- Trending Categories
- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

# Return the underlying data as a view of the masked array in Numpy

To return the underlying data, as a view of the masked array, use the **ma.MaskedArray.data** in Python Numpy.

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)

Create a masked array −

arr = ma.array(arr) arr[0, 1] = ma.masked arr[1, 1] = ma.masked arr[2, 1] = ma.masked arr[2, 2] = ma.masked arr[3, 0] = ma.masked arr[3, 2] = ma.masked 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))

Return the mask of a masked array −

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

Return the data of a masked array as an ndarray −

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

Determine whether input is an instance of masked array −

print("\nWhether input is an instance of masked array?\n",ma.isMaskedArray(arr))

To return the underlying data, as a view of the masked array, use the ma.MaskedArray.data −

print("\nResult...\n",arr.data)

## 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 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) # Create a masked array arr = ma.array(arr) arr[0, 1] = ma.masked arr[1, 1] = ma.masked arr[2, 1] = ma.masked arr[2, 2] = ma.masked arr[3, 0] = ma.masked arr[3, 2] = ma.masked 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)) # Return the mask of a masked array print("\nThe mask of a masked array)...\n",ma.getmask(arr)) # Return the data of a masked array as an ndarray print("\nData of a masked array as an ndarray...\n",ma.getdata(arr)) # Determine whether input is an instance of masked array print("\nWhether input is an instance of masked array?\n",ma.isMaskedArray(arr)) # To return the underlying data, as a view of the masked array, use the ma.MaskedArray.data in Python Numpy print("\nResult...\n",arr.data)

## 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 Our Masked Array Shape... (4, 4) Elements in the Masked Array... 16 The number of masked elements... [1 1 2 3] The mask of a masked array)... [[False True False False] [False True False False] [False True True False] [ True False True True]] Data of a masked array as an ndarray... [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]] Whether input is an instance of masked array? True Result... [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11] [12 13 14 15]]

- Related Questions & Answers
- Return a view of the masked array with axes transposed in NumPy
- Return the pickle of the masked array as a string in NumPy
- Return all the non-masked data as a 1-D array in Numpy
- Return the data of a masked array as an ndarray
- Return a view of the MaskedArray data in Numpy
- Return a view of the masked array with axis1 and axis2 interchanged in Numpy
- Return a copy of the masked array in NumPy
- Return the mask of a masked array in Numpy
- Return the transpose of the masked array in NumPy
- Return the length of the masked array in Numpy
- Return the data portion of the masked array as a hierarchical Python list
- Return a view of the masked array with axes transposed along given axis in NumPy
- Return the addresses of the data and mask areas of a masked array in Numpy
- Return the absolute value of a masked Array in NumPy
- Return the average of the masked array elements in Numpy