getting index of nan values in numpy array









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Getting the index of nan values from where condition and passing it to original array but it is returning empty



#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan


( iris_2d[np.where(iris_2d[a,b]==np.nan)])









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  • By definition nan!=nan which is why your code does not work.
    – Paul Panzer
    23 hours ago










  • thank you i know now.
    – Rajneesh Master
    22 hours ago














up vote
0
down vote

favorite












Getting the index of nan values from where condition and passing it to original array but it is returning empty



#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan


( iris_2d[np.where(iris_2d[a,b]==np.nan)])









share|improve this question























  • By definition nan!=nan which is why your code does not work.
    – Paul Panzer
    23 hours ago










  • thank you i know now.
    – Rajneesh Master
    22 hours ago












up vote
0
down vote

favorite









up vote
0
down vote

favorite











Getting the index of nan values from where condition and passing it to original array but it is returning empty



#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan


( iris_2d[np.where(iris_2d[a,b]==np.nan)])









share|improve this question















Getting the index of nan values from where condition and passing it to original array but it is returning empty



#Input
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris_2d = np.genfromtxt(url, delimiter = ',', dtype = 'float')# random number from 0 to 150 as high is none
iris_2d[np.random.randint(150, size = 20), np.random.randint(4, size = 20)] = np.nan


( iris_2d[np.where(iris_2d[a,b]==np.nan)])






python-3.x numpy






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edited 22 hours ago









Xatyrian

786320




786320










asked yesterday









Rajneesh Master

53




53











  • By definition nan!=nan which is why your code does not work.
    – Paul Panzer
    23 hours ago










  • thank you i know now.
    – Rajneesh Master
    22 hours ago
















  • By definition nan!=nan which is why your code does not work.
    – Paul Panzer
    23 hours ago










  • thank you i know now.
    – Rajneesh Master
    22 hours ago















By definition nan!=nan which is why your code does not work.
– Paul Panzer
23 hours ago




By definition nan!=nan which is why your code does not work.
– Paul Panzer
23 hours ago












thank you i know now.
– Rajneesh Master
22 hours ago




thank you i know now.
– Rajneesh Master
22 hours ago












1 Answer
1






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oldest

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0
down vote



accepted










I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.



import numpy as np

iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')

nan_indx = np.argwhere(np.isnan(iris_2d))

print nan_indx.shape
print " "
print nan_indx[0:5,:]


Output:



(150, 2)

[[0 4]
[1 4]
[2 4]
[3 4]
[4 4]]





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    1 Answer
    1






    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes








    up vote
    0
    down vote



    accepted










    I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.



    import numpy as np

    iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')

    nan_indx = np.argwhere(np.isnan(iris_2d))

    print nan_indx.shape
    print " "
    print nan_indx[0:5,:]


    Output:



    (150, 2)

    [[0 4]
    [1 4]
    [2 4]
    [3 4]
    [4 4]]





    share|improve this answer








    New contributor




    Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.





















      up vote
      0
      down vote



      accepted










      I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.



      import numpy as np

      iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')

      nan_indx = np.argwhere(np.isnan(iris_2d))

      print nan_indx.shape
      print " "
      print nan_indx[0:5,:]


      Output:



      (150, 2)

      [[0 4]
      [1 4]
      [2 4]
      [3 4]
      [4 4]]





      share|improve this answer








      New contributor




      Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.



















        up vote
        0
        down vote



        accepted







        up vote
        0
        down vote



        accepted






        I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.



        import numpy as np

        iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')

        nan_indx = np.argwhere(np.isnan(iris_2d))

        print nan_indx.shape
        print " "
        print nan_indx[0:5,:]


        Output:



        (150, 2)

        [[0 4]
        [1 4]
        [2 4]
        [3 4]
        [4 4]]





        share|improve this answer








        New contributor




        Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
        Check out our Code of Conduct.









        I downloaded the data from the url that you mentioned, and saved it as 'iris_data.txt'. Try the following code. It gives you indices of nan in the numpy array iris_2d.



        import numpy as np

        iris_2d = np.genfromtxt('iris_data.txt', delimiter = ',', dtype = 'float')

        nan_indx = np.argwhere(np.isnan(iris_2d))

        print nan_indx.shape
        print " "
        print nan_indx[0:5,:]


        Output:



        (150, 2)

        [[0 4]
        [1 4]
        [2 4]
        [3 4]
        [4 4]]






        share|improve this answer








        New contributor




        Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
        Check out our Code of Conduct.









        share|improve this answer



        share|improve this answer






        New contributor




        Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
        Check out our Code of Conduct.









        answered 23 hours ago









        Siddharth Satpathy

        264




        264




        New contributor




        Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
        Check out our Code of Conduct.





        New contributor





        Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
        Check out our Code of Conduct.






        Siddharth Satpathy is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
        Check out our Code of Conduct.



























             

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