Python numpy.quantile()用法及代碼示例

numpy.quantile(arr, q, axis = None)：計算q^th沿指定軸的給定數據(數組元素)的分位數。

當人們處理正態分布時，分位數在統計中起著非常重要的作用。

在上圖中，Q2是個median正態分布的數據。Q3 - Q2表示給定數據集的分位數範圍。

參數:
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.

代碼1：

# Python Program illustrating  
# numpy.quantile() method  
import numpy as np 
  
  
# 1D array  
arr = [20, 2, 7, 1, 34] 
  
print("arr:", arr)  
print("Q2 quantile of arr:", np.quantile(arr, .50)) 
print("Q1 quantile of arr:", np.quantile(arr, .25)) 
print("Q3 quantile of arr:", np.quantile(arr, .75)) 
print("100th quantile of arr:", np.quantile(arr, .1))

輸出：

arr:[20, 2, 7, 1, 34]
Q2 quantile of arr:7.0)
Q1 quantile of arr:2.0)
Q3 quantile of arr:20.0)
100th quantile of arr:1.4)

代碼2：

# Python Program illustrating  
# numpy.quantile() method  
import numpy as np 
   
# 2D array  
arr = [[14, 17, 12, 33, 44],   
       [15, 6, 27, 8, 19],  
       [23, 2, 54, 1, 4, ]]  
print("\narr:\n", arr)  
     
# quantile of the flattened array  
print("\n50th quantile of arr, axis = None:", np.quantile(arr, .50))  
print("0th quantile of arr, axis = None:", np.quantile(arr, 0))  
     
# quantile along the axis = 0  
print("\n50th quantile of arr, axis = 0:", np.quantile(arr, .25, axis = 0))  
print("0th quantile of arr, axis = 0:", np.quantile(arr, 0, axis = 0))  
    
# quantile along the axis = 1  
print("\n50th quantile of arr, axis = 1:", np.quantile(arr, .50, axis = 1))  
print("0th quantile of arr, axis = 1:", np.quantile(arr, 0, axis = 1))  
   
print("\n0th quantile of arr, axis = 1:\n",  
   np.quantile(arr, .50, axis = 1, keepdims = True)) 
print("\n0th quantile of arr, axis = 1:\n",  
   np.quantile(arr, 0, axis = 1, keepdims = True))

輸出：

arr:
[[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4]]

50th quantile of arr, axis = None:15.0
0th quantile of arr, axis = None:1)

50th quantile of arr, axis = 0:[14.5  4.  19.5  4.5 11.5]
0th quantile of arr, axis = 0:[14  2 12  1  4]

50th quantile of arr, axis = 1:[17. 15.  4.]
0th quantile of arr, axis = 1:[12  6  1]

0th quantile of arr, axis = 1:
[[17.]
[15.]
[ 4.]]

0th quantile of arr, axis = 1:
[[12]
[ 6]
[ 1]]

相關用法

注：本文由純淨天空篩選整理自Mohit Gupta_OMG 大神的英文原創作品 numpy.quantile() in Python。非經特殊聲明，原始代碼版權歸原作者所有，本譯文未經允許或授權，請勿轉載或複製。