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 to Append to a […]
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To create an empty NumPy array: 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 an empty 2D array: Output (contains arbitrary values due to
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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
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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
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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
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To concatenate two arrays with NumPy: 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 concatenate arrays in NumPy. Before introducing these, it is important you understand that all
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To check if two NumPy arrays A and B are equal: For example: This is the easiest approach to comparing two arrays. But this approach is not 100% reliable. Instead, you should consider using the built-in np.array_equal() function for good measure. This always produces the right result. In this guide, you learn how to compare
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To resize an image using OpenCV, use the cv2.resize() function. To do this: Read an image into your program. Specify a scaling factor. Multiply the width and the height by the scaling factor. Call cv2.resize() function with the new dimensions Here is a quick cheat sheet for resizing images in four ways: Next, let’s take
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In Python, slicing is used to access specific parts of an iterable, such as a list. Here are some examples: But how does the slicing notation work? There are two syntaxes you can use the slice notation in Python: Let’s take a look at how both of these work. [start:stop] The slicing notation [start:stop] means
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In Python, there are 7 arithmetic operators you can use to perform basic mathematical operations. Here is a table of all the arithmetic operators in Python with examples: Operator Name Use + Addition x + y – Subtraction x – y * Multiplication x * y / Division x / y % Modulus x %
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