NumPy Asarray Function

Introduction

In data analysis and scientific computing, the numpy library is a popular tool for faster mathematical operation. The numpy.asarray() function is used to convert the input data into a NumPy array object. The function can accept any existing data like Lists, Tuples, and ndarrays and convert it into an array. This lab will provide the step-by-step guide to using the numpy.asarray() function with examples.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

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Install NumPy

First, we need to install the NumPy module using pip. If you don't have pip already, you can install it using the terminal.

!pip install numpy

Import Required Libraries

Next, we have to import the required NumPy library into our Python environment.

import numpy as np

Convert Python List To Numpy Array

Here's the code snippet to convert a Python list into a NumPy array.

my_list = [1, 2, 4, 5, 8, 10]
np.asarray(my_list)

Create NumPy Array From Python Tuple

In this step, we will convert a Python tuple into a NumPy array using the numpy.asarray() function.

inp = (10, 9, 1, 2, 3, 4, 5, 6, 7, 8)
a = np.asarray(inp)
print("The output is:")
print(a)
print("The datatype of output is:")
print(type(a))

Create NumPy Array Using More Than One List

In this step, we will create a NumPy array using more than one list.

l = [[1, 2, 3, 4, 5, 6, 7], [8, 9], [12, 34, 45]]
a = np.asarray(l, dtype=object)
print("The data type of output is:")
print(type(a))
print("The output array is:")
print(a)

Summary

This lab demonstrated the usage of the numpy.asarray() function. The function can accept input data that is in the form of lists, tuples of tuples, list of tuples, tuples of lists, or ndarrays and convert them into a NumPy array object. NumPy provides a lot of useful functions for working with arrays and matrices, and the numpy.asarray() function is a great tool to have when you're working with Python sequences and need to convert them into a NumPy array.