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numpy.nanpercentile()
used to calculate the nth percentile of data (array elements) along the specified axis, ang ignores nan values.
Syntax: numpy.nanpercentile (arr, q, axis = None, out = None)
Parameters:
arr: input array.
q: percentile value.
axis: axis along which we want to calculate the percentile value.Otherwise, it will consider arr to be flattened (works on all the axis). axis = 0
means along the column and axis = 1 means working along the row.
out: Different array in which we want to place the result. The array must have same dimensions as expected output.Return: Percentile of the array (a scalar value if axis is none) or array with percentiles of values ​​along specified axis.
Code # 1: Work
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Output:
arr: [20, 2, 7, nan, 34] 30th percentile of arr: nan 25th percentile of arr: nan 75th percentile of arr: nan 30th percentile of arr: 13.5 25th percentile of arr: 5.75 75th percentile of arr: 23.5
Code # 2:
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Output:
arr: [[14, nan, 12, 33, 44], [15, nan, 27, 8, 19], [23, 2, nan, 1, 4]] 50th Percentile of arr , axis = None: nan 50th Percentile of arr, axis = None: 14.5 0th Percentile of arr, axis = None: 1.0 50th Percentile of arr, axis = 0: [15. 2. 19.5 8. 19.] 0th Percentile of arr, axis = 0: [14. 2. 12. 1. 4.] 50th Percentile of arr, axis = 1: [23.5 17. 3.] 0th Percentile of arr, axis = 1: [12. 8. 1.] 0th Percentile of arr, axis = 1: [[23.5] [17. ] [3.]] 0th Percentile of arr, axis = 1: [[12.] [8.] [1.]]
Code # 3:
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Output:
arr: [[14, nan, 12, 33, 44] , [15, nan, 27, 8, 19], [23, nan, nan, 1, 4]] 50th Percentile of arr, axis = 1: [23.5 17. 4.] 50th Percentile of arr, axis = 0: [fifteen. nan 19.5 8. 19.] RuntimeWarning: All-NaN slice encountered overwrite_input, interpolation)
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San Francisco | 2023-03-21
I was preparing for my coding interview, thanks for clarifying this - numpy.nanpercentile () in Python in Python is not the simplest one. Checked yesterday, it works!
Moscow | 2023-03-21
Simply put and clear. Thank you for sharing. numpy.nanpercentile () in Python and other issues with Expect PHP module was always my weak point 😁. Will get back tomorrow with feedback
Rome | 2023-03-21
I was preparing for my coding interview, thanks for clarifying this - numpy.nanpercentile () in Python in Python is not the simplest one. I just hope that will not emerge anymore