Code W0 W1 W2 W3 W4 W5 W6 W7 W8 ... \
806 P815 0 0 1 0 0 2 1 0 0 ...
807 P816 0 1 0 0 1 2 2 6 0 ...
808 P817 1 0 0 0 1 1 2 1 1 ...
809 P818 0 0 0 1 0 0 0 0 1 ...
810 P819 0 1 0 0 0 0 0 0 0 ...
Normalized 42 Normalized 43 Normalized 44 Normalized 45 \
806 0.00 0.33 0.33 0.00
807 0.43 0.43 0.57 0.29
808 0.50 0.00 0.00 0.50
809 0.00 0.00 0.00 0.50
810 0.00 0.00 0.00 0.00
but I don't need these columns as a matter of fact I need only W0 and W4, So I wanna remove all of them so this is what I tried:
raw_data = [ raw_data.drop( [i], 1, inplace = True ) for i in raw_data if i is not 'W0' and i is not 'W4' ]
after half an hour I figured out that for some reason that != does not work strings and I was wondering why? so I have a stable solution:
#WORKS !!!!
# for i in raw_data:
# if i != 'W0' and i != 'W4':
# raw_data.drop( [i], 1, inplace = True )
But I don't like it at all and I have commented it because it takes a lot of space and it's not beautiful, I want to make the one-line loop if expression to work, is it possible, the problem is that:
raw_data = [ raw_data.drop( [i], 1, inplace = True ) for i in raw_data if i != 'W0' and i != 'W4' ]
tries to convert the DataFrame to a list, how should it be done?
You can use:
raw_data.drop([i for i in raw_data if i is not 'W0' and i is not 'W4'],
axis=1, inplace=True)
This answers the question but the condition that you state doesn't make sense. The condition you have put is if i is not 'W0' and i is not 'W4', this is going to be true always. You probably need to look at the condition again.
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