NumPy strings.strip() – Remove Leading and Trailing Characters

NumPy strings.strip()

The numpy.strings.strip() function removes leading and trailing characters from each element in an array-like structure. By default, it removes whitespace, but a custom set of characters can be specified.

Syntax

numpy.strings.strip(a, chars=None)

Parameters

Parameter	Type	Description
a	array-like, with StringDType, bytes_, or str_ dtype	The input array containing strings to be stripped.
chars	scalar with the same dtype as a, optional	Specifies the set of characters to be removed. If None, it removes whitespace.

Return Value

Returns an ndarray of the same type as the input, with leading and trailing characters removed based on the specified chars argument.

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Examples

1. Stripping Whitespace from Strings

By default, strings.strip() removes whitespace from the beginning and end of each string.

import numpy as np

# Define an array of strings with leading and trailing spaces
fruits = np.array(["  apple  ", "  banana", "cherry   "], dtype="str")

# Strip whitespace from both ends
stripped_fruits = np.strings.strip(fruits)

# Print the results
print("Original:", fruits)
print("Stripped:", stripped_fruits)

Output:

Original: ['  apple  ' '  banana' 'cherry   ']
Stripped: ['apple' 'banana' 'cherry']

2. Stripping Specific Characters

You can specify a set of characters to remove instead of whitespace.

import numpy as np

# Define an array of strings with extra characters
fruits = np.array(["--apple--", "**banana**", "!!cherry!!"], dtype="str")

# Strip specified characters
stripped_fruits = np.strings.strip(fruits, "-*!")

# Print the results
print("Original:", fruits)
print("Stripped:", stripped_fruits)

Output:

Original: ['--apple--' '**banana**' '!!cherry!!']
Stripped: ['apple' 'banana' 'cherry']

3. Stripping Numbers from Strings

The function removes any combination of characters specified, not just prefixes or suffixes.

import numpy as np

# Define an array of strings with numbers at different positions
fruits = np.array(["123apple321", "456banana789", "000cherry000"], dtype="str")

# Strip numbers from both ends
stripped_fruits = np.strings.strip(fruits, "0123456789")

# Print the results
print("Original:", fruits)
print("Stripped:", stripped_fruits)

Output:

Original: ['123apple321' '456banana789' '000cherry000']
Stripped: ['apple' 'banana' 'cherry']

4. Stripping Mixed Characters

Combining various characters like spaces, special characters, and numbers to remove from strings.

import numpy as np

# Define an array of strings with mixed unwanted characters
fruits = np.array(["  *123apple321*  ", "**banana!@#", "000  cherry  000"], dtype="str")

# Strip spaces, numbers, and special characters
stripped_fruits = np.strings.strip(fruits, " *0123456789!@#")

# Print the results
print("Original:", fruits)
print("Stripped:", stripped_fruits)

Output:

Original: ['  *123apple321*  ' '**banana!@#' '000  cherry  000']
Stripped: ['apple' 'banana' 'cherry']