# Return the data of a masked array as an ndarray

NumpyServer Side ProgrammingProgramming

To return the data of a masked array as an ndarray, use the ma.getdata() method in Python Numpy. Returns the data of a (if any) as an ndarray if a is a MaskedArray, else return a as a ndarray or subclass if not.

The subok parameter suggest whether to force the output to be a pure ndarray (False) or to return a subclass of ndarray if appropriate (True, default).

A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.

## 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...\n", arr)
print("\nArray type...\n", arr.dtype)

Get the dimensions of the Array −

print("\nArray Dimensions...\n",arr.ndim)


Get the shape of the Array −

print("\nOur Masked Array Shape...\n",arr.shape)

Get the number of elements of the Array −

print("\nElements in the Masked Array...\n",arr.size)


arr = ma.array(arr)
arr[3, 3] = ma.masked

Count the number of masked elements along specific axis −

print("\nThe number of masked elements...\n",ma.count_masked(arr, axis = 1))


print("\nThe mask of a masked array)...\n",ma.getmask(arr))

To return the data of a masked array as an ndarray, use the ma.getdata() method in Python Numpy −

print("\nResult (data of a masked array as an ndarray)...\n",ma.getdata(arr))


## Example

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...\n", arr)
print("\nArray type...\n", arr.dtype)

# Get the dimensions of the Array
print("\nArray Dimensions...\n",arr.ndim)
print("\nOur Array type...\n", arr.dtype)

# Get the shape of the Array

# Get the number of elements of the Array

arr = ma.array(arr)

# Count the number of masked elements along specific axis

# To return the data of a masked array as an ndarray, use the ma.getdata() method in Python Numpy
print("\nResult (data of a masked array as an ndarray)...\n",ma.getdata(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

(4, 4)

16

[1 1 2 3]

[12 13 14 15]]