Problem Description: You have a Numpy array. You want to select specific elements from the array. But neither slicing nor indexing seem to solve your problem. What can you do? In this short tutorial, I show you how to select specific Numpy array elements via Boolean matrices. A feature called conditional indexing or selective indexing. … Read more
Problem Formulation You use NumPy’s np.nanmedian() function in your code that is supposed to ignore NaN values when computing the mean of a NumPy array. But when using it, NumPy raises a RuntimeWarning: All-NaN slice encountered message: What is the reason for this warning and how to fix it? Solution + Explanation The reason this … Read more
Problem Formulation You use NumPy’s np.nanmean() function in your code that is supposed to ignore NaN values when computing the mean of a NumPy array. But when using it, NumPy raises a RuntimeWarning: Mean of empty slice message: What is the reason for this warning and how to fix it? Solution + Explanation The reason … Read more
Problem Formulation: Replacing One Element Given List lst Element x Index i How to replace the element at index i in the list lst with the new element x? Solution Indexing You use simple indexing using the square bracket notation lst[i] = x to replace the element at index i in list lst with the … Read more
You can extract text from images with EasyOCR, a deep learning-based OCR tool in Python. EasyOCR performs very well on invoices, handwriting, car plates, and public signs. First released in 2007, PyTesseract [1] is the to-go library for extracting text from images. It uses classical computer vision methods to perform optical character recognition (OCR), then … Read more
The np.arange() function appears in 21% of the 35 million Github repositories that use the NumPy library! This illustrated tutorial shows you the ins and outs of the NumPy arange function. So let’s get started! What’s the NumPy Arange Function? The np.arange([start,] stop[, step]) function creates a new NumPy array with evenly-spaced integers between start … Read more
![Numpy Weighted Average np.average(array, axis=0, weights=[0.1,0.1,0.8])](https://blog.finxter.com/wp-content/uploads/2018/08/Numpy-Weighted-Average.png)
Problem Formulation: How to calculate the weighted average of the elements in a NumPy array? Definition weighted average: Each array element has an associated weight. The weighted average is the sum of all array elements, properly weighted, divided by the sum of all weights. Here’s the problem exemplified: Quick solution: Before we discuss the solution … Read more
NumPy is a popular Python library for data science focusing on arrays, vectors, and matrices. This article introduces the np.average() function from the NumPy library. When applied to a 1D array, this function returns the average of the array values. When applied to a 2D array, NumPy simply flattens the array. The result is the … Read more
NumPy is a popular Python library for data science for array, vector, and matrix computations. This puzzle introduces basic indexing of elements in NumPy arrays. Problem Formulation: How to index elements in NumPy arrays? Indexing 1D Arrays with Positive Indices The most simple use of indexing is with the square bracket notation and positive integers: … Read more
Problem Formulation: How to calculate the standard deviation in NumPy? Differentiations: There are many different variants of this problem: Calculate the standard deviation of a 1D array Calculate the standard deviation of a 2D array Calculate the standard deviation of a 3D array Then you can also calculate the standard deviation along an axis: Calculate … Read more
This article deals with calculating percentiles. Percentiles are statistical indicators that are used to describe specific portions of a sample population. The following sections will explain what percentiles are, what they are used for and how to calculate them, using Python. As you will see, Python allows solving this problem in multiple ways, either by … Read more
Numpy is a popular Python library for data science focusing on arrays, vectors, and matrices. Problem Formulation: Given a one-dimensional NumPy array arr. How to access the i-th value in the array? How to access all values between the i-th value (included) and the j-th value (excluded) from the array? How to access all values … Read more