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Mask an array where a condition is met in Numpy
To mask an array where a condition is met, use the numpy.ma.masked_where() method in Python Numpy. Return the array to mask as an array masked where condition is True. Any masked values of a or condition are also masked in the output.
The condition parameter sets the masking condition. When condition tests floating point values for equality, consider using masked_values instead. The copy parameter, If True (default) make a copy of a in the result. If False modify a in place and return a view.
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([[71, 55, 91], [82, 33, 39], [73, 82, 51], [90, 45, 82]])
print("Array...
", arr)Get the type pf array −
print("
Array type...
", arr.dtype)
Get the dimensions of the Array −
print("
Array Dimensions...
",arr.ndim)Get the shape of the Array −
print("
Our Array Shape...
",arr.shape)
Get the number of elements of the Array −
print("
Number of Elements in the Array...
",arr.size)To mask an array where a condition is met, use the numpy.ma.masked_where() method in Python Numpy. Here, all the elements above 60 will get masked −
print("
Result...
",np.ma.masked_where(arr > 60, arr))
Example
import numpy as np
import numpy.ma as ma
# Create an array with int elements using the numpy.array() method
arr = np.array([[71, 55, 91], [82, 33, 39], [73, 82, 51], [90, 45, 82]])
print("Array...
", arr)
# Get the type pf array
print("
Array type...
", arr.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)
# Get the shape of the Array
print("
Our Array Shape...
",arr.shape)
# Get the number of elements of the Array
print("
Number of Elements in the Array...
",arr.size)
# To mask an array where a condition is met, use the numpy.ma.masked_where() method in Python Numpy
# Here, all the elements above 60 will get masked
print("
Result...
",np.ma.masked_where(arr > 60, arr))Output
Array... [[71 55 91] [82 33 39] [73 82 51] [90 45 82]] Array type... int64 Array Dimensions... 2 Our Array Shape... (4, 3) Number of Elements in the Array... 12 Result... [[-- 55 --] [-- 33 39] [-- -- 51] [-- 45 --]]
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