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Python numpy.char.add() Method (With Examples)
By IncludeHelp Last updated : November 28, 2023
Python numpy.char.add() Method
The add() method is a built-in method of char class in the numpy module, it is used to concatenate two arrays of string or Unicode element-wise.
Module
The following module is required to use the add() method:
import numpy as np
Syntax
The following is the syntax of the add() method:
char.add(arr1, arr2)
Parameter(s)
The following are the parameter(s):
- arr1: The first array-like value which can be string, array of string, or Unicode.
- arr2: The second array-like value which can be string, array of string, or Unicode.
Return Value
The return type of add() method is <class 'numpy.ndarray'>, it returns element-wise concatenated array of bytes_ or str_.
Example 1: Using single element strings
# Importing numpy module
import numpy as np
# Creating two arrays with
# single element string
arr1 = ["Include"]
arr2 = ["Help"]
# Printing the arrays
print("arr1: ", arr1)
print("arr2: ", arr2)
# Using char.add() method
result = np.char.add(arr1, arr2)
print("The concatenated array is (result):", result)
print("The type of the result is:", type(result))
Output
The output of the above example is:
arr1: ['Include']
arr2: ['Help']
The concatenated array is (result): ['IncludeHelp']
The type of the result is: <class 'numpy.ndarray'>
Example 2: Using array of strings
# Importing numpy module
import numpy as np
# Creating two arrays with
# arrays of strings
arr1 = ["Hello", "Hi", "Hey", "Include"]
arr2 = ["World", "Earth", "Sun", "Help"]
# Printing the arrays
print("arr1: ", arr1)
print("arr2: ", arr2)
# Using char.add() method
result = np.char.add(arr1, arr2)
print("\nThe concatenated array is (result):\n", result)
print("\nThe type of the result is:", type(result))
Output
The output of the above example is:
arr1: ['Hello', 'Hi', 'Hey', 'Include']
arr2: ['World', 'Earth', 'Sun', 'Help']
The concatenated array is (result):
['HelloWorld' 'HiEarth' 'HeySun' 'IncludeHelp']
The type of the result is: <class 'numpy.ndarray'>
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