Are you looking to become a professional Python developer? Or are you interested in programming but don’t know where to start? Python is a beginner-friendly and versatile programming language. Python is used in every area of software development. Knowing Python is a great in-demand skill in the job market. For instance, nearly every Machine Learning …
8 Best Python Courses with Certifications [in 2022] Read More »
To remove an element from a NumPy array: Specify the index of the element to remove. Call the numpy.delete() function on the array for the given index. For example: Output: This is the quick answer. However, there is a lot more when it comes to removing elements from a NumPy array. In this guide, you …
numpy.delete: How to Remove Elements from a NumPy Array Read More »
A NumPy array does not have a built-in append method. Instead, to append elements to a NumPy array, use a separate numpy.append() function. For example: Output: Notice how numpy.append() creates a new copy of the original array. It does not directly append values to it. In this guide, you learn: How appending NumPy arrays work. …
numpy.append(): How to Add Elements to a NumPy Array Read More »
To create an empty NumPy array: Specify the shape of the array. Call the numpy.empty() function. For instance, let’s create an empty array with no elements: Output: However, creating an array without elements rarely makes any sense. Instead, you should know and specify the shape of the final array in advance. For instance, let’s create …
In NumPy, -1 in reshape(-1) refers to an unknown dimension that the reshape() function calculates for you. It is like saying: “I will leave this dimension for the reshape() function to determine”. A common use case is to flatten a nested array of an unknown number of elements to a 1D array. For example: But …
In NumPy, the @ operator means matrix multiplication. For instance, let’s multiply two NumPy arrays that represent 2 x 2 matrices: Output: If you are familiar with matrix multiplication, I’m sure this answers your questions. However, if you do not know what matrix multiplication means, or if you are interested in how the @ operator …
NumPy @ Operator: Matrix Multiplication in Python Read More »
To transpose a matrix with NumPy, call the transpose() method. For instance: Output: If you are in a hurry, I’m sure this quick answer is enough. To learn more about matrix transpose, keep on reading. What Is the Transpose of a Matrix The transpose of a matrix is another matrix where the matrix is flipped …
To concatenate two arrays with NumPy: Import numpy. Put two arrays in a list. Call numpy.concatenate() on the list of arrays. For instance: Output: This is a quick answer. To learn more ways to concatenate arrays and about their efficiency, please, stick around. 4 Ways to Concatenate 1D NumPy Arrays There are four built-in ways …
To check if two NumPy arrays A and B are equal: Use a comparison operator (==) to form a comparison array. Check if all the elements in the comparison array are True. For example: This is the easiest approach to comparing two arrays. But this approach is not 100% reliable. Instead, you should consider using …
Data manipulation is an integral part of data preparation. This is especially so since data collection leaves room for duplication and data omission. There are various ways and coding languages for cleaning and manipulating data, but Python is arguably one of the best languages for this. Cleaning and manipulation of data ensure that the data …
