Python中的 numpy.var()

numpy.var(arr, axis = None) ：计算给定数据（数组元素）沿指定轴（如果有）的方差。

例子 ：

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

参数 ：

arr : [array_like] input array.
axis : [int or tuples of int] axis along which we want to calculate the variance. Otherwise, it will consider arr to be flattened (works on all the axis). axis = 0 means variance along the column and axis = 1 means variance 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 variance.

Results : Variance of the array (a scalar value if axis is none) or array with variance values along specified axis.

代码#1：

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

输出 ：

arr :  [20, 2, 7, 1, 34]
var of arr :  158.16

var of arr :  158.16

var of arr :  158.16

代码#2：

# Python Program illustrating 
# numpy.var() 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]] 
  
      
# var of the flattened array 
print("\nvar of arr, axis = None : ", np.var(arr)) 
      
# var along the axis = 0 
print("\nvar of arr, axis = 0 : ", np.var(arr, axis = 0)) 
  
# var along the axis = 1 
print("\nvar of arr, axis = 1 : ", np.var(arr, axis = 1)) 

输出 ：

var of arr, axis = None :  236.14000000000004

var of arr, axis = 0 :  [ 57.1875 312.75   345.6875   9.25     0.    ]

var of arr, axis = 1 :  [  0.    77.04 421.84 269.04]