R v Python Series: Introduction

-

 


Introduction

In this series of posts, we will cover exercises in both R and Python.  The examples were inspired by Matt Dancho and his incredible library of training videos on Business Science University.  These posts are not intended to steer you towards one software or another.  Both R and Python are powerful programming languages, and both have their advantages and disadvantages.  In fact, with packages such as Reticulate, you can now leverage the power of both R and Python together.  

The topics included in future posts include some of the most commonly used data ingestion, wrangling, and visualization techniques used in data analysis and data science.



Popular posts from this blog

MySQL Part 1: Getting MySQL Set Up in goormIDE

-
Image
Introduction In this article, we will walk through how to set up the goormIDE so that you can utilize it in the examples presented later on my blog.  You can always download a local version of MySQL on your desktop and follow along as well. As a disclaimer, the data in these examples were provided by Business Science University 's DSB4 101-R: Business Analysis with R course.  If you want additional MySQL training, please check out  The Ultimate MySQL Bootcamp: Go from SQL Beginner to Expert on Udemy . Both links are provided below. https://www.business-science.io/ https://www.udemy.com/course/the-ultimate-mysql-bootcamp-go-from-sql-beginner-to-expert/ A Few Notes Before We Start The subsequent articles assume that you have a working version of MySQL already downloaded and installed.  However, this article provides links to help you get started in the goorm cloud IDE.  The benefit of using goorm is that it is cloud-based and does not require you to download...
Read more

Do Popular Market Index Returns Follow a Normal Distribution?

-
Image
Introduction Many statistical tests assume normality within the data set.  In other words, before you perform any type of parametric test, one should first view the data sets and run experiments to test this assumption.  This article will show you how to pull several market indices’ historical returns and see if they follow a normal distribution using the Shapiro-Wilk test. The main reason this article is testing the normal distribution validity of portfolio returns is to set up Monte Carlo simulations to project future retirement balances and their respective probabilities in Tableau.   To view the interactive application and estimate your own retirement savings, click here .   Sources:  Normality Test in R Analyzing Performance with tidyquant Market Index Background We were able to pull the following historical index information using a convenient package in R called tidyquant .  We will test the normality of the various benchmarks listed below...
Read more