# Return a copy of the masked array collapsed into one dimension in row-major order in Numpy

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To return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy. The "order" parameter is used to flatter in order. The ‘C’ order means to flatten in row-major (C-style) order.

The order ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’.

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

Create an array with int elements using the numpy.array() method −

arr = np.array([[49, 85, 45], [67, 33, 59]])
print("Array...", arr)
print("Array type...", arr.dtype)

Get the dimensions of the Array −

print("Array Dimensions...",arr.ndim)

Create a masked array and mask some of them as invalid −

maskArr = ma.masked_array(arr, mask =[[0, 0, 1], [ 0, 1, 0]])
print("Our Masked Array type...", maskArr.dtype)

Get the dimensions of the Masked Array −

print("Our Masked Array Dimensions...",maskArr.ndim)

Get the shape of the Masked Array −

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

Get the number of elements of the Masked Array −

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

Return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy. The "order" parameter is used to flatter in order. The ‘C’ order means to flatten in rowmajor (C-style) order −

print("Result...",maskArr.flatten(order = 'C'))

## Example

# Python ma.MaskedArray - Return a copy of the array collapsed into one dimension

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[78, 85, 51], [56, 33, 97]])
print("Array...", arr)
print("Array type...", arr.dtype)

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

# Create a masked array and mask some of them as invalid

# Get the dimensions of the Masked Array

# Get the shape of the Masked Array

# Get the number of elements of the Masked Array

# To return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy
# The "order" parameter is used to flatter in order
# The ‘C’ order means to flatten in row-major (C-style) order.
print("Result...",maskArr.flatten())

## Output

Array...
[[78 85 51]
[56 33 97]]

Array type...
int64

Array Dimensions...
2

[[78 -- 51]
[56 -- 97]]

int64

[78 -- 51 56 -- 97]