Top 20 Perfume Brands Ranked by Average Rating and Portfolio Size

This chart displays the leading perfume brands based on their average customer ratings. The length of each bar represents the brand’s average rating, while the height indicates the number of fragrances in their portfolio.

TidyTuesday
Data Visualization
R Programming
2024
Analysis of top perfume brands using TidyTuesday data. Creating a Mekko chart visualization to showcase ratings and portfolio sizes using R and ggplot2.
Author

Steven Ponce

Published

December 7, 2024

Figure 1: Mekko chart displaying the top 20 perfume brands ranked by average rating and portfolio size. The length of each bar represents the brand’s average rating, and the height represents the number of fragrances. Notable brands include Ensar Oud, Guerlain, and Sunnamusk, with annotations highlighting their portfolio sizes.

Steps to Create this Graphic

1. Load Packages & Setup

Show code 
## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
    pacman::p_load(
    tidyverse,      # Easily Install and Load the 'Tidyverse'
    ggtext,         # Improved Text Rendering Support for 'ggplot2'
    showtext,       # Using Fonts More Easily in R Graphs
    janitor,        # Simple Tools for Examining and Cleaning Dirty Data
    skimr,          # Compact and Flexible Summaries of Data
    scales,         # Scale Functions for Visualization
    glue,           # Interpreted String Literals
    here            # A Simpler Way to Find Your Files
    )   
})

suppressMessages(source(here::here("_setup.R")))

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  =  8,
  height =  16,
  units  = "in",
  dpi    = 320
)

### |- resolution ----
showtext_opts(dpi = 320, regular.wt = 300, bold.wt = 800)

2. Read in the Data

Show code 
# tt <- tidytuesdayR::tt_load(2024, week = 50)
#
# parfumo_data_raw  <- tt$parfumo_data |> clean_names()
#
# tidytuesdayR::readme(tt)
# rm(tt)

# Option 2: Read directly from GitHub
parfumo_data_raw <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2024/2024-12-10/parfumo_data_clean.csv")
parfumo_data_raw <- parfumo_data_raw |> clean_names()

3. Examine the Data

Show code 
glimpse(parfumo_data_raw)
skim(parfumo_data_raw)

4. Tidy Data

Show code 
### |- tidy data ----

parfumo_brand_stats <- parfumo_data_raw |>
    group_by(brand) |>
    summarise(
        n_fragrances = n(),
        avg_rating = mean(rating_value, na.rm = TRUE),
        .groups = "drop"
    ) |>
    filter(n_fragrances >= 50) |> # Filter for brands with at least 50 fragrances
    arrange(desc(avg_rating)) |>
    head(20) |> # Select the top 20 brands based on average rating
    # Create y-coordinates for rectangles
    mutate(
        ymax = cumsum(n_fragrances),
        ymin = lag(ymax, default = 0),
        font_size = ifelse(n_fragrances > 200, 7.5, 4.5), # Larger bars get a bigger font size
        brand = case_when(
            brand == "Abdul Samad Al Qurashi / عبدالصمد القرشي" ~ "Abdul Samad Al Qurashi", # Arabic characters were not rendering properly
            brand == "Teone Reinthal Natural Perfume" ~ "Teone Reinthal\nNatural Perfume",
            TRUE ~ as.character(brand)
        )
    )

5. Visualization Parameters

Show code 
### |-  plot aesthetics ----
bkg_col      <- "#f5f5f2"
title_col    <- "gray20"
subtitle_col <- "gray20"
caption_col  <- "gray30"
text_col     <- "gray30"
note_col     <- "gray40" 
bar_col      <- "#1B2B48"

# icons
tt <- str_glue("#TidyTuesday: { 2024 } Week { 50 } &bull; Source: Parfumo Fragrance Dataset<br>")
li <- str_glue("<span style='font-family:fa6-brands'>&#xf08c;</span>")
gh <- str_glue("<span style='font-family:fa6-brands'>&#xf09b;</span>")
bs <- str_glue("<span style='font-family:fa6-brands'>&#xe671; </span>")

# text
title_text    <- str_glue("Top 20 Perfume Brands Ranked by Average Rating<br>
                          and Portfolio Size")
subtitle_text <- str_glue("This chart displays the leading perfume brands based on their average<br>
                          customer ratings. The length of each bar represents the brand\\'s average<br>
                          rating, while the height indicates the number of fragrances in their portfolio.")
caption_text <- str_glue("{tt} {li} stevenponce &bull; {bs} sponce1 &bull; {gh} poncest &bull; #rstats #ggplot2")

### |-  fonts ----
setup_fonts()

### |-  plot theme ----
theme_set(theme_minimal(base_size = 14, base_family = "text"))

theme_update(
    plot.title.position   = "plot",
    plot.caption.position = "plot",
    legend.position       = "plot",
    plot.background       = element_rect(fill = bkg_col, color = bkg_col),
    panel.background      = element_rect(fill = bkg_col, color = bkg_col),
    plot.margin           = margin(t = 10, r = 20, b = 10, l = 20),
    axis.title.x          = element_text(margin = margin(10, 0, 0, 0), size = rel(1.1),
                                         color = text_col, family = "text", face = "bold", hjust = 0.5),
    axis.title.y.right    = element_text(margin = margin(0, 20, 0, 10), size = rel(1.1),
                                         color = text_col, family = "text", face = "bold",
                                         angle = 0, vjust = 1.0, hjust = 1),
    axis.line.x           = element_line(color = "#252525", linewidth = .2),
    axis.title            = element_text(size = rel(0.93), face = "bold", color = text_col),
    axis.text             = element_text(size = rel(0.79), color = text_col),
    legend.title          = element_blank(),
    legend.text           = element_text(size = rel(0.71), color = text_col),
    panel.grid.major.x    = element_blank(),
    panel.grid.major.y    = element_line(color = "gray90", linewidth = 0.2),
    panel.grid.minor      = element_blank()
)

6. Plot

Show code 
### |-  initial plot ----

p <- ggplot(parfumo_brand_stats) +
    # Horizontal bar chart with variable width
    geom_rect(
        aes(
            xmin = 0,
            xmax = avg_rating,
            ymin = ymin,
            ymax = ymax
        ),
        color = "#e0e0e0",
        fill = bar_col,
        linewidth = ifelse(parfumo_brand_stats$n_fragrances > 200, 1, 0.3)
    ) +
    # Add brand names to bars
    geom_text(
        aes(
            x = 0.2,
            y = ymin + ((ymax - ymin) / 2),
            label = ifelse(n_fragrances >= 80, brand, ""),
        ),
        color = ifelse(parfumo_brand_stats$n_fragrances < 200, "#e0e0e0", "white"),
        hjust = 0,
        size = parfumo_brand_stats$font_size
    ) +
    # Add ratings to bars
    geom_text(
        aes(
            x = avg_rating - 0.3,
            y = ymin + ((ymax - ymin) / 2),
            label = ifelse(n_fragrances >= 80,
                           paste(sprintf("(%.1f)", avg_rating)),
                           ""
            ),
        ),
        color = ifelse(parfumo_brand_stats$n_fragrances < 200, "#e0e0e0", "white"),
        hjust = 1,
        size = 3.2
    ) +
    # Scales
    scale_x_continuous(
        limits = c(0, 11),
        breaks = seq(0, 11, 2),
        expand = c(0, 0, 0.05, 0)
    ) +
    scale_y_continuous(
        expand = c(0, 0, 0.01, 0),
        position = "right",
        labels = scales::comma,
        breaks = seq(0, max(parfumo_brand_stats$ymax), 1000)
    ) +
    # Labs
    labs(
        x = "Average Rating",
        y = "Number of\nFragrances",
        title    = title_text,
        subtitle = subtitle_text,
        caption  = caption_text
    ) +
    # Theme
    theme(
        plot.title      = element_markdown(
            size        = rel(1.8),
            family      = "title",
            face        = "bold",
            color       = title_col,
            lineheight  = 1.1,
            margin      = margin(t = 5, b = 5)
        ),
        plot.subtitle   = element_markdown(
            size        = rel(1.06),
            family      = "subtitle",
            color       = text_col,
            lineheight  = 1.1,
            margin      = margin(t = 5, b = 20)
        ),
        plot.caption    = element_markdown(
            size        = rel(.65),
            family      = "caption",
            color       = caption_col,
            lineheight  = 0.65,
            hjust       = 0.5,
            halign      = 0.5,
            margin      = margin(t = 10, b = 5)
        ),
    )

annotation_data <- tibble(
    x = c(9, 9, 9),
    y = c(parfumo_brand_stats$ymin[3] + ((parfumo_brand_stats$ymax[3] - parfumo_brand_stats$ymin[3]) / 2),
          parfumo_brand_stats$ymin[18] + ((parfumo_brand_stats$ymax[18] - parfumo_brand_stats$ymin[18]) / 2),
          parfumo_brand_stats$ymin[8] + ((parfumo_brand_stats$ymax[8] - parfumo_brand_stats$ymin[8]) / 2)),
    xend = c(parfumo_brand_stats$avg_rating[3], parfumo_brand_stats$avg_rating[18], parfumo_brand_stats$avg_rating[8]),
    yend = c((parfumo_brand_stats$ymin[3] + parfumo_brand_stats$ymax[3]) / 2,
             (parfumo_brand_stats$ymin[18] + parfumo_brand_stats$ymax[18]) / 2,
             (parfumo_brand_stats$ymin[8] + parfumo_brand_stats$ymax[8]) / 2),
    label = c("Ensar Oud / Oriscent has\n534 fragrances in its portfolio",
              "Guerlain has 586 fragrances\nin its portfolio",
              "Sunnamusk has 57 fragrances\nin its portfolio")
)

p <- p +
    # Add annotation outside the grid
    coord_cartesian(
        expand = FALSE,
        clip = "off",
        xlim = c(0, 11)
    ) +
    
    # Add labels and curves programmatically
    geom_label(
        data = annotation_data,
        aes(
            x = x + 0.2,
            y = y,
            label = label
        ),
        size = 4,
        color = note_col,
        hjust = 0,
        lineheight = 1,
        label.size = NA,
        label.padding = unit(0, "lines"),
        fill = "transparent"
    ) +
    geom_curve(
        data = annotation_data,
        aes(
            x = x,
            y = y,
            xend = xend,
            yend = yend
        ),
        curvature = 0,
        color = note_col,
        arrow = arrow(type = "closed", length = unit(0.1, "inches"))
    )

7. Save

Show code 
### |-  plot image ----  

source(here::here("R/image_utils.R"))
save_plot(p, type = "tidytuesday", year = 2024, week = 50, height = 16, width = 8)

8. Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

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    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] here_1.0.1      glue_1.8.0      scales_1.3.0    skimr_2.1.5    
 [5] janitor_2.2.0   showtext_0.9-7  showtextdb_3.0  sysfonts_0.8.9 
 [9] ggtext_0.1.2    lubridate_1.9.3 forcats_1.0.0   stringr_1.5.1  
[13] dplyr_1.1.4     purrr_1.0.2     readr_2.1.5     tidyr_1.3.1    
[17] tibble_3.2.1    ggplot2_3.5.1   tidyverse_2.0.0

loaded via a namespace (and not attached):
 [1] gtable_0.3.6      xfun_0.49         htmlwidgets_1.6.4 tzdb_0.4.0       
 [5] vctrs_0.6.5       tools_4.4.0       generics_0.1.3    curl_6.0.0       
 [9] parallel_4.4.0    gifski_1.32.0-1   fansi_1.0.6       pacman_0.5.1     
[13] pkgconfig_2.0.3   lifecycle_1.0.4   farver_2.1.2      compiler_4.4.0   
[17] textshaping_0.4.0 munsell_0.5.1     repr_1.1.7        codetools_0.2-20 
[21] snakecase_0.11.1  htmltools_0.5.8.1 yaml_2.3.10       crayon_1.5.3     
[25] pillar_1.9.0      camcorder_0.1.0   magick_2.8.5      commonmark_1.9.2 
[29] tidyselect_1.2.1  digest_0.6.37     stringi_1.8.4     rsvg_2.6.1       
[33] rprojroot_2.0.4   fastmap_1.2.0     grid_4.4.0        colorspace_2.1-1 
[37] cli_3.6.3         magrittr_2.0.3    base64enc_0.1-3   utf8_1.2.4       
[41] withr_3.0.2       bit64_4.5.2       timechange_0.3.0  rmarkdown_2.29   
[45] bit_4.5.0         ragg_1.3.3        hms_1.1.3         evaluate_1.0.1   
[49] knitr_1.49        markdown_1.13     rlang_1.1.4       gridtext_0.1.5   
[53] Rcpp_1.0.13-1     xml2_1.3.6        renv_1.0.3        svglite_2.1.3    
[57] rstudioapi_0.17.1 vroom_1.6.5       jsonlite_1.8.9    R6_2.5.1         
[61] systemfonts_1.1.0

9. GitHub Repository

The complete code for this analysis is available in tt_2024_50.qmd.

For the full repository, click here.

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