Python | numpy.nanmean()函数
原文:https://www . geesforgeks . org/python-numpy-nan mean-function/
numpy.nanmean() 函数可以用来计算忽略 NaN 值的数组的平均值。如果数组中有 NaN 值，我们可以在不影响 NaN 值的情况下求出平均值。
语法: numpy.nanmean(a，axis=None，dtype=None，out=None，keepdims =) 参数: a:【arr _ like】输入数组 axis: 我们可以用 axis=1 表示行方向或者 axis=0 表示列方向。 出:输出数组 数据类型:数组的数据类型 overwrite_input: 如果为真，则允许使用输入数组 a 的内存进行计算。对中值的调用将修改输入数组。 保持尺寸:如果设置为真，缩小的轴将作为尺寸为 1 的尺寸留在结果中。使用此选项，结果将会正确地广播到原始 a 中。 返回:返回数组元素的平均值
示例#1:
蟒蛇 3
# Python code to demonstrate the
# use of numpy.nanmean
import numpy as np
# create 2d array with nan value.
arr = np.array([[20, 15, 37], [47, 13, np.nan]])
print("Shape of array is", arr.shape)
print("Mean of array without using nanmean function:",
np.mean(arr))
print("Using nanmean function:", np.nanmean(arr))
Output:
Shape of array is (2, 3)
Mean of array without using nanmean function: nan
Using nanmean function: 26.4
例 2:
蟒蛇 3
# Python code to demonstrate the
# use of numpy.nanmean
# with axis = 0
import numpy as np
# create 2d matrix with nan value
arr = np.array([[32, 20, 24],
[47, 63, np.nan],
[17, 28, np.nan],
[10, 8, 9]])
print("Shape of array is", arr.shape)
print("Mean of array with axis = 0:",
np.mean(arr, axis = 0))
print("Using nanmedian function:",
np.nanmean(arr, axis = 0))
Output:
Shape of array is (4, 3)
Mean of array with axis = 0: [ 26.5 29.75 nan]
Using nanmedian function: [ 26.5 29.75 16.5 ]
例 3:
蟒蛇 3
# Python code to demonstrate the
# use of numpy.nanmedian
# with axis = 1
import numpy as np
# create 2d matrix with nan value
arr = np.array([[32, 20, 24],
[47, 63, np.nan],
[17, 28, np.nan],
[10, 8, 9]])
print("Shape of array is", arr.shape)
print("Mean of array with axis = 1:",
np.mean(arr, axis = 1))
print("Using nanmedian function:",
np.nanmean(arr, axis = 1))
Output:
Shape of array is (4, 3)
Mean of array with axis = 1: [ 25.33333333 nan nan 9\. ]
Using nanmedian function: [ 25.33333333 55\. 22.5 9\. ]
