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Home/ Questions/Q 870613
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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T10:30:21+00:00 2026-05-15T10:30:21+00:00

The following example shows what I want to do: >>> test rec.array([(0, 0, 0),

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The following example shows what I want to do:

>>> test
rec.array([(0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0),
   (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0)], 
  dtype=[('ifAction', '|i1'), ('ifDocu', '|i1'), ('ifComedy', '|i1')])

>>> test[['ifAction', 'ifDocu']][0]
(0, 0)

>>> test[['ifAction', 'ifDocu']][0] = (1,1)
>>> test[['ifAction', 'ifDocu']][0]
(0, 0)

So, I want to assign the values (1,1) to test[['ifAction', 'ifDocu']][0]. (Eventually, I want to do something like test[['ifAction', 'ifDocu']][0:10] = (1,1), assigning the same values for for 0:10. I have tried many ways but never succeeded. Is there any way to do this?

Thank you,
Joon

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1 Answer

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  1. Editorial Team
    Editorial Team
    2026-05-15T10:30:22+00:00Added an answer on May 15, 2026 at 10:30 am

    When you say test['ifAction'] you get a view of the data.
    When you say test[['ifAction','ifDocu']] you are using fancy-indexing and thus get a copy of the data. The copy doesn’t help you since modifying the copy leaves the original data unchanged.

    So a way around this is to assign values to test['ifAction'] and test['ifDocu'] individually:

    test['ifAction'][0]=1
    test['ifDocu'][0]=1
    

    For example:

    import numpy as np
    test=np.rec.array([(0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0),
       (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0)], 
      dtype=[('ifAction', '|i1'), ('ifDocu', '|i1'), ('ifComedy', '|i1')])
    
    print(test[['ifAction','ifDocu']])
    # [(0, 0) (0, 0) (0, 0) (0, 0) (0, 0) (0, 0) (0, 0) (0, 0) (0, 0) (0, 0)]
    test['ifAction'][0]=1
    test['ifDocu'][0]=1
    
    print(test[['ifAction','ifDocu']][0])
    # (1, 1)
    test['ifAction'][0:10]=1
    test['ifDocu'][0:10]=1
    
    print(test[['ifAction','ifDocu']])
    # [(1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1)]
    

    For a deeper look under the hood, see this post by Robert Kern .

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