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# Concatenate a sequence of masked arrays in Numpy

To concatenate a sequence of arrays, use the **ma.concatenate()** method in Python Numpy. The parameters are the arrays that must have the same shape, except in the dimension corresponding to axis (the first, by default). The axis is the axis along which the arrays will be joined. Default is 0. The function returns the concatenated array with any masked entries preserved.

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 Array 1, a 3x3 array with int elements using the numpy.arange() method −

arr1 = np.arange(9).reshape((3,3)) print("Array1...

", arr1) print("

Array type...

", arr1.dtype)

Create a masked array 1 −

arr1 = ma.array(arr1)

Mask Array1 −

arr1[0, 1] = ma.masked arr1[1, 1] = ma.masked

Display Masked Array 1 −

print("

Masked Array1...

",arr1)

Create Array 2, another 3x3 array with int elements using the numpy.arange() method −

arr2 = np.arange(9).reshape((3,3)) print("

Array2...

", arr2) print("

Array type...

", arr2.dtype)

Create a masked array 2 −

arr2 = ma.array(arr2)

Mask Array2 −

arr2[2, 1] = ma.masked arr2[2, 2] = ma.masked

Display Masked Array 2 −

print("

Masked Array2...

",arr2)

To concatenate a sequence of arrays, use the ma.concatenate() method in Python Numpy −

print("

Result of concatenation...

",ma.concatenate([arr1, arr2]))

## Example

# Python ma.MaskedArray - Concatenate a sequence of masked arrays import numpy as np import numpy.ma as ma # Array 1 # Creating a 3x3 array with int elements using the numpy.arange() method arr1 = np.arange(9).reshape((3,3)) print("Array1...

", arr1) print("

Array type...

", arr1.dtype) # Get the dimensions of the Array print("

Array Dimensions...

",arr1.ndim) # Get the shape of the Array print("

Our Array Shape...

",arr1.shape) # Get the number of elements of the Array print("

Elements in the Array...

",arr1.size) # Create a masked array arr1 = ma.array(arr1) # Mask Array1 arr1[0, 1] = ma.masked arr1[1, 1] = ma.masked # Display Masked Array 1 print("

Masked Array1...

",arr1) # Array 2 # Creating another 3x3 array with int elements using the numpy.arange() method arr2 = np.arange(9).reshape((3,3)) print("

Array2...

", arr2) print("

Array type...

", arr2.dtype) # Get the dimensions of the Array print("

Array Dimensions...

",arr2.ndim) # Get the shape of the Array print("

Our Array Shape...

",arr2.shape) # Get the number of elements of the Array print("

Elements in the Array...

",arr2.size) # Create a masked array arr2 = ma.array(arr2) # Mask Array2 arr2[2, 1] = ma.masked arr2[2, 2] = ma.masked # Display Masked Array 2 print("

Masked Array2...

",arr2) # To concatenate a sequence of arrays, use the ma.concatenate() method in Python Numpy print("

Result of concatenation...

",ma.concatenate([arr1, arr2]))

## Output

Array1... [[0 1 2] [3 4 5] [6 7 8]] Array type... int64 Array Dimensions... 2 Our Array Shape... (3, 3) Elements in the Array... 9 Masked Array1... [[0 -- 2] [3 -- 5] [6 7 8]] Array2... [[0 1 2] [3 4 5] [6 7 8]] Array type... int64 Array Dimensions... 2 Our Array Shape... (3, 3) Elements in the Array... 9 Masked Array2... [[0 1 2] [3 4 5] [6 -- --]] Result of concatenation... [[0 -- 2] [3 -- 5] [6 7 8] [0 1 2] [3 4 5] [6 -- --]]

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