Array Filtering with NumPy for Python

Array Filtering

Taking some elements out of an existing array and creating a new one from it is called filtering.

In NumPy, we use Boolean indexed lists to filter arrays.

A Boolean indexed list is a list of Boolean values corresponding to the indexes in the array.

If the value at the index is True, the element is included in the filtered array; if the value at the index is False, the element is excluded from the filtered array.

an actual example

Creates an array with elements at indexes 0 and 2, 4:

import numpy as np
arr = ([61, 62, 63, 64, 65])
x = [True, False, True, False, True]
newarr = arr[x]
print(newarr)

running example

The above example will return [61, 63, 65], why?

Because the new filter only contains values for which the filter array has the value True, in this case the indexes are 0 and 2, 4.

Creating Filter Arrays

In the above example, we hard-coded the True and False values, but the usual use is to create filter arrays based on conditions.

an actual example

Creates a filter array that returns only values greater than 62:

import numpy as np
arr = ([61, 62, 63, 64, 65])
# Create an empty list
filter_arr = []
# Iterate over each element of arr
for element in arr:
  # Set the value to True if the element is greater than 62, False otherwise:
  if element > 62:
    filter_arr.append(True)
  else:
    filter_arr.append(False)
newarr = arr[filter_arr]
print(filter_arr)
print(newarr)

running example

an actual example

Creates a filter array that returns only the even elements of the original array:

import numpy as np
arr = ([1, 2, 3, 4, 5, 6, 7])
# Create an empty list
filter_arr = []
# Iterate over each element of arr
for element in arr:
  # Set the value to True if the element is divisible by 2, False otherwise
  if element % 2 == 0:
    filter_arr.append(True)
  else:
    filter_arr.append(False)
newarr = arr[filter_arr]
print(filter_arr)
print(newarr)

running example

Creating filters directly from an array

The above example is a very common task in NumPy, and NumPy provides a good way to solve it.

Instead of iterable variables, we can just replace the array in the condition and it will work as we expect.

an actual example

Creates a filter array that returns only values greater than 62:

import numpy as np
arr = ([61, 62, 63, 64, 65])
filter_arr = arr > 62
newarr = arr[filter_arr]
print(filter_arr)
print(newarr)

running example

an actual example

Creates a filter array that returns only the even elements of the original array:

import numpy as np
arr = ([1, 2, 3, 4, 5, 6, 7])
filter_arr = arr % 2 == 0
newarr = arr[filter_arr]
print(filter_arr)
print(newarr)

running example

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