Diamonds dataset from R

Introduction

Our main focus in the diamonds dataset from R. We will be looking into more details surrounding the coding as well as figures we conclude on from the dataset

Running Code

We will need to insert the following libraries that we will be using throughout this section:

library(tidyverse)
library(ggplot2)
library(dplyr)
library(gt)

Warning: package 'gt' was built under R version 4.5.3

Dataset

data(diamonds)
gt(head(diamonds))

carat	cut	color	clarity	depth	table	price	x	y	z
0.23	Ideal	E	SI2	61.5	55	326	3.95	3.98	2.43
0.21	Premium	E	SI1	59.8	61	326	3.89	3.84	2.31
0.23	Good	E	VS1	56.9	65	327	4.05	4.07	2.31
0.29	Premium	I	VS2	62.4	58	334	4.20	4.23	2.63
0.31	Good	J	SI2	63.3	58	335	4.34	4.35	2.75
0.24	Very Good	J	VVS2	62.8	57	336	3.94	3.96	2.48

Code

ggplot(diamonds, aes(x=carat,
                     y = price,
                     color=color))+
  geom_point()+
  geom_smooth()+
  labs(title='diamond prices based on carat')

Other figure(s)

Bar graph showing the various cuts of diamonds

Boxplot showing the various cuts of diamonds

Conclusion

We have analysed the different types of diamonds based on the given dataset “diamonds”.

Also note:

facet_wrap was used to show the cuts of the diamonds and their prices based on the different colors. We can use this figure to analyse the differences in colors between the diamonds. Facet wrap is 1 dimensional (1D) as a single variable is used to create subplots.