Another way of using np.where() !?

Question

Hi everyone,

Since I want to substitute every number of 2000 with number 20 in Lending-Company-Numeric-Data-NAN, used in this video. I wonder the following code would work properly or not:

import_numeric_NAN_csv = np.genfromtxt('Lending-Company-Numeric-Data-NAN.csv', delimiter = ';')
import_numeric_NAN_csv = np.where(import_numeric_NAN_csv[:, :] == 2000, 20, import_numeric_NAN_csv[:, :])

After running the code above, I see only number 20 without any 2000 anymore, and the quantitative of nan values are still the same. But does it work properly? Any advice?
Thanks!

Answer 1

Hi,

That's because you set you whole data equal to 2000 as condition so to avoid that you need to spcifiy column or row

Another way of using np.where() !?

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