MATH2270 Module 2

Skill Builder - Diamond Dataset

Loading the Packages

library(ggplot2)
library(dplyr)

Defining the Variables

• “Diamonds.csv” was added to local folder for addition to the RStudio IDE.

Diamonds <- read.csv("Diamonds.csv")
Diamonds$cut<- factor(Diamonds$cut, levels=c('Fair','Good','Very Good','Premium','Ideal'), 
                       ordered=TRUE)
Diamonds$color<- factor(Diamonds$color, levels=c('J','I','H','G','F','E','D'), 
                         ordered=TRUE)
Diamonds$clarity<- factor(Diamonds$clarity, levels=c('I1','SI2','SI1','VS2','VS1','VVS2','VVS1','IF'), 
                           ordered=TRUE)

• Check the import

str(Diamonds)

'data.frame':   53940 obs. of  10 variables:
 $ carat  : num  0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
 $ cut    : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
 $ color  : Ord.factor w/ 7 levels "J"<"I"<"H"<"G"<..: 6 6 6 2 1 1 2 3 6 3 ...
 $ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
 $ depth  : num  61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
 $ table  : num  55 61 65 58 58 57 57 55 61 61 ...
 $ price  : int  326 326 327 334 335 336 336 337 337 338 ...
 $ x      : num  3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
 $ y      : num  3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
 $ z      : num  2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...

• Check summary statistics

summary(Diamonds)

     carat               cut        color        clarity          depth           table           price             x         
 Min.   :0.2000   Fair     : 1610   J: 2808   SI1    :13065   Min.   :43.00   Min.   :43.00   Min.   :  326   Min.   : 0.000  
 1st Qu.:0.4000   Good     : 4906   I: 5422   VS2    :12258   1st Qu.:61.00   1st Qu.:56.00   1st Qu.:  950   1st Qu.: 4.710  
 Median :0.7000   Very Good:12082   H: 8304   SI2    : 9194   Median :61.80   Median :57.00   Median : 2401   Median : 5.700  
 Mean   :0.7979   Premium  :13791   G:11292   VS1    : 8171   Mean   :61.75   Mean   :57.46   Mean   : 3933   Mean   : 5.731  
 3rd Qu.:1.0400   Ideal    :21551   F: 9542   VVS2   : 5066   3rd Qu.:62.50   3rd Qu.:59.00   3rd Qu.: 5324   3rd Qu.: 6.540  
 Max.   :5.0100                     E: 9797   VVS1   : 3655   Max.   :79.00   Max.   :95.00   Max.   :18823   Max.   :10.740  
                                    D: 6775   (Other): 2531                                                                   
       y                z         
 Min.   : 0.000   Min.   : 0.000  
 1st Qu.: 4.720   1st Qu.: 2.910  
 Median : 5.710   Median : 3.530  
 Mean   : 5.735   Mean   : 3.539  
 3rd Qu.: 6.540   3rd Qu.: 4.040  
 Max.   :58.900   Max.   :31.800  
                                  

Challenge - What determines a diamond’s price?

In the case of the Plot 1, Clarity ‘IF’ is associated with the greatest rise in price, as compared to the other clarity values.

In the case of the Plot 2, Cut ‘Ideal’ is associated with the greatest rise in price, as compared to the other cut values.

In the case of the Plot 3, Color ‘D’ is associated with the greatest rise in price, as compared to the other color values.

Overall, a diamond with clarity equal to IF, cut equal to Ideal and color equal to D would have the greatest value per unit of carat.