numpy.nanquantile(arr, q, axis = None)
:计算qth沿指定轴的给定数据(数组元素)的分位数,忽略nan值。
当人们处理正态分布时,分位数在统计中起着非常重要的作用。
在上图中,Q2
是个median
正态分布的数据。Q3 - Q2
表示给定数据集的分位数范围。
参数:
arr : [array_like]input array.
q : quantile value.
axis: [int or tuples of int]axis along which we want to calculate the quantile 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 : [ndarray, optional]Different array in which we want to place the result. The array must have same dimensions as expected output.
Results: qth quantile of the array (a scalar value if axis is none) or array with quantile values along specified axis, ignoring nan values.
代码1:
# Python Program illustrating
# numpy.nanquantile() method
import numpy as np
# 1D array
arr = [20, 2, 7, np.nan, 34]
print("arr:", arr)
print("\n-Q1 quantile of arr:", np.quantile(arr, .50))
print("Q2 - quantile of arr:", np.quantile(arr, .25))
print("Q3 - quantile of arr:", np.quantile(arr, .75))
print("\nQ1 - nanquantile of arr:", np.nanquantile(arr, .50))
print("Q2 - nanquantile of arr:", np.nanquantile(arr, .25))
print("Q3 - nanquantile of arr:", np.nanquantile(arr, .75))
输出:
arr:[20, 2, 7, nan, 34] Q1 - quantile of arr:nan Q2 - quantile of arr:nan Q3 - quantile of arr:nan Q1 - nanquantile of arr:13.5 Q2 - nanquantile of arr:5.75 Q3 - nanquantile of arr:23.5
代码2:
# Python Program illustrating
# numpy.nanquantile() method
import numpy as np
# 2D array
arr = [[14, np.nan, 12, 33, 44],
[15, np.nan, 27, 8, 19],
[23, 2, np.nan, 1, 4, ]]
print("\narr:\n", arr)
# quantile of the flattened array
print("\nQ2 quantile of arr, axis = None:", np.quantile(arr, .50))
print("\nQ2 quantile of arr, axis = None:", np.nanquantile(arr, .50))
print("0th quantile of arr, axis = None:", np.nanquantile(arr, 0))
输出:
arr: [[14, nan, 12, 33, 44], [15, nan, 27, 8, 19], [23, 2, nan, 1, 4]] Q2 quantile of arr, axis = None:nan Q2 quantile of arr, axis = None:14.5 0th quantile of arr, axis = None:1.0
代码3:
# Python Program illustrating
# numpy.nanquantile() method
import numpy as np
# 2D array
arr = [[14, np.nan, 12, 33, 44],
[15, np.nan, 27, 8, 19],
[23, 2, np.nan, 1, 4, ]]
print("\narr:\n", arr)
# quantile along the axis = 0
print("\nQ2 quantile of arr, axis = 0:", np.nanquantile(arr, .50, axis = 0))
print("0th quantile of arr, axis = 0:", np.nanquantile(arr, 0, axis = 0))
# quantile along the axis = 1
print("\nQ2 quantile of arr, axis = 1:", np.nanquantile(arr, .50, axis = 1))
print("0th quantile of arr, axis = 1:", np.nanquantile(arr, 0, axis = 1))
print("\nQ2 quantile of arr, axis = 1:\n",
np.nanquantile(arr, .50, axis = 1, keepdims = True))
print("\n0th quantile of arr, axis = 1:\n",
np.nanquantile(arr, 0, axis = 1, keepdims = True))
输出:
arr: [[14, nan, 12, 33, 44], [15, nan, 27, 8, 19], [23, 2, nan, 1, 4]] Q2 quantile of arr, axis = 0:[15. 2. 19.5 8. 19. ] 0th quantile of arr, axis = 0:[14. 2. 12. 1. 4.] Q2 quantile of arr, axis = 1:[23.5 17. 3. ] 0th quantile of arr, axis = 1:[12. 8. 1.] Q2 quantile of arr, axis = 1: [[23.5] [17. ] [ 3. ]] 0th quantile of arr, axis = 1: [[12.] [ 8.] [ 1.]]
相关用法
注:本文由纯净天空筛选整理自Mohit Gupta_OMG 大神的英文原创作品 numpy.nanquantile() in Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。