Python NumPy Tutorial: Get Length of Array in Python

Introduction

NumPy is a popular Python library used for numerical computing. It provides support for multi-dimensional arrays and matrices, along with a wide range of mathematical functions to operate on these arrays. In this tutorial, we will learn how to get the length of an array in Python using NumPy.

What is NumPy?

NumPy stands for Numerical Python, and it is a Python library that is used for working with arrays. It also has functions for working in domain of linear algebra, Fourier transform, and matrices. NumPy was created in 2005 by Travis Olliphant.

NumPy provides an efficient way to store and manipulate large arrays of numerical data in Python. It is designed to be fast and efficient, making it ideal for scientific computing and data analysis.

One of the most important features of NumPy is its ndarray object, which is a multidimensional array that can store homogeneous data types. This means that all the elements in the array must be of the same data type, such as integers or floats.

To use NumPy in your Python code, you ne

Getting Started with NumPy

NumPy is a popular Python package used for scientific computing. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. NumPy is an essential tool for data analysis, machine learning, and other scientific applications in Python.

To use NumPy in your Python project, you need to first install it. You can do this by running the following command in your terminal:


pip install numpy

Once you have installed NumPy, you can import it into your Python script using the following line of code:


import numpy as np

This line of code imports NumPy and gives it an alias “np”. This is a common convention used by many developers when working with NumPy.

Now that we have imported NumPy, let’s create an array and get its length. In NumPy, arrays are represented using the `ndarray` class. Here’s an example:


import numpy as np

arr = np.array([1, 2, 3, 4, 5])

print(len(arr))

In this example, we created an array `arr` containing five elements. We then used the built-in `len()` function to get the length of the array and printed it to the console. The output will be:


5

As you can see, getting the length of an array in NumPy is as simple as calling the `len()` function on the array object.

How to Create a NumPy Array?

NumPy is a popular Python library for scientific computing. It provides a powerful array object that can hold homogeneous data, as well as tools for working with these arrays. In this section, we will discuss how to create a NumPy array in Python.

To create a NumPy array, you first need to import the NumPy library. You can do this by using the following command:


import numpy as np

Once you have imported the NumPy library, you can create an array using the `np.array()` function. This function takes a sequence (like a list or tuple) and converts it into an array.

Here’s an example of how to create a one-dimensional array:


a = np.array([1, 2, 3])
print(a)

Output:

[1 2 3]

You can also create multi-dimensional arrays using nested lists. Here’s an example of how to create a two-dimensional array:


b = np.array([[1, 2], [3, 4]])
print(b)

Output:

[[1 2]
[3 4]]

NumPy also provides several functions for creating arrays with specific properties. For example, you can create an array of zeros or ones using the `np.zeros()` and `np.ones()` functions respectively. Here’s an example of how to create a three-dimensional array of zeros:


c = np.zeros((2, 3, 4))
print(c)

Output:

[[[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]]

[[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]]]

In this example, we created an array with dimensions `(2, 3, 4)`. The first dimension has length 2, the second dimension has length 3, and the third dimension has length 4.

NumPy also provides functions for creating arrays with a range of values using `np.arange()` or `np.linspace()`. Here’s an example of how to create a one-dimensional array with values ranging from 0 to 9:


d = np.arange(10)
print(d)

Output:

[0 1 2 3 4 5 6 7 8 9]

Overall, NumPy provides a wide range of functions for creating arrays in Python. By using these functions, you can quickly and easily create arrays of different shapes and sizes to suit your needs.

Get Length of a NumPy Array

When working with NumPy arrays in Python, we often need to determine the length of an array. In this section, we’ll cover three different ways to get the length of a NumPy array.

Using the len() function

The easiest and most straightforward way to get the length of a NumPy array is by using the built-in Python function `len()`. This function returns the number of elements in an object, including the elements in a NumPy array. Here’s an example:


import numpy as np

# create a 1D NumPy array
arr = np.array([1, 2, 3, 4, 5])

# get the length of the array using len()
length = len(arr)

print(length) # output: 5

As you can see, we created a one-dimensional NumPy array called `arr` and then used the `len()` function to get its length. The output is `5`, which is the number of elements in the array.

Using the shape attribute

Another way to get the length of a NumPy array is by using its `shape` attribute. The `shape` attribute returns a tuple that contains the dimensions of the array. For a one-dimensional array, this tuple will only have one element, which represents the size of that dimension. Here’s an example:


import numpy as np

# create a 1D NumPy array
arr = np.array([1, 2, 3, 4, 5])

# get the shape of the array
shape = arr.shape

# get the length by accessing the first element of the shape tuple
length = shape[0]

print(length) # output: 5

In this example, we created a one-dimensional NumPy array called `arr` and then used its `shape` attribute to get a tuple containing the dimensions of the array. Since `arr` is one-dimensional, the shape tuple only has one element. We then accessed the first element of the tuple to get the length of the array, which is `5`.

Using the size attribute

Finally, we can also get the length of a NumPy array by using its `size` attribute. The `size` attribute returns the total number of elements in the array. Here’s an example:


import numpy as np

# create a 1D NumPy array
arr = np.array([1, 2, 3, 4, 5])

# get the size of the array
size = arr.size

print(size) # output: 5

In this example, we created a one-dimensional NumPy array called `arr` and then used its `size` attribute to get the total number of elements in the array. Since `arr` has five elements, its size is also `5`.

In conclusion, there are three ways to get the length of a NumPy array in Python: using the built-in function `len()`, using the `shape` attribute and accessing its first element, or using the `size` attribute. Choose whichever method you find most convenient for your particular use case.

Conclusion

In this tutorial, we learned how to get the length of an array in Python using the len() function. We also explored how to create arrays using the NumPy library and how to perform some basic operations on them.

Knowing the length of an array is a crucial aspect of working with arrays in Python, as it helps us understand how many elements are present in an array and allows us to access or manipulate elements accordingly. The len() function is a simple yet powerful tool that can help us achieve this.

In addition, we saw how NumPy provides a wide range of functionalities for working with arrays, such as creating arrays with specific shapes and sizes, performing element-wise operations, and calculating statistics on arrays.

Overall, understanding these concepts can greatly enhance your ability to work with arrays in Python and enable you to build more robust and efficient code. So go ahead and start exploring the world of NumPy arrays today!
Interested in learning more? Check out our Introduction to Python course!


How to Become a Data Scientist PDF

Your FREE Guide to Become a Data Scientist

Discover the path to becoming a data scientist with our comprehensive FREE guide! Unlock your potential in this in-demand field and access valuable resources to kickstart your journey.

Don’t wait, download now and transform your career!


Pierian Training
Pierian Training
Pierian Training is a leading provider of high-quality technology training, with a focus on data science and cloud computing. Pierian Training offers live instructor-led training, self-paced online video courses, and private group and cohort training programs to support enterprises looking to upskill their employees.

You May Also Like

Deep Learning, Tutorials

ChatGPT API Python Guide

Introduction Welcome to this tutorial on using the ChatGPT API from OpenAI with Python! ChatGPT is a state-of-the-art language model that can generate human-like responses to text-based inputs. With its ability to understand context and generate coherent responses, ChatGPT has become a popular tool for chatbots and conversational agents in a variety of industries. In […]

Python Basics, Tutorials

Using Min Function in Python

Introduction Python is a powerful programming language that can be used for a variety of tasks, including data analysis and manipulation. One common task in data analysis is finding the smallest number in a list, which one can do in a variety of ways, including using the Python min function. In this tutorial, we will […]

Python Basics, Tutorials

Understanding the Max Python Function

Introduction Lists are an important data structure in Python programming. They allow us to store a collection of values in a single variable. Sometimes we need to find the maximum value in a list, in this blog post we’ll cover how to use the max python function. This can be useful in many situations, for […]