# Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

A boxplot, also known as a box and whisker plot, is a popular data visualization tool in R for Business Analytics. It is used to graphically represent the distribution of a set of numerical data by showing the median, quartiles, and outliers of the data set. A boxplot is useful in analyzing the central tendency and dispersion of the data, and identifying any outliers or skewness in the data.

In a boxplot, the center of the box represents the median, or the middle value, of the data set. The box itself spans from the first quartile, which is the 25th percentile of the data set, to the third quartile, which is the 75th percentile of the data set. The height of the box represents the interquartile range, which is the range between the first and third quartiles.

In addition to the box, the plot includes “whiskers” that extend from either side of the box. The whiskers represent the range of the data excluding the outliers. Outliers are plotted as individual points outside the whiskers, and are typically defined as data points that fall outside of 1.5 times the interquartile range.

In R, creating a boxplot is very simple. All you need is the data set and a few lines of code. You can customize the appearance of the boxplot by changing the color, width, and style of the box, whiskers, and outliers. You can also add labels, titles, and legends to the plot to help explain the data.

Boxplots are commonly used in business analytics to quickly analyze the distribution of data and identify any patterns or trends. They are particularly useful for comparing multiple sets of data, as you can easily compare the median, quartiles, and ranges of the data sets. Boxplots can also be combined with other types of plots, such as histograms, to get a more comprehensive view of the data.

In summary, the boxplot is a powerful data visualization tool in R for Business Analytics, and is an essential tool for anyone who wants to analyze, understand, and communicate their data. Whether you’re working in finance, marketing, or any other field, the boxplot is a simple and effective way to make sense of your data and present your findings in a clear and compelling way.

# R for Business Analytics – Boxplot

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# Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

## Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

# Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

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`Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.`

# Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

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Python Boxplot

End-to-End Machine Learning: model selection in R using boxplot

How to generate Boxplots in R using ggpubr package