Python Numpy nanmedian()

numpy.nanmedian()函数可以用来计算数组的中位数，忽略NaN值。如果数组中有NaN值，我们可以找出中位数而不受NaN值的影响。让我们看看关于numpy.nanmedian()方法的不同类型的例子。

语法:

numpy.nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=)

参数:
a: [arr_like] 输入阵列
轴：我们可以使用轴=1表示行，或轴=0表示列。
out:输出阵列
overwrite_input: 如果为真，则允许使用输入数组a的内存进行计算。输入数组将被调用median修改。
keepdims:如果设置为True，被缩小的轴会作为尺寸为1的尺寸留在结果中。有了这个选项，结果将正确地与原始的A进行对比。
返回：它在ndarray中返回中值。

示例 #1:

# Python code to demonstrate the
# use of numpy.nanmedian
import numpy as np
 
# create 2d array with nan value.
arr = np.array([[12, 10, 34], [45, 23, np.nan]])
 
print("Shape of array is", arr.shape)
 
print("Median of array without using nanmedian function:",
                                           np.median(arr))
 
print("Using nanmedian function:", np.nanmedian(arr))

输出:

Shape of array is (2, 3)
Median of array without using nanmedian function: nan
Using nanmedian function: 23.0

示例 #2:

# Python code to demonstrate the
# use of numpy.nanmedian
# with axis
import numpy as np
 
# create 2d array with nan value.
arr = np.array([[12, 10, 34], [45, 23, np.nan]])
 
print("Shape of array is", arr.shape)
 
print("Median of array with axis = 0:",
             np.median(arr, axis = 0))
 
print("Using nanmedian function:",
      np.nanmedian(arr, axis = 0))

输出:

Shape of array is (2, 3)
Median of array with axis = 0: [ 28.5  16.5   nan]
Using nanmedian function: [ 28.5  16.5  34. ]

示例 #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([[12, 10, 34],
                [45, 23, np.nan], 
                [7, 8, np.nan]])
 
print("Shape of array is", arr.shape)
 
print("Median of array with axis = 0:",
             np.median(arr, axis = 1))
 
print("Using nanmedian function:",
      np.nanmedian(arr, axis = 1))

输出:

Shape of array is (3, 3)
Median of array with axis = 0: [ 12.  nan  nan]
Using nanmedian function: [ 12.   34.    7.5]