The Diamonds dataSet EDA
The diamonds dataset EDA in R.
It contains measurements on 10 different variables (like price, color, clarity, etc.) for 53,940 different diamonds [53940 10].
This tutorial explains how to explore, summarize, and visualise the diamonds dataset in R.
Load the diamonds data
## # A tibble: 53,940 × 10
## carat cut color clarity depth table price x y z
## <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
## 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
## 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
## 4 0.29 Premium I VS2 62.4 58 334 4.2 4.23 2.63
## 5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
## 6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48
## 7 0.24 Very Good I VVS1 62.3 57 336 3.95 3.98 2.47
## 8 0.26 Very Good H SI1 61.9 55 337 4.07 4.11 2.53
## 9 0.22 Fair E VS2 65.1 61 337 3.87 3.78 2.49
## 10 0.23 Very Good H VS1 59.4 61 338 4 4.05 2.39
## # … with 53,930 more rows
## # ℹ Use `print(n = ...)` to see more rows## # A tibble: 6 × 10
## carat cut color clarity depth table price x y z
## <dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
## 1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
## 2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
## 3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
## 4 0.29 Premium I VS2 62.4 58 334 4.2 4.23 2.63
## 5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
## 6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48## [1] "carat" "cut" "color" "clarity" "depth" "table" "price"
## [8] "x" "y" "z"## carat cut color clarity depth
## Min. :0.2000 Fair : 1610 D: 6775 SI1 :13065 Min. :43.00
## 1st Qu.:0.4000 Good : 4906 E: 9797 VS2 :12258 1st Qu.:61.00
## Median :0.7000 Very Good:12082 F: 9542 SI2 : 9194 Median :61.80
## Mean :0.7979 Premium :13791 G:11292 VS1 : 8171 Mean :61.75
## 3rd Qu.:1.0400 Ideal :21551 H: 8304 VVS2 : 5066 3rd Qu.:62.50
## Max. :5.0100 I: 5422 VVS1 : 3655 Max. :79.00
## J: 2808 (Other): 2531
## table price x y
## Min. :43.00 Min. : 326 Min. : 0.000 Min. : 0.000
## 1st Qu.:56.00 1st Qu.: 950 1st Qu.: 4.710 1st Qu.: 4.720
## Median :57.00 Median : 2401 Median : 5.700 Median : 5.710
## Mean :57.46 Mean : 3933 Mean : 5.731 Mean : 5.735
## 3rd Qu.:59.00 3rd Qu.: 5324 3rd Qu.: 6.540 3rd Qu.: 6.540
## Max. :95.00 Max. :18823 Max. :10.740 Max. :58.900
##
## z
## Min. : 0.000
## 1st Qu.: 2.910
## Median : 3.530
## Mean : 3.539
## 3rd Qu.: 4.040
## Max. :31.800
## ## [1] 53940 10## tibble [53,940 × 10] (S3: tbl_df/tbl/data.frame)
## $ carat : num [1:53940] 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 "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
## $ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
## $ depth : num [1:53940] 61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
## $ table : num [1:53940] 55 61 65 58 58 57 57 55 61 61 ...
## $ price : int [1:53940] 326 326 327 334 335 336 336 337 337 338 ...
## $ x : num [1:53940] 3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
## $ y : num [1:53940] 3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
## $ z : num [1:53940] 2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...Visualise the diamonds Dataset
We can also create some plots to visualize the values in the dataset.
For example, we can create an histogram of the values for a certain variable:
Create a scatterplot of any pairwise combination of variables:
Create scatterplot of price, grouped by cut
Plot histogram of diamond prices by cut
## diamonds$cut: Fair
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 337 2050 3282 4359 5206 18574
## ------------------------------------------------------------
## diamonds$cut: Good
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 327 1145 3050 3929 5028 18788
## ------------------------------------------------------------
## diamonds$cut: Very Good
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 336 912 2648 3982 5373 18818
## ------------------------------------------------------------
## diamonds$cut: Premium
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 326 1046 3185 4584 6296 18823
## ------------------------------------------------------------
## diamonds$cut: Ideal
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 326 878 1810 3458 4678 18806
#Plot histogram of diamond prices by carat
# This session Summary
## R version 4.2.1 (2022-06-23 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22000)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_United States.utf8
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggplot2_3.3.6
##
## loaded via a namespace (and not attached):
## [1] highr_0.9 bslib_0.4.0 compiler_4.2.1 pillar_1.8.0
## [5] jquerylib_0.1.4 rmdformats_1.0.4 tools_4.2.1 digest_0.6.29
## [9] jsonlite_1.8.0 evaluate_0.15 lifecycle_1.0.1 tibble_3.1.8
## [13] gtable_0.3.0 pkgconfig_2.0.3 rlang_1.0.4 DBI_1.1.3
## [17] cli_3.3.0 rstudioapi_0.13 yaml_2.3.5 xfun_0.31
## [21] fastmap_1.1.0 withr_2.5.0 stringr_1.4.0 dplyr_1.0.9
## [25] knitr_1.39 generics_0.1.3 sass_0.4.2 vctrs_0.4.1
## [29] tidyselect_1.1.2 grid_4.2.1 glue_1.6.2 R6_2.5.1
## [33] fansi_1.0.3 rmarkdown_2.14 bookdown_0.28 farver_2.1.1
## [37] purrr_0.3.4 magrittr_2.0.3 codetools_0.2-18 scales_1.2.0
## [41] htmltools_0.5.3 assertthat_0.2.1 colorspace_2.0-3 labeling_0.4.2
## [45] utf8_1.2.2 stringi_1.7.8 munsell_0.5.0 cachem_1.0.6