Python中的 numpy.std()

numpy.std(arr, axis = None) ：计算给定数据（数组元素）沿指定轴（如果有）的标准差。

标准偏差 (SD)被测量为给定数据集中数据分布的分布。

例如 ：

x = 1 1 1 1 1 
Standard Deviation = 0 . 

y = 9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4 
Step 1 : Mean of distribution 4 = 7
Step 2 : Summation of (x - x.mean())**2 = 178
Step 3 : Finding Mean = 178 /20 = 8.9 
This Result is Variance.
Step 4 : Standard Deviation = sqrt(Variance) = sqrt(8.9) = 2.983..

Parameters :
arr : [array_like]input array.
axis : [int or tuples of int]axis along which we want to calculate the standard deviation. Otherwise, it will consider arr to be flattened (works on all the axis). axis = 0 means SD along the column and axis = 1 means SD along the row.
out : [ndarray, optional]Different array in which we want to place the result. The array must have the same dimensions as expected output.
dtype : [data-type, optional]Type we desire while computing SD.

Results : Standard Deviation of the array (a scalar value if axis is none) or array with standard deviation values along specified axis.

代码#1：

# Python Program illustrating 
# numpy.std() method 
import numpy as np
    
# 1D array 
arr = [20, 2, 7, 1, 34]
  
print("arr : ", arr) 
print("std of arr : ", np.std(arr))
  
print ("\nMore precision with float32")
print("std of arr : ", np.std(arr, dtype = np.float32))
  
print ("\nMore accuracy with float64")
print("std of arr : ", np.std(arr, dtype = np.float64))

输出 ：

arr :  [20, 2, 7, 1, 34]
std of arr :  12.576167937809991

More precision with float32
std of arr :  12.576168

More accuracy with float64
std of arr :  12.576167937809991

代码#2：

# Python Program illustrating 
# numpy.std() method 
import numpy as np
    
  
# 2D array 
arr = [[2, 2, 2, 2, 2],  
       [15, 6, 27, 8, 2], 
       [23, 2, 54, 1, 2, ], 
       [11, 44, 34, 7, 2]] 
  
    
# std of the flattened array 
print("\nstd of arr, axis = None : ", np.std(arr)) 
    
# std along the axis = 0 
print("\nstd of arr, axis = 0 : ", np.std(arr, axis = 0)) 
   
# std along the axis = 1 
print("\nstd of arr, axis = 1 : ", np.std(arr, axis = 1))

输出 ：

std of arr, axis = None :  15.3668474320532

std of arr, axis = 0 :  [ 7.56224173 17.68473918 18.59267329  3.04138127  0.        ]

std of arr, axis = 1 :  [ 0.          8.7772433  20.53874388 16.40243884]