How to Compare Each Element of a Numpy Array Against a Value?

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To compare each element of a NumPy array arr against the scalar x using any of the greater (>), greater equal (>=), smaller (<), smaller equal (<=), or equal (==) operators, use the broadcasting feature with the array as one operand and the scalar as another operand. For example, the greater comparison arr > x results in an array of Boolean values from the element-wise comparisons.

array > scalar
array >= scalar 
array < scalar 
array <= scalar 
array == scalar  

# yields a new Boolean array [True/False ... True/False]

Problem Formulation

Given are:

  • A NumPy array arr.
  • A scalar value x.

❓ How to compare each element of the NumPy array arr against the scalar x using any of the greater (>), greater equal (>=), smaller (<), smaller equal (<=), or equal (==) operators?

The desired result is a NumPy array of Boolean values respresenting the element-wise comparison results.

For example, consider the following pseudocode of what you’re trying to accomplish:

# Given
arr = [1 10 100]
x = 3

# Desired
res = [1>x 10>x 100>x] = [False True True]

Solution: Broadcasting

You can use all comparison operators of a scalar value on a NumPy array:

  • Greater: arr > x
  • Greater or equal: arr >= x
  • Smaller: arr < x
  • Smaller or equal: arr <= x
  • Equal: arr == x

NumPy will automatically bring both operands into the same shape (a feature called “broadcasting“).

import numpy as np


# Given
arr = np.array([1, 10, 100])
x = 3

# Greater:
print(arr > x)
# [False  True  True]

# Greater or equal:
print(arr >= x)
# [False  True  True]

# Smaller:
print(arr < x)
# [ True False False]

# Smaller or equal:
print(arr <= x)
# [ True False False]

# Equal:
print(arr == x)
# [False False False]

The comparison is performed element-wise and the result of the operation is a Boolean array as desired.

Data Science Puzzle

import numpy as np

# popular instagram accounts
# (millions followers)
inst = [232, #"@instagram"
        133, #"@selenagomez"
        59, #"@victoriassecret"
        120, #"@cristiano"
        111, #"@beyonce"
        76] #"@nike"

inst = np.array(inst)
superstars = inst > 100
print(superstars[0])
print(superstars[2])

Exercise: What is the output of this puzzle?

You can solve this puzzle on our interactive puzzle-based training app and track your Python skills:

NumPy is a popular Python library for data science focusing on linear algebra.

The following handy NumPy feature will prove useful throughout your career. You can use comparison operators directly on NumPy arrays. The result is an equally-sized NumPy array with Boolean values. Each Boolean indicates whether the comparison evaluates to True for the respective value in the original array.

The puzzle creates a list of integers. Each integer represents the number of followers of popular Instagram accounts (in millions).

We print the first and the third boolean value of the resulting NumPy array. The result is True for @instagram with 232 million followers and False for @victoriassecret with 59 million followers.

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