NumPy strings.less_equal() – Compare Two String Arrays

NumPy strings.less_equal()

The numpy.strings.less_equal() function compares two string arrays element-wise and returns a boolean array indicating whether each element in x1 is less than or equal to the corresponding element in x2.

Syntax

numpy.strings.less_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True)

Parameters

Parameter	Type	Description
x1, x2	array_like	Input string arrays to compare. If their shapes differ, they must be broadcastable to a common shape.
out	ndarray, None, or tuple of ndarray and None, optional	Optional output array where the result is stored. If None, a new array is created.
where	array_like, optional	Boolean mask specifying which elements to compare. Elements where where=False retain their original value.
casting	str, optional	Defines the casting behavior when comparing strings.
order	str, optional	Memory layout order of the output array.
dtype	data-type, optional	Defines the data type of the output array.
subok	bool, optional	Determines if subclasses of ndarray are preserved in the output.

Return Value

Returns an array of boolean values indicating where x1 <= x2 element-wise. If both inputs are scalars, a single boolean value is returned.

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Examples

1. Comparing Two Scalar Strings

Here, we compare two string values directly.

import numpy as np

# Define two string scalars
str1 = "apple"
str2 = "banana"

# Compare the strings using less_equal
result = np.strings.less_equal(str1, str2)

# Print the result
print("Is 'apple' <= 'banana'? :", result)

Output:

Is 'apple' <= 'banana'? : True

2. Comparing Arrays of Strings

We compare element-wise in two string arrays.

import numpy as np

# Define two arrays of strings
arr1 = np.array(["apple", "cherry", "banana"])
arr2 = np.array(["banana", "apple", "cherry"])

# Compare element-wise
result = np.strings.less_equal(arr1, arr2)

# Print the result
print("Array 1:", arr1)
print("Array 2:", arr2)
print("Comparison result:", result)

Output:

Array 1: ['apple' 'cherry' 'banana']
Array 2: ['banana' 'apple' 'cherry']
Comparison result: [ True False  True]

3. Broadcasting a Single String Against an Array

We compare a single string with each element in an array.

import numpy as np

# Define a single string and an array of strings
single_str = "banana"
str_array = np.array(["apple", "banana", "cherry"])

# Compare the single string with each array element
result = np.strings.less_equal(single_str, str_array)

# Print the result
print("Single String:", single_str)
print("String Array:", str_array)
print("Comparison result:", result)

Output:

Single String: banana
String Array: ['apple' 'banana' 'cherry']
Comparison result: [False  True  True]

4. Using the where Parameter

Using a mask to selectively compare only certain elements.

import numpy as np

# Define two arrays of strings
arr1 = np.array(["apple", "cherry", "banana"])
arr2 = np.array(["banana", "apple", "cherry"])

# Define a mask (only compare where mask is True)
mask = np.array([True, False, True])

# Compare with the where parameter
result = np.strings.less_equal(arr1, arr2, where=mask)

# Print the result
print("Comparison result with mask:", result)

Output:

Comparison result with mask: [ True False  True]

The comparison is only performed for elements where mask=True. Other values remain unchanged.