NumPy @ Operator vs np.dot()

Both the @ operator and the dot function are pivotal for matrix multiplication. However, beginners and even some seasoned programmers might find themselves puzzled over which to use and when. What are the @ Operator and dot Function? NumPy, Python’s fundamental package for scientific computing, offers several ways to perform operations on arrays and matrices. … Read more

How to Fit a Curve to Power-law Distributed Data in Python

In this tutorial, you’ll learn how to generate synthetic data that follows a power-law distribution, plot its cumulative distribution function (CDF), and fit a power-law curve to this CDF using Python. This process is useful for analyzing datasets that follow power-law distributions, which are common in natural and social phenomena. Prerequisites Ensure you have Python … Read more

How to Generate and Plot Random Samples from a Power-Law Distribution in Python?

To generate random samples from a power-law distribution in Python, use the numpy library for numerical operations and matplotlib for visualization. Here’s a minimal code example to generate and visualize random samples from a power-law distribution: First, we import the necessary libraries: numpy for generating the power-law distributed samples and matplotlib.pyplot for plotting. The a … Read more

Visualizing Wealth: Plotting the Net Worth of the World’s Richest in Log/Log Space

The distribution of wealth, especially when it comes to the ultra-wealthy, is a subject of immense fascination and study. It can reveal patterns and insights into economic structures, inequality, and financial dynamics at the highest levels. One of the most revealing ways to examine this distribution is through a log/log plot of the net worths … Read more

5 Best Ways to Find Common Elements in Two Arrays in Python

π‘ Problem Formulation: When working with data in Python, a common task is to find the intersection of two arrays β in other words, to find elements that are common to both arrays. For example, given two arrays array1 = [1, 2, 3, 4] and array2 = [2, 4, 6, 8], the desired output would … Read more

Python One Line Array Filter

π‘ Problem Formulation: Filtering arrays (or lists in Python) is a common task where we aim to create a new list that includes only those elements that satisfy a specific condition. For example, given an input array [1, 2, 3, 4, 5], we might want to filter out all values greater than 2, resulting in … Read more

10 Best Ways to Create a Pandas Series

To create a Pandas Series for different data types, start by importing the Pandas library in Python using import pandas as pd. Then, create a Series object by using pd.Series(data), where data can be a list, array, or dictionary containing elements of various data types like integers, strings, or floats. Finally, you can specify the … Read more

Python List to 2D Array – The Ultimate Conversion Guide

Python Lists and 2D Arrays Understanding Python Lists Python lists are container data structures that allow you to store and manipulate collections of elements. Lists are created using square brackets [], and you can store any data type within a list, including numbers, strings, and even other lists. Here’s a simple Python list example: To … Read more

How I Solved a Real-World Problem Using Monte Carlo Simulation

In this project, you are taking the role of a data analyst. Your client, a large retail outlet has been running an affiliate marketing program in an effort to increase its sales. You are tasked to come up with a predictive model to predict how much should be budgeted for sales commission for the following … Read more

Python Return Two or Multiple Lists, Dicts, Arrays, DataFrames From a Function

Python Functions and Return Statements Basic Function Syntax Python functions are a key element in writing modular and reusable code. They allow you to define a block of code that can be called with specific arguments to perform a specific task. The function syntax in Python is simple and clean. You can define a function … Read more

How to Plot a 3D Normal Distribution in Python?

To create a 3D surface plot of a bivariate normal distribution define two normally distributed random variables x and y, each with its own mean (mu_x, mu_y) and variance (variance_x, variance_y). The random variables are independent,the covariance between x and y is 0. Use the grid of (x, y) pairs to calculate the probability density … Read more

How Do I Make a 3D Waterfall Plot with Colored Heights in Python?

To generate a 3D waterfall plot with colored heights create a 2D sine wave using the NumPy meshgrid() function, then apply a colormap to the heights using Matplotlib’s Normalize function. The plot_surface() function generates the 3D plot, while the color gradient is added using a ScalarMappable object. Here’s a code example for copy and paste: … Read more