Category: NumPy Tutorial

🔢 Rounding Decimals in Python Python provides several ways to round numbers to a specific number of decimal places. You can use built-in functions, string formatting, or NumPy for arrays.  1. Using round() Function...

🔢 NumPy Simple Arithmetic NumPy allows you to perform fast, element-wise arithmetic operations on arrays without writing loops.This is one of the biggest advantages of NumPy over normal Python lists. 1️⃣ Import NumPy import...

🛠️ Creating Your Own ufunc in NumPy NumPy allows you to create custom universal functions (ufuncs), which can then operate element-wise on NumPy arrays just like built-in ufuncs.There are two main ways: Using np.vectorize()...

🔢 NumPy Universal Functions (ufuncs) Universal functions (ufuncs) in NumPy are vectorized functions that operate element-wise on arrays.They are highly optimized, fast, and avoid explicit Python loops.  1. Types of ufuncs Arithmetic ufuncs Comparison...

📊 Zipf Distribution in Python The Zipf distribution is a discrete probability distribution that models ranked data, where the frequency of an item is inversely proportional to its rank.It appears in linguistics, social networks,...

📈 Pareto Distribution in Python The Pareto Distribution is a heavy-tailed continuous probability distribution often used in economics, finance, and social sciences.It is famous for modeling wealth distribution, income, or city sizes, where a...

🌊 Rayleigh Distribution in Python The Rayleigh distribution is a continuous probability distribution often used in signal processing, communications, and reliability analysis. It describes the magnitude of a vector with two independent, normally distributed...

📊 Chi-Square (χ²) Distribution in Python Chi Square Distribution is widely used in statistics, especially for hypothesis testing, goodness-of-fit tests, and variance analysis. It describes the distribution of a sum of squared independent standard...

📈 Exponential Distribution in Python The Exponential Distribution models the time between independent events that occur at a constant rate.It is closely related to the Poisson Distribution, which models the number of events in...

🎲 Multinomial Distribution in Python The Multinomial Distribution generalizes the binomial distribution to more than two outcomes per trial.It models the number of occurrences of each outcome in a fixed number of independent trials....