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# Remove axes of length one with specific axis in Numpy

To remove axes of length one, use the **ma.MaskedArray.squeeze()** method in Numpy. The axis is set using the "axis" parameter. The axis selects a subset of the entries of length one in the shape. If an axis is selected with shape entry greater than one, an error is raised.

The function returns an input array, but with all or a subset of the dimensions of length 1 removed. This is always a itself or a view into a. Note that if all axes are squeezed, the result is a 0d array and not a scalar.

## 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([[[15], [30], [45]]]) 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, 1, 0]]) print("

Our Masked Array

", maskArr) 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)

To remove axes of length one, use the ma.MaskedArray.squeeze() method in Numpy. The axis is set using the "axis" parameter −

print("

Result...

",np.squeeze(maskArr, axis = 0)) print("

Shape...

",np.squeeze(maskArr, axis = 0).shape)

## Example

# Python ma.MaskedArray - Remove axes of length one with specific axis import numpy as np import numpy.ma as ma # Create an array with int elements using the numpy.array() method arr = np.array([[[15], [30], [45]]]) 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, 1, 0]]) print("

Our Masked Array

", maskArr) 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) # To remove axes of length one, use the ma.MaskedArray.squeeze() method in Numpy # The axis is set using the "axis" parameter print("

Result...

",np.squeeze(maskArr, axis = 0)) print("

Shape...

",np.squeeze(maskArr, axis = 0).shape)

## Output

Array... [[[15] [30] [45]]] Array type... int64 Array Dimensions... 3 Our Masked Array [[[15] [--] [45]]] Our Masked Array type... int64 Our Masked Array Dimensions... 3 Our Masked Array Shape... (1, 3, 1) Elements in the Masked Array... 3 Result... [[15] [--] [45]] Shape... (3, 1)

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