1 Load packages
library(tidyverse) # data wrangling
library(plotly) # make interactive JS plots
library(printr) # print dataframes as tables2 Load data
data_url <- "https://vincentarelbundock.github.io/Rdatasets/csv/ggplot2/diamonds.csv"diamonds <- read_csv(data_url)glimpse(diamonds)
#> Rows: 53,940
#> Columns: 11
#> $ X1 <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18…
#> $ carat <dbl> 0.23, 0.21, 0.23, 0.29, 0.31, 0.24, 0.24, 0.26, 0.22, 0.23, 0…
#> $ cut <chr> "Ideal", "Premium", "Good", "Premium", "Good", "Very Good", "…
#> $ color <chr> "E", "E", "E", "I", "J", "J", "I", "H", "E", "H", "J", "J", "…
#> $ clarity <chr> "SI2", "SI1", "VS1", "VS2", "SI2", "VVS2", "VVS1", "SI1", "VS…
#> $ depth <dbl> 61.5, 59.8, 56.9, 62.4, 63.3, 62.8, 62.3, 61.9, 65.1, 59.4, 6…
#> $ table <dbl> 55, 61, 65, 58, 58, 57, 57, 55, 61, 61, 55, 56, 61, 54, 62, 5…
#> $ price <dbl> 326, 326, 327, 334, 335, 336, 336, 337, 337, 338, 339, 340, 3…
#> $ x <dbl> 3.95, 3.89, 4.05, 4.20, 4.34, 3.94, 3.95, 4.07, 3.87, 4.00, 4…
#> $ y <dbl> 3.98, 3.84, 4.07, 4.23, 4.35, 3.96, 3.98, 4.11, 3.78, 4.05, 4…
#> $ z <dbl> 2.43, 2.31, 2.31, 2.63, 2.75, 2.48, 2.47, 2.53, 2.49, 2.39, 2…Find here more information on this data set.
3 Objective
Visualize the distribution of the price of the diamonds, grouped by cut. Add the mean and/or the median to the picture for each subgroup.
4 Plot 1
plot1 <- diamonds %>%
ggplot() +
aes(x = price, fill = cut) +
geom_histogram() +
facet_wrap(~ cut)
plot1
5 Plot 2
Summarized data:
diamonds %>%
group_by(cut) %>%
summarise(price_md_cut = median(price, na.rm = T),
price_max_cut = max(price, na.rm = T)) -> diamonds_summarized
diamonds_summarized| cut | price_md_cut | price_max_cut |
|---|---|---|
| Fair | 3282.0 | 18574 |
| Good | 3050.5 | 18788 |
| Ideal | 1810.0 | 18806 |
| Premium | 3185.0 | 18823 |
| Very Good | 2648.0 | 18818 |
plot2 <- plot1 +
geom_vline(data = diamonds_summarized, aes(xintercept = price_md_cut)) +
geom_label(data = diamonds_summarized, aes(x = price_md_cut,
y = price_max_cut*0.07, # at 7% height
label = price_md_cut)) +
labs(caption = "verticals bars show the median per group")
plot2
6 Plot 3: Interactive plot
Make the diagram interactive.
plot3 <- ggplotly(plot2)
plot37 Reproducibility
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