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NumPy: Convert a list and tuple into arrays

NumPy Array Object Exercises, Practice and Solution: Write a NumPy program to convert a list and tuple into arrays.

NumPy: Convert a list and tuple into arrays

Last update on August 19 2022 21:50:48 (UTC/GMT +8 hours)

NumPy: Array Object Exercise-11 with Solution

Write a NumPy program to convert a list and tuple into arrays.

Sample Solution:-NumPy Code:

import numpy as np

my_list = [1, 2, 3, 4, 5, 6, 7, 8]

print("List to array: ")

print(np.asarray(my_list))

my_tuple = ([8, 4, 6], [1, 2, 3])

print("Tuple to array: ")

print(np.asarray(my_tuple))

Sample Output: List to array: [1 2 3 4 5 6 7 8] Tuple to array: [[8 4 6] [1 2 3]]

Python-Numpy Code Editor:Have another way to solve this solution? Contribute your code (and comments) through Disqus.Previous: Write a NumPy program to create a 8x8 matrix and fill it with a checkerboard pattern.Next: Write a NumPy program to append values to the end of an array.

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How to convert a list and tuple into NumPy arrays?

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How to convert a list and tuple into NumPy arrays?

Difficulty Level : Medium

Last Updated : 29 Aug, 2020

Read Discuss Courses Practice Video

In this article, let’s discuss how to convert a list and tuple into arrays using NumPy. NumPy provides various methods to do the same. Let’s discuss them

Method 1: Using numpy.asarray()

It converts the input to an array. The input may be lists of tuples, tuples, tuples of tuples, tuples of lists and ndarray.

Syntax:

numpy.asarray( a, type = None, order = None )

Example:

Python3

import numpy as np # list

list1 = [3, 4, 5, 6]

print(type(list1)) print(list1) print() # conversion

array1 = np.asarray(list1)

print(type(array1)) print(array1) print() # tuple

tuple1 = ([8, 4, 6], [1, 2, 3])

print(type(tuple1)) print(tuple1) print() # conversion

array2 = np.asarray(tuple1)

print(type(array2)) print(array2)

Output:

[3, 4, 5, 6] [3 4 5 6]

([8, 4, 6], [1, 2, 3])

[[8 4 6] [1 2 3]]

Method 2: Using numpy.array()

It creates an array.

Syntax: numpy.array( object, dtype  = None, *, copy = True, order = ‘K’, subok = False, ndmin = 0 )Parameters:object: array-likedtype: data-type, optional ( The desired data-type for the array. If not given, then the type will be determined as the minimum type required to hold the objects in the sequence. )copy: bool, optional ( If true (default), then the object is copied. Otherwise, a copy will only be made if __array__ returns a copy, if obj is a nested sequence, or if a copy is needed to satisfy any of the other requirements (dtype, order, etc.). )order: {‘K’, ‘A’, ‘C’, ‘F’}, optional ( same as above )subok: bool, optional ( If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default). )ndmin: int, optional ( Specifies the minimum number of dimensions that the resulting array should have. Ones will be pre-pended to the shape as needed to meet this requirement. )Returns: ndarray ( An array object satisfying the specified requirements. )Example:

Python3

import numpy as np # list list1 = [1, 2, 3] print(type(list1)) print(list1) print() # conversion

array1 = np.array(list1)

print(type(array1)) print(array1) print() # tuple

tuple1 = ((1, 2, 3))

print(type(tuple1)) print(tuple1) print() # conversion

array2 = np.array(tuple1)

print(type(array2)) print(array2) print()

# list, array and tuple

array3 = np.array([tuple1, list1, array2])

print(type(array3)) print(array3)

Output:

[1, 2, 3]

[1 2 3]

(1, 2, 3)

[1 2 3]

[[1 2 3]

[1 2 3]

[1 2 3]]

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Convert Python List to NumPy Arrays

Convert Python List to NumPy Arrays with python, tutorial, tkinter, button, overview, entry, checkbutton, canvas, frame, environment set-up, first python program, operators, etc.

Convert Python List to NumPy Arrays

Convert Python List to NumPy Arrays Introduction

In Python, a list is a linear data structure that may store heterogeneous elements. It does not need to be defined and can shrink and expand as needed. On the other end, a NumPy array is a data structure that may store homogenous elements. It is implemented in Python using the NumPy library. This library is very efficient in handling multi-dimensional arrays. It is also very efficient in handling a huge number of data elements. NumPy arrays use less memory than List data structures. Both the NumPy array and the list can be identified by their index value.

The NumPy library provides two methods for converting lists to arrays in Python.

Using numpy.array()

Using numpy.asarray()

Method 1: Using numpy.array()

In Python, the simplest way to convert a list to a NumPy array is with numpy.array() function. It takes an argument and returns a NumPy array. It creates a new copy in memory.

Program 1

# importing library of the array in python

import numpy

# initilizing elements of the list

a = [1, 2, 3, 4, 5, 6, 7, 8, 9]

# converting elements of the list into array elements

arr = numpy.array(a)

# displaying elements of the list

print ("List: ", a)

# displaying elements of the array

print ("Array: ", arr)

Output:

List: [1, 2, 3, 4, 5, 6, 7, 8, 9]

Array: [1 2 3 4 5 6 7 8 9]

Method 2: Using numpy.asarray()

In Python, the second method is numpy.asarray() function that converts a list to a NumPy array. It takes an argument and converts it to the NumPy array. It does not create a new copy in memory. In this, all changes made to the original array are reflected on the NumPy array.

Program 2

# importing library of the array in python

import numpy

# initilizing elements of the list

a = [1, 2, 3, 4, 5, 6, 7, 8, 9]

# converting elements of the list into array elements

arr = numpy.asarray(a)

# displaying elements of the list

print ("List:", a)

# displaying elements of the array

print ("Array: ", arr)

Output:

List: [1, 2, 3, 4, 5, 6, 7, 8, 9]

Array: [1 2 3 4 5 6 7 8 9]

Program 3

# importing library of the NumPy array in python

import numpy

# initilizing elements of the list

lst = [1, 2, 3, 4, 5, 6, 7, 8, 9]

# converting elements of the list into array elements

arr = numpy.asarray(lst)

# displaying elements of the list

print ("List:", lst)

# displaying elements of the array

print ("arr: ", arr)

# made another array out of arr using asarray function

arr1 = numpy.asarray(arr)

#displaying elements of the arr1 before the changes made

print("arr1: " , arr1)

#change made in arr1

arr1[3] = 23

#displaying arr1 , arr , list after the change has been made

print("lst: " , lst)

print("arr: " , arr)

print("arr1: " , arr1)

Output:

List: [1, 2, 3, 4, 5, 6, 7, 8, 9]

arr: [1 2 3 4 5 6 7 8 9]

arr1: [1 2 3 4 5 6 7 8 9]

lst: [1, 2, 3, 4, 5, 6, 7, 8, 9]

arr: [ 1 2 3 23 5 6 7 8 9]

arr1: [ 1 2 3 23 5 6 7 8 9]

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