# Suppress whole rows of a 2-D array that contain masked values in Numpy

NumpyServer Side ProgrammingProgramming

To suppress whole rows of a 2-D array that contain masked values, use the np.ma.mask_compress_rows() method in 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

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

arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

Get the dimensions of the Array −

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

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

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

Get the dimensions of the Masked Array −

print("\nOur Masked Array Dimensions...\n",maskArr.ndim)

Get the shape of the Masked Array −

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

Get the number of elements of the Masked Array −

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


To suppress whole rows of a 2-D array that contain masked values, use the np.ma.mask_compress_rows() method −

print("\nResult...\n",np.ma.compress_rows(maskArr))

## Example

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

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

# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[1, 1, 0], [ 0, 0, 0], [0, 1, 0], [0, 1, 0]])

# Get the dimensions of the Masked Array

# Get the shape of the Masked Array

# Get the number of elements of the Masked Array

# To suppress whole rows of a 2-D array that contain masked values, use the np.ma.mask_compress_rows() method in Numpy
print("\nResult...\n",np.ma.compress_rows(maskArr))

## Output

Array...
[[65 68 81]
[93 33 39]
[73 88 51]
[62 45 67]]

Array type...
int64

Array Dimensions...
2

[[-- -- 81]
[93 33 39]
[73 -- 51]
[62 -- 67]]

int64

[[93 33 39]]