numpy.mean() 函數
numpy.mean(a, axis, dtype, out,keepdims ) [source]
mean()函數功能:求取均值
經常操作的參數為 axis,以 $m * n$ 矩陣舉例:
- axis 不設置值,對 $m*n$ 個數求均值,返回一個實數;
- axis = 0:壓縮行,對各列求均值;
- axis =1 :壓縮列,對各行求均值;
例子:
import numpy as np a = np.array([[1, 2], [3, 4]]) print(np.mean(a)) #2.5
print(np.mean(a, axis=0))# axis=0,計算每一列的均值 #[2., 3.]
print(np.mean(a, axis=1)) # axis = 1計算每一行的均值 #[1.5, 3.5]
numpy.std()函數
numpy.std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>, *, where=<no value>) [source]
該函數用於求標准差。
例子:
import numpy as np a = np.array([[1, 2], [3, 4]]) print(np.std(a)) #1.118033988749895
print(np.std(a, axis=0)) #[1., 1.]
print(np.std(a, axis=1) ) #[0.5, 0.5]
numpy.var()函數
numpy.var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>, *, where=<no value>) [source]
Compute the variance along the specified axis.計算方差。
例子:
import numpy as np a = np.array([[1, 2], [3, 4]]) print(np.var(a)) #1.25
print(np.var(a, axis=0)) #[1., 1.]
print(np.var(a, axis=1)) #[0.25, 0.25]
