CODEWITHSUNDEEP
pythonarraysnumpy
lee.edward01
lee.edward01

Reputation: 473

numpy remove column from array where the first element in column is a 0

If I had a random numpy array as shown below:

myArray:

        [0  ,        0      ,  51.78  ,      17],
        [823.    ,   91.31  ,  51.63  ,      13],
        [819.    ,   93.03  ,  51.77  ,      52],
        [776.32  ,   93.85  ,  52.02  ,      34],
        [755.12  ,   92.48  ,  49.955 ,      77],
        [739.01  ,   97.68  ,  50.75  ,      48],
        [760.17  ,   98.26  ,  51.1   ,      12],
        [780.37  ,   98.82  ,  51.52  ,      13],
        [740.34  ,   98.5   ,  50.48  ,      17],
        [768.65  ,  104.86  ,  51.71  ,      97]]

I was looking to remove the columns in which the first element is a 0, resulting in an array that follows:

myArray:

        [51.78  ,      17],
        [51.63  ,      13],
        [51.77  ,      52],
        [52.02  ,      34],
        [49.955 ,      77],
        [50.75  ,      48],
        [51.1   ,      12],
        [1.52   ,      13],
        [50.48  ,      17],
        [51.71  ,      97]]

NOTE

I am aware of np.delete, I am not sure if I can implement this given any random array. I am looking for a method in which, if given a random array that has 0's in the first row, I can implement the same function to any array, not just the given example above.

Any tips would be greatly appreciated!

Upvotes: 0

Views: 60

Answers (1)

akuiper
akuiper

Reputation: 214957

Use Boolean Indexing and the condition would be arr[0] != 0:

arr[:, arr[0] != 0]

#array([[ 51.78 ,  17.   ],
#       [ 51.63 ,  13.   ],
#       [ 51.77 ,  52.   ],
#       [ 52.02 ,  34.   ],
#       [ 49.955,  77.   ],
#       [ 50.75 ,  48.   ],
#       [ 51.1  ,  12.   ],
#       [ 51.52 ,  13.   ],
#       [ 50.48 ,  17.   ],
#       [ 51.71 ,  97.   ]])

Upvotes: 3

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