Python Scipy stats.mode()用法及代碼示例

scipy.stats.mode(array, axis=0)函數沿數組的指定軸(python中的列表)計算數組元素的模式。

其公式-

where,
l:Lower Boundary of modal class
h:Size of modal class
fm:Frequency corresponding to modal class
f1:Frequency preceding  to modal class
f2:Frequency proceeding to modal class

參數：
array:具有用於計算模式的元素的輸入數組或對象。
axis :要沿著其計算模式的軸。默認情況下軸= 0

返回：基於設置的參數的數組元素的模態值。

代碼1：

# Arithmetic mode   
from scipy import stats 
import numpy as np  
  
arr1 = np.array([[1, 3, 27, 13, 21, 9], 
                [8, 12, 8, 4, 7, 10]])  
   
  
print("Arithmetic mode is:\n", stats.mode(arr1)) 

輸出：

Arithmetic mode is:
 ModeResult(mode=array([[1, 3, 8, 4, 7, 9]]), count=array([[1, 1, 1, 1, 1, 1]]))

代碼2：多維數據

# Arithmetic mode  
from scipy import stats 
import numpy as np  
  
arr1 = [[1, 3, 27],  
        [3, 4, 6],  
        [7, 6, 3],  
        [3, 6, 8]]  
    
print("Arithmetic mode is:\n", stats.mode(arr1))  
  
print("\nArithmetic mode is:\n", stats.mode(arr1, axis = None))  
  
print("\nArithmetic mode is:\n", stats.mode(arr1, axis = 0))  
  
print("\nArithmetic mode is:\n", stats.mode(arr1, axis = 1)) 

輸出：

Arithmetic mode is:
 ModeResult(mode=array([[3, 6, 3]]), count=array([[2, 2, 1]]))

Arithmetic mode is:
 ModeResult(mode=array([3]), count=array([4]))

Arithmetic mode is:
 ModeResult(mode=array([[3, 6, 3]]), count=array([[2, 2, 1]]))

Arithmetic mode is:
 ModeResult(mode=array([[1],
       [3],
       [3],
       [3]]), count=array([[1],
       [1],
       [1],
       [1]]))