This can be done using numpy.char.add. Here is an example:
>>> import numpy as np
>>> a1 = np.array(['a', 'b'])
>>> a2 = np.array(['E', 'F'])
>>> np.char.add(a1, a2)
array(['aE', 'bF'],
dtype='<U2')
(This was previously known as numpy.core.defchararray.add, and that name is still usable, but numpy.char.add is the preferred alias now.)
There are other useful string operations available for NumPy data types.
Answer from Mike T on Stack Overflow Top answer 1 of 7
83
This can be done using numpy.char.add. Here is an example:
>>> import numpy as np
>>> a1 = np.array(['a', 'b'])
>>> a2 = np.array(['E', 'F'])
>>> np.char.add(a1, a2)
array(['aE', 'bF'],
dtype='<U2')
(This was previously known as numpy.core.defchararray.add, and that name is still usable, but numpy.char.add is the preferred alias now.)
There are other useful string operations available for NumPy data types.
2 of 7
15
You can use the chararray subclass to perform array operations with strings:
a1 = np.char.array(['a', 'b'])
a2 = np.char.array(['E', 'F'])
a1 + a2
#chararray(['aE', 'bF'], dtype='|S2')
another nice example:
b = np.array([2, 4])
a1*b
#chararray(['aa', 'bbbb'], dtype='|S4')
w3resource
w3resource.com › python-exercises › numpy › python-numpy-string-exercise-1.php
NumPy: Concatenate element-wise two arrays of string - w3resource
August 30, 2025 - # Importing the necessary library import numpy as np # Creating two NumPy arrays with string elements x1 = np.array(['Python', 'PHP'], dtype=np.str) x2 = np.array([' Java', ' C++'], dtype=np.str) # Displaying the contents of Array1 print("Array1:") print(x1) # Displaying the contents of Array2 print("Array2:") print(x2) # Concatenating the strings element-wise between x1 and x2 using np.char.add function new_array = np.char.add(x1, x2) # Displaying the new array formed by concatenating elements from x1 and x2 print("New array:") print(new_array)
Top answer 1 of 3
10
It's not hard to do outside of numpy:
>>> import numpy as np
>>> pic = np.array([ 'H','e','l','l','o','W','o','r','l','d']).reshape(2,5)
>>> pic
array([['H', 'e', 'l', 'l', 'o'],
['W', 'o', 'r', 'l', 'd']],
dtype='|S1')
>>> '\n'.join([''.join(row) for row in pic])
'Hello\nWorld'
There is also the np.core.defchararray module which has "goodies" for working with character arrays -- However, it states that these are merely wrappers around the python builtin and standard library functions so you'll probably not get any real speedup by using them.
2 of 3
8
You had the right ideas there. Here's a vectorized NumPythonic implementation trying to go along those ideas -
# Create a separator string of the same rows as input array
separator_str = np.repeat(['\n'], pic.shape[0])[:,None]
# Concatenate these two and convert to string for final output
out = np.concatenate((pic,separator_str),axis=1).tostring()
Or a one-liner with np.column_stack -
np.column_stack((pic,np.repeat(['\n'], pic.shape[0])[:,None])).tostring()
Sample run -
In [123]: pic
Out[123]:
array([['H', 'e', 'l', 'l', 'o'],
['W', 'o', 'r', 'l', 'd']],
dtype='|S1')
In [124]: np.column_stack((pic,np.repeat(['\n'], pic.shape[0])[:,None])).tostring()
Out[124]: 'Hello\nWorld\n'
NumPy
numpy.org › doc › stable › reference › generated › numpy.concatenate.html
numpy.concatenate — NumPy v2.5 Manual
Concatenate function that preserves input masks. ... Split an array into multiple sub-arrays of equal or near-equal size.
GeeksforGeeks
geeksforgeeks.org › python › element-wise-concatenation-of-two-numpy-arrays-of-string
Element-wise concatenation of two NumPy arrays of string - GeeksforGeeks
January 4, 2022 - Printing first name array: ['Geeks'] Printing last name array: ['forGeeks'] Printing concatenate array as full name: ['GeeksforGeeks'] Example 2: String array with multiple elements. ... # importing library numpy as np import numpy as np # creating array as first_name first_name = np.array(['Akash', 'Ayush', 'Diksha', 'Radhika'], dtype = np.str) print("Printing first name array:") print(first_name) # creating array as last name last_name = np.array(['Kumar', 'Sharma', 'Tewari', 'Pegowal'], dtype = np.str) print("Printing last name array:") print(last_name) # concat first_name and last_name # into new array named as full_name full_name = np.char.add(first_name, last_name) print("\nPrinting concatenate array as full name:") print(full_name)
w3resource
w3resource.com › numpy › string-operations › add.php
NumPy: numpy.char.add() function - w3resource
April 28, 2026 - The numpy.char.add() function is used to create element-wise string concatenation for two given arrays of str or unicode.
Programiz
programiz.com › python-programming › numpy › methods › concatenate
NumPy concatenate()
import numpy as np array1 = np.array([[0, 1], [2, 3]]) array2 = np.array([[10, 11], [12, 13]]) # change elements of the concatenated array to string concatenatedArray = np.concatenate((array1, array2), dtype = str) print(concatenatedArray)
TutorialsPoint
tutorialspoint.com › return-element-wise-string-concatenation-for-two-arrays-of-string-in-numpy
Return element-wise string concatenation for two arrays of string in Numpy
To return element-wise string concatenation for two arrays of string, use the numpy.char.add() method in Python Numpy.
TutorialsPoint
tutorialspoint.com › element-wise-concatenation-of-two-numpy-arrays-of-string
Element wise concatenation of two NumPy arrays of string
The resulting array, result, contains the concatenated strings. import numpy as np arr1 = np.array(['apple', 'banana', 'cherry']) arr2 = np.array([' pie', ' split', ' tart']) result = np.core.defchararray.add(arr1, arr2) print(result)
Educative
educative.io › answers › what-is-the-numpycharjoin-function-from-numpy-in-python
What is the numpy.char.join() function from NumPy in Python?
The char.join() function in Python’s NumPy library is used to concatenate an array of strings in a given sequence seq.
Top answer 1 of 3
9
Try np.apply_along_axis
arr_list = [strings1, strings2, strings3]
arr_out = np.apply_along_axis(' '.join, 0, arr_list)
In [35]: arr_out
Out[35]: array(['a d g', 'b e h', 'c f i'], dtype='<U5')
2 of 3
2
You could use a for loop to help you achieve this:
import numpy as np
strings1 = np.array(["a", "b", "c"], dtype=np.str)
strings2 = np.array(["d", "e", "f"], dtype=np.str)
strings3 = np.array(["g", "h", "i"], dtype=np.str)
Create a list of your strings:
strings=[strings1, strings2, strings3]
Create an empty list:
list_for_new_array=[]
For loop to iterate through each array in strings, and create a list of strings containing array items separated by a space:
for string in strings:
i=""
for item in string:
i+=item+" "
list_for_new_array.append(i)
Create new array with list created in for loop:
new_array= np.array(list_for_array, dtype='<U5')
i2tutorials
i2tutorials.com › home › numpy tutorial › numpy – string functions
NumPy - String Functions | i2tutorials
April 29, 2019 - >>> x=np.array(("iam a numpy")) >>> y=np.array(("program")) >>> np.char.add(x,y) array('iam a numpyprogram',dtype='<U18') multiply: This will return element-wise string multiple concatenation.
NumPy
numpy.org › doc › 1.25 › reference › routines.char.html
String operations — NumPy v1.25 Manual
The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.
GeeksforGeeks
geeksforgeeks.org › numpy-concatenate-function-python
numpy.concatenate() function in Python - GeeksforGeeks
May 13, 2025 - Example #1 : In this example we can see that by using np.ma.concatenate() method, we are a ... The add() method of the char class in the NumPy module is used for element-wise string concatenation for two arrays of str or unicode.
Top answer 1 of 4
3
You have to convert the integer array to strings:
import numpy as np
out = np.core.defchararray.add('User', np.arange(10).astype(str))
print(out)
# ['User0' 'User1' 'User2' 'User3' 'User4' 'User5' 'User6' 'User7' 'User8'
# 'User9']
2 of 4
2
How about something like this:
np.array(['User{}'.format(i) for i in range(10)])
NumPy
numpy.org › doc › stable › reference › routines.char.html
Legacy fixed-width string functionality — NumPy v2.4 Manual
The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.
Programiz
programiz.com › python-programming › numpy › string-functions
NumPy String Functions (With Examples)
In this example, we have defined two NumPy arrays: array1 and array2, with string elements 'iphone: ' and 'price: ' and '15' and '$900' respectively. We then used np.char.add(array1, array2) to concatenate the elements of array1 and array2 element-wise.
NumPy
numpy.org › doc › 2.1 › reference › generated › numpy.char.join.html
numpy.char.join — NumPy v2.1 Manual
Return a string which is the concatenation of the strings in the sequence seq. Calls str.join element-wise. Parameters: separray-like, with StringDType, bytes_, or str_ dtype · seqarray-like, with StringDType, bytes_, or str_ dtype · Returns: outndarray · Output array of StringDType, bytes_ or str_ dtype, depending on input types ·
Python Guides
pythonguides.com › python-concatenate-arrays
How to Concatenate Arrays in Python
August 20, 2025 - This is a real-world scenario where array concatenation makes reporting and analysis much easier. Most of the time, I find myself using NumPy’s concatenate() or hstack() because they are fast and reliable.