﻿ Raymiljit Kaur, Author at WTMatter - Page 2 of 4

# Author Archives: Raymiljit Kaur

## NumPy Ufuncs (Python Tutorial)

This is a detailed tutorial of NumPy Universal Functions. Learn about the different functions that you can apply to the ndArray Objects. Ufuncs Ufuncs stands for universal functions. These are those function which can be helpful in operating NumPy Arrays. They help in operating the NumPy array, which we refer to as ndarray objects. They […]

## NumPy Zipf Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Zipf Distribution. Learn to get Zipf Distribution data using NumPy and visualize using Seaborn. Zipf Distribution Zipf distribution can be referred to as zeta distribution. It is a discrete distribution which quite commonly used in linguistics, insurance and also in the modelling of rare events. These distributions are […]

## NumPy Pareto Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Pareto Distribution. Learn to get Pareto Distribution data using NumPy and visualize using Seaborn. Pareto Distribution This distribution is based on Pareto’s law which works on the Pareto principle. The Pareto principle states that for every occurring event constitutes 80% of the effects, whereas 20% is the causes. […]

## NumPy Rayleigh Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Rayleigh Distribution. Learn to get Rayleigh Distribution data using NumPy and visualize using Seaborn. Rayleigh Distribution This distribution is helpful in the processing of the signal. It is a continuous probability distribution for nonnegative-valued random variables. Similarly, it usually helpful in observing the magnitude of a vector which […]

## NumPy Chi-Square Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Chi-Square Distribution. Learn to get Chi-Square Distribution data using NumPy and visualize using Seaborn. Chi-Square Distribution Chi-Square Distribution is one of the cases of the gamma distribution, and in most cases, it is helpful in probability distribution and also in the hypothesis testing. It also helps in working […]

## NumPy Exponential Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Exponential Distribution. Learn to implement Exponential Distribution using NumPy and visualize using Seaborn. Exponential Distribution In the theory of probability and statistics, this is the distribution of time between the events which will occur in the future. In this process, the events will continuously and independently. As a […]

## NumPy Multinomial Distribution (Python Tutorial)

This a detailed tutorial of NumPy Multinomial Distribution. Learn to get the data for Multinomial Distribution using NumPy with the help of examples. Multinomial Distribution The multinomial distribution is basically known as a generalized form of the binomial distribution. It is helpful in describing the scenarios which are by nature multi-nomial. In these scenarios, the […]

## NumPy Logistic Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Logistic Distribution. Learn to implement Logistic Distribution in NumPy and visualize using Seaborn. Logistic Distribution These distributions help us in describing the statistical growth of the data. It is known for predicting how the growth will happen by taking in certain data. These distributions are continuous in nature. […]

## NumPy Uniform Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Uniform Distribution. Learn to implement Uniform Distribution in NumPy and visualize using Seaborn. Uniform Distribution Uniform Distribution has a large use in the Random Numbers. This distribution is helpful where the chances of occurrence of every event are very much equal in all the aspects. It is very […]

## NumPy Poisson Distribution (Python Tutorial)

This is a detailed tutorial of NumPy Poisson Distribution. Learn to implement Poisson Distribution in NumPy and visualize using Seaborn. Poisson Distribution This distribution is a discrete distribution in which we have a discrete set of data. This data is not in the continuous form of data. In this type of data, we have certain […]