Project 1
Kayla Williams
2025-02-19
R Markdown
Introduction
This project analyzes the diamonds dataset from the
ggplot2 package. The dataset contains attributes like
price, carat, cut, color, and clarity. We’ll visualize and analyze these
categorical variables. ## Load & Explore the Diamonds Dataset
# Load the diamonds dataset
data("diamonds")
# Check structure and summary statistics
str(diamonds)## 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 ...summary(diamonds)## 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
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## Introduction
This project analyzes the **diamonds dataset** from the `ggplot2` package.
The dataset contains approximately **54,000 diamonds**, with attributes such as:
- `price`: The price of the diamond in US dollars.
- `carat`: The weight of the diamond.
- `cut`: The quality of the diamond's cut (Fair, Good, Very Good, Premium, Ideal).
- `color`: The diamond's color grade, ranked from **D** (best) to **J** (worst).
- `clarity`: The number of inclusions and blemishes in the diamond.
```r
## Including Plots
## Bar Chart of Diamond Cut
``` r
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut))
Proportion-Based Bar Chart
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, y = after_stat(prop), group = 1))
Using stat_count() Instead of geom_bar()
ggplot(data = diamonds) +
stat_count(mapping = aes(x = cut))
Coloring Bars by Clarity
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity))
Stacked Bar Chart
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity))
## Fill-Adjusted Bar Chart
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity), position = "fill")
## Dodged Bar Chart
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge")
## Flipping the Coordinates
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity)) +
coord_flip()