# Count the number of masked elements in Numpy

To count the number of masked elements, use the ma.MaskedArray.count_masked() method in Python Numpy. The method returns the total number of masked elements (axis=None) or the number of masked elements along each slice of the given axis.

The axis parameter is the axis along which to count. If None (default), a flattened version of the array is used.

## Steps

At first, import the required library −

import numpy as np
import numpy.ma as ma

Creating a 4x4 array with int elements using the numpy.arange() method −

arr = np.arange(16).reshape((4,4))
print("Array...", arr)
print("Array type...", arr.dtype)

Get the dimensions of the Array −

print("Array Dimensions...",arr.ndim)
print("Our Array type...", arr.dtype)

Get the shape of the Array −

print("Our Masked Array Shape...",arr.shape)


Get the number of elements of the Array −

print("Elements in the Masked Array...",arr.size)

arr = ma.array(arr)

arr[3, 3] = ma.masked

print("Result (number of masked elements)...",ma.count_masked(arr))


## Example

# Python ma.MaskedArray - Count the number of masked elements

import numpy as np
import numpy.ma as ma

# Creating a 4x4 array with int elements using the numpy.arange() method
arr = np.arange(16).reshape((4,4))
print("Array...", arr)
print("Array type...", arr.dtype)

# Get the dimensions of the Array
print("Array Dimensions...",arr.ndim)
print("Our Array type...", arr.dtype)

# Get the shape of the Array

# Get the number of elements of the Array

arr = ma.array(arr)

print("Result (number of masked elements)...",ma.count_masked(arr))

## Output

Array...
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]]

Array type...
int64

Array Dimensions...
2

Our Array type...
int64

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