Python Numpy recarray.mean()用法及代碼示例

在numpy中，數組可能具有包含字段的數據類型，類似於電子表格中的列。一個例子是[(a, int), (b, float)]，其中數組中的每個條目都是一對(int，float)。通常，這些屬性是使用字典查找(例如，arr['a'] and arr['b']。記錄數組允許使用以下方式將字段作為數組的成員進行訪問arr.a and arr.b。

numpy.recarray.mean()函數返回沿給定軸的數組元素的平均值。

用法： numpy.recarray.mean(axis=None, dtype=None, out=None, keepdims=False)

參數：
axis :[無，整數或整數元組，可選]沿其運行的一個或多個軸。默認情況下，使用拚合的輸入。
dtype :[數據類型，可選]計算均值時需要的類型。
out :[ndarray，可選]將結果存儲到的位置。
->如果提供，則必須具有廣播輸入的形狀。
->如果未提供或沒有，則返回新分配的數組。
keepdims :[布爾，可選]如果將其設置為True，則縮小的軸將保留為尺寸為1的尺寸。

Return :[ndarray或scalar]數組的算術平均值(如果軸不存在，則為標量值)或具有沿指定軸的平均值的數組。

代碼1：

# Python program explaining 
# numpy.recarray.mean() method  
  
# importing numpy as geek 
import numpy as geek 
  
# creating input array with 2 different field  
in_arr = geek.array([[(5.0, 2), (3.0, 6), (6.0, 10)], 
                     [(9.0, 1), (5.0, 4), (-12.0, 7)]], 
                     dtype =[('a', float), ('b', int)]) 
  
print ("Input array:", in_arr) 
  
# convert it to a record array, 
# using arr.view(np.recarray) 
rec_arr = in_arr.view(geek.recarray) 
print("Record array of float:", rec_arr.a) 
print("Record array of int:", rec_arr.b) 
  
# applying recarray.mean methods 
# to float record array along default axis  
# i, e along flattened array 
out_arr1 = rec_arr.a.mean() 
# Mean of the flattened array  
print("\nMean of float record array, axis = None:", out_arr1)  
  
  
# applying recarray.mean methods 
# to float record array along axis 0 
# i, e along vertical 
out_arr2 = rec_arr.a.mean(axis = 0) 
# Mean along 0 axis 
print("\nMean of float record array, axis = 0:", out_arr2) 
  
  
# applying recarray.mean methods 
# to float record array along axis 1 
# i, e along horizontal 
out_arr3 = rec_arr.a.mean(axis = 1) 
# Mean along 0 axis 
print("\nMean of float record array, axis = 1:", out_arr3) 
  
  
# applying recarray.mean methods 
# to int record array along default axis  
# i, e along flattened array 
out_arr4 = rec_arr.b.mean(dtype ='int') 
# Mean of the flattened array  
print("\nMean of int record array, axis = None:", out_arr4)  
  
  
# applying recarray.mean methods 
# to int record array along axis 0 
# i, e along vertical 
out_arr5 = rec_arr.b.mean(axis = 0) 
# Mean along 0 axis 
print("\nMean of int record array, axis = 0:", out_arr5) 
  
  
# applying recarray.mean methods 
# to int record array along axis 1 
# i, e along horizontal 
out_arr6 = rec_arr.b.mean(axis = 1) 
# Mean along 0 axis 
print("\nMean of int record array, axis = 1:", out_arr6)

輸出：

Input array: [[(  5.,  2) (  3.,  6) (  6., 10)]
 [(  9.,  1) (  5.,  4) (-12.,  7)]]
Record array of float: [[  5.   3.   6.]
 [  9.   5. -12.]]
Record array of int: [[ 2  6 10]
 [ 1  4  7]]

Mean of float record array, axis = None: 2.6666666666666665

Mean of float record array, axis = 0: [ 7.  4. -3.]

Mean of float record array, axis = 1: [4.66666667 0.66666667]

Mean of int record array, axis = None: 5

Mean of int record array, axis = 0: [1.5 5.  8.5]

Mean of int record array, axis = 1: [6. 4.]

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注：本文由純淨天空篩選整理自jana_sayantan大神的英文原創作品 Numpy recarray.mean() function | 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。