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NumPy Array Functions

Last Updated : 23 Jul, 2025
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NumPy array functions are a set of built-in operations provided by the NumPy library that allow users to perform various tasks on arrays. With NumPy array functions, you can create, reshape, slice, sort, perform mathematical operations, and much more—all while taking advantage of the library's speed and efficiency.

Table of Content

This article explores some of the most important NumPy array functions with examples to help you harness their power.

Array Creation Functions

  • np.array(): Converts a Python list, tuple, or sequence into an array.
Python 
import numpy as np
arr = np.array([1, 2, 3])
print(arr)
Python 
import numpy as np 
zeros_array = np.zeros((2, 3))
print(zeros_array)
  • np.ones(): Creates an array filled with ones.
Python 
import numpy as np
ones_array = np.ones((3, 2))
print(ones_array)
  • np.arange(): Generates an array with values in a specified range.
Python 
import numpy as np
range_array = np.arange(0, 10, 2) 
print(range_array)
  • np.linspace() : Generates an array of evenly spaced numbers over a specified range.
Python 
import numpy as np
linear_array = np.linspace(0, 1, 5)  
print(linear_array)
Python 
import numpy as np 
random_array = np.random.rand(2, 3) 
print(random_array)

Array Manipulation Functions

Python 
import numpy as np 
reshaped = np.reshape(np.arange(6), (2, 3))
print(reshaped)
  • np.flatten(): Flattens a multi-dimensional array into one dimension.
Python 
import numpy as np
flattened = reshaped.flatten()
print(flattened)
Python 
import numpy as np
transposed = reshaped.T
print(transposed)
Python 
import numpy as np
a = np.array([1, 2])
b = np.array([3, 4])
concatenated = np.concatenate((a, b))
print(concatenated)

Mathematical and Statistical Functions

  • np.sum() : Computes the sum of array elements.
Python 
import numpy as np
array = np.array([1, 2, 3])
total = np.sum(array) 
print(total)
  • np.mean(): Computes the mean of array elements.
Python 
import numpy as np
mean_value = np.mean(array)  
print(mean_value)
Python 
import numpy as np
max_val = np.max(array) 
min_val = np.min(array) 
print(max_val)
print(min_value)
  • np.sqrt(): Computes the square root of each element in an array.
Python 
import numpy as np
sqrt_array = np.sqrt(array)
print(sqrt_array)


Indexing and Slicing Functions

  • Indexing: Access specific elements
Python 
import numpy as np
array = np.array([1, 2, 3, 4])
element = array[2]  
print(element)
  • Slicing: Access subsets of arrays
Python 
import numpy as np
subset = array[1:3]  
print(subset)

Sorting and Searching Functions

Python 
import numpy as np
sorted_array = np.sort(np.array([3, 1, 2]))
print(sorted_array)
Python 
import numpy as np
indices = np.argsort(np.array([3, 1, 2]))
print(indices)
  • np.where(): Returns the indices of elements that satisfy a condition.
Python 
import numpy as np
array = np.array([1, 2, 3, 4])
indices = np.where(array > 2)  
print(indices)

Input/Output Functions

Python 
import numpy as np
np.save('array.npy', array)
loaded_array = np.load('array.npy')
print(loaded array)
  • np.savetxt() and np.loadtxt() : Save and load arrays in text format.
Python 
import numpy as np 
np.savetxt('array.txt', array)
loaded_array = np.loadtxt('array.txt')
print(loaded_array)

Other Different Methods of NumPy Array

all()diag()hypot()ones_like()
any()diagflat()absolute()full_like()
take()diag_indices()ceil()sin()
put()asmatrix()floor()cos()
apply_along_axis()bmat()degrees()tan()
apply_over_axes()eye()radians()sinh()
argmin()roll()npv()cosh()
argmax()identity()fv()tanh()
nanargmin()arange()pv()arcsin()
nanargmax()place()power()arccos()
amax()extract()float_power()exp()
amin()compress()log()exp2()
insert()rot90()log1()fix()
delete()tile()log2()logical_or()
append()reshape()log10()logical_and()
around()ravel()dot()logical_not()
flip()isinf()vdot()logical_xor()
fliplr()isrealobj()trunc()array_equal()
flipud()isscalar()divide()array_equiv()
triu()isneginf()floor_divide()arctan2()
tril()isposinf()true_divide()equal()
tri()iscomplex()random.rand()not_equal()
empty()isnan()random.randn()less()
empty_like()iscomplexobj()ndarray.flat()less_equal()
zeros()isreal()expm1()greater()
zeros_like()isfinite()bincount()greater_equal()
ones()isfortran()rint()prod()
arctan()cbrt()square()

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