Most Popular Valentine’s Candy Across U.S. States (2024)

Number of states ranking each candy as their 1st, 2nd, or 3rd choice

MakeoverMonday

2025

Explore the sweet preferences across America with this visualization of Valentine’s candy rankings. Using data from Candystore.com, this analysis reveals which candies dominate the Valentine’s season, with Conversation Hearts and Heart-Shaped Chocolates emerging as clear favorites among U.S. states.

Author

Steven Ponce

Published

February 9, 2025

Original

The original visualization Most Popular Valentine’s Candy by State comes from Candystore.com

Makeover

Figure 1: A horizontal stacked bar chart showing Valentine’s candy preferences across U.S. states in 2024. Each bar represents a candy type, with segments indicating the number of states ranking it as 1st, 2nd, or 3rd choice. Conversation Hearts leads with 46 states, followed by Heart-Shaped Box of Chocolates with 37 states. The remaining candies, including M&M’s, Hershey Kisses, and others, received fewer state rankings.

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
    lubridate,      # Make Dealing with Dates a Little Easier
    camcorder       # Record Your Plot History 
)
})

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

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))

2. Read in the Data

Show code

sv_candies_raw <- read_csv(
  here::here('data/MakeoverMonday_ SV_day.csv')) |> 
  clean_names()

3. Examine the Data

Show code

glimpse(sv_candies_raw)
skim(sv_candies_raw)

4. Tidy Data

Show code

### |-  tidy data ----
sv_candies_clean <- sv_candies_raw |>
  rename_with(~str_remove(., "^x"), starts_with("x"))

# Create long format data
candies_long <- sv_candies_clean |>
  pivot_longer(
    cols = ends_with("2024"),
    names_to = "rank",
    values_to = "candy"
  ) |>
  # Clean up rank names
  mutate(rank = case_when(
    rank == "1st_place_2024" ~ "1st Place",
    rank == "2nd_place_2024" ~ "2nd Place",
    rank == "3rd_place_2024" ~ "3rd Place"
  ),
  rank = factor(rank, levels = c("1st Place", "2nd Place", "3rd Place"))
  )

# Prepare data with totals
candies_with_counts <- candies_long |>
  mutate(rank = factor(rank, levels = c("1st Place", "2nd Place", "3rd Place"))) |> 
  count(candy, rank) |>
  group_by(candy) |>  
  mutate(
    total = sum(n)
  ) |>
  ungroup() |>
  arrange(-total, candy)

# Create total summary data
total_summary <- candies_with_counts |> 
  group_by(candy) |> 
  summarize(
    total = sum(n),
    y = total,
    rank = "1st Place"  
  )

5. Visualization Parameters

Show code

### |-  plot aesthetics ----
# Get base colors with custom palette
colors <- get_theme_colors(palette = c("1st Place" = "#FFB6C1",    
                                       "2nd Place" = "#FF69B4",     
                                       "3rd Place" = "#C71585"))

### |-  titles and caption ----
title_text <- str_glue("Most Popular Valentine's Candy Across U.S. States (2024)")
subtitle_text <- str_glue("Number of states ranking each candy as their 1st, 2nd, or 3rd choice")

# Create caption
caption_text <- create_mm_caption(
    mm_year = 2025,
    mm_week = 07,
    source_text = "Candystore.com"
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----

# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Weekly-specific modifications
    axis.line.x           = element_line(color = "#252525", linewidth = .2),
    
    panel.spacing.x       = unit(2, 'lines'),
    panel.spacing.y       = unit(1, 'lines'),
    panel.grid.major.x    = element_line(color = alpha(colors[5], 0.2), linewidth = 0.2),
    panel.grid.major.y    = element_blank(),
    panel.grid.minor      = element_blank(),
    
    legend.position = "top"
    
  )
)

# Set theme
theme_set(weekly_theme)

6. Plot

Show code

### |-  Plot  ----
p <- ggplot(candies_with_counts, 
       aes(x = reorder(candy, total), 
           y = n,
           fill = rank)) +  
  
  # Geoms
  geom_col() +
  geom_text(aes(label = n),
            position = position_stack(vjust = 0.5),
            color = "white",
            size = 3) +
  geom_text(data = total_summary,
            aes(y = y, label = paste0("(", total, ")")),
            hjust = -0.2,
            color = colors$text,
            size = 3) +
  
  # Scales
  scale_x_discrete() +
  scale_y_continuous(
    expand = expansion(mult = c(0, 0.1))
  ) +
  coord_flip() +
  scale_fill_manual(values = colors$palette) +
  
  # Labs
  labs(
    x = NULL,
    y = "Number of States",
    fill = "Ranking",
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text
  ) +
  
  # Theme
  theme(
    plot.title = element_text(
      size   = rel(1.6),
      family = fonts$title,
      face   = "bold",
      color  = colors$title,
      lineheight = 1.1,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size   = rel(1),
      family = fonts$subtitle,
      color  = colors$subtitle,
      lineheight = 1.2,
      margin = margin(t = 5, b = 15)
    ),
    plot.caption = element_markdown(
      size   = rel(0.6),
      family = fonts$caption,
      color  = colors$caption,
      hjust  = 0.5,
      margin = margin(t = 10)
    )
  )

7. Save

Show code

### |-  plot image ----  
save_plot(
  p, 
  type = "makeovermonday", 
  year = 2025,
  week = 07,
  width = 8, 
  height = 8
  )

8. Session Info

Expand for 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] camcorder_0.1.0 here_1.0.1      glue_1.8.0      scales_1.3.0   
 [5] skimr_2.1.5     janitor_2.2.0   showtext_0.9-7  showtextdb_3.0 
 [9] sysfonts_0.8.9  ggtext_0.1.2    lubridate_1.9.3 forcats_1.0.0  
[13] stringr_1.5.1   dplyr_1.1.4     purrr_1.0.2     readr_2.1.5    
[17] tidyr_1.3.1     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      magick_2.8.5      commonmark_1.9.2  tidyselect_1.2.1 
[29] digest_0.6.37     stringi_1.8.4     labeling_0.4.3    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

Expand for GitHub Repo

The complete code for this analysis is available in mm_2025_07.qmd.

For the full repository, click here.

10. References

Expand for References

Article:
- Most Popular Valentine’s Candy by State: Most Popular Valentine’s Candy by State
Data:

Makeover Monday 2025 Week 07: Candystore.com

--- title: "Most Popular Valentine's Candy Across U.S. States (2024)" subtitle: "Number of states ranking each candy as their 1st, 2nd, or 3rd choice" description: "Explore the sweet preferences across America with this visualization of Valentine's candy rankings. Using data from Candystore.com, this analysis reveals which candies dominate the Valentine's season, with Conversation Hearts and Heart-Shaped Chocolates emerging as clear favorites among U.S. states." author: "Steven Ponce" date: "2025-02-09" categories: ["MakeoverMonday", "2025"] tags: [ "ggplot2", "tidyverse", "Valentine's Day", "candy", "rankings", "consumer preferences", "state data", "stacked bar chart", "candystore" ] image: "thumbnails/mm_2025_07.png" format: html: toc: true toc-depth: 5 code-link: true code-fold: true code-tools: true code-summary: "Show code" editor_options: chunk_output_type: inline execute: freeze: true cache: true error: false message: false warning: false eval: true # filters: # - social-share # share: # permalink: "https://stevenponce.netlify.app/data_visualizations/MakeoverMonday/2025/mm_2025_07.html" # description: "Discover which Valentine's candies are most popular across U.S. states in 2024! From Conversation Hearts to M&M's, see how different states rank their favorite sweet treats. #DataViz #MakeoverMonday #rstats" # twitter: true # linkedin: true # email: true # facebook: false # reddit: false # stumble: false # tumblr: false # mastodon: true # bsky: true --- ### Original The original visualization Most Popular Valentine's Candy by State comes from [Candystore.com](https://www.candystore.com/blogs/holidays/valentines-candy-popular-states) ![Original visualization](https://raw.githubusercontent.com/poncest/MakeoverMonday/master/2025/Week_07/original_chart.png) ### Makeover ![A horizontal stacked bar chart showing Valentine's candy preferences across U.S. states in 2024. Each bar represents a candy type, with segments indicating the number of states ranking it as 1st, 2nd, or 3rd choice. Conversation Hearts leads with 46 states, followed by Heart-Shaped Box of Chocolates with 37 states. The remaining candies, including M&M's, Hershey Kisses, and others, received fewer state rankings.](mm_2025_07.png){#fig-1} ### <mark> **Steps to Create this Graphic** </mark> #### 1. Load Packages & Setup ```{r} #| label: load #| warning: false #| message: false #| results: "hide" ## 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 lubridate, # Make Dealing with Dates a Little Easier camcorder # Record Your Plot History ) }) ### |- figure size ---- gg_record( dir = here::here("temp_plots"), device = "png", width = 8, height = 8, units = "in", dpi = 320 ) # Source utility functions suppressMessages(source(here::here("R/utils/fonts.R"))) source(here::here("R/utils/social_icons.R")) source(here::here("R/utils/image_utils.R")) source(here::here("R/themes/base_theme.R")) ``` #### 2. Read in the Data ```{r} #| label: read #| include: true #| eval: true #| warning: false sv_candies_raw <- read_csv( here::here('data/MakeoverMonday_ SV_day.csv')) |> clean_names() ``` #### 3. Examine the Data ```{r} #| label: examine #| include: true #| eval: true #| results: 'hide' #| warning: false glimpse(sv_candies_raw) skim(sv_candies_raw) ``` #### 4. Tidy Data ```{r} #| label: tidy #| warning: false ### |- tidy data ---- sv_candies_clean <- sv_candies_raw |> rename_with(~str_remove(., "^x"), starts_with("x")) # Create long format data candies_long <- sv_candies_clean |> pivot_longer( cols = ends_with("2024"), names_to = "rank", values_to = "candy" ) |> # Clean up rank names mutate(rank = case_when( rank == "1st_place_2024" ~ "1st Place", rank == "2nd_place_2024" ~ "2nd Place", rank == "3rd_place_2024" ~ "3rd Place" ), rank = factor(rank, levels = c("1st Place", "2nd Place", "3rd Place")) ) # Prepare data with totals candies_with_counts <- candies_long |> mutate(rank = factor(rank, levels = c("1st Place", "2nd Place", "3rd Place"))) |> count(candy, rank) |> group_by(candy) |> mutate( total = sum(n) ) |> ungroup() |> arrange(-total, candy) # Create total summary data total_summary <- candies_with_counts |> group_by(candy) |> summarize( total = sum(n), y = total, rank = "1st Place" ) ``` #### 5. Visualization Parameters ```{r} #| label: params #| include: true #| warning: false ### |- plot aesthetics ---- # Get base colors with custom palette colors <- get_theme_colors(palette = c("1st Place" = "#FFB6C1", "2nd Place" = "#FF69B4", "3rd Place" = "#C71585")) ### |- titles and caption ---- title_text <- str_glue("Most Popular Valentine's Candy Across U.S. States (2024)") subtitle_text <- str_glue("Number of states ranking each candy as their 1st, 2nd, or 3rd choice") # Create caption caption_text <- create_mm_caption( mm_year = 2025, mm_week = 07, source_text = "Candystore.com" ) ### |- fonts ---- setup_fonts() fonts <- get_font_families() ### |- plot theme ---- # Start with base theme base_theme <- create_base_theme(colors) # Add weekly-specific theme elements weekly_theme <- extend_weekly_theme( base_theme, theme( # Weekly-specific modifications axis.line.x = element_line(color = "#252525", linewidth = .2), panel.spacing.x = unit(2, 'lines'), panel.spacing.y = unit(1, 'lines'), panel.grid.major.x = element_line(color = alpha(colors[5], 0.2), linewidth = 0.2), panel.grid.major.y = element_blank(), panel.grid.minor = element_blank(), legend.position = "top" ) ) # Set theme theme_set(weekly_theme) ``` #### 6. Plot ```{r} #| label: plot #| warning: false ### |- Plot ---- p <- ggplot(candies_with_counts, aes(x = reorder(candy, total), y = n, fill = rank)) + # Geoms geom_col() + geom_text(aes(label = n), position = position_stack(vjust = 0.5), color = "white", size = 3) + geom_text(data = total_summary, aes(y = y, label = paste0("(", total, ")")), hjust = -0.2, color = colors$text, size = 3) + # Scales scale_x_discrete() + scale_y_continuous( expand = expansion(mult = c(0, 0.1)) ) + coord_flip() + scale_fill_manual(values = colors$palette) + # Labs labs( x = NULL, y = "Number of States", fill = "Ranking", title = title_text, subtitle = subtitle_text, caption = caption_text ) + # Theme theme( plot.title = element_text( size = rel(1.6), family = fonts$title, face = "bold", color = colors$title, lineheight = 1.1, margin = margin(t = 5, b = 5) ), plot.subtitle = element_markdown( size = rel(1), family = fonts$subtitle, color = colors$subtitle, lineheight = 1.2, margin = margin(t = 5, b = 15) ), plot.caption = element_markdown( size = rel(0.6), family = fonts$caption, color = colors$caption, hjust = 0.5, margin = margin(t = 10) ) ) ``` #### 7. Save ```{r} #| label: save #| warning: false ### |- plot image ---- save_plot( p, type = "makeovermonday", year = 2025, week = 07, width = 8, height = 8 ) ``` #### 8. Session Info ::: {.callout-tip collapse="true"} ##### Expand for Session Info ```{r, echo = FALSE} #| eval: true #| warning: false sessionInfo() ``` ::: #### 9. GitHub Repository ::: {.callout-tip collapse="true"} ##### Expand for GitHub Repo The complete code for this analysis is available in [`mm_2025_07.qmd`](https://github.com/poncest/personal-website/blob/master/data_visualizations/MakeoverMonday/2025/mm_2025_07.qmd). For the full repository, [click here](https://github.com/poncest/personal-website/). ::: #### 10. References ::: {.callout-tip collapse="true"} ##### Expand for References 1. Article: - Most Popular Valentine's Candy by State: [Most Popular Valentine's Candy by State](https://www.candystore.com/blogs/holidays/valentines-candy-popular-states) 2. Data: - Makeover Monday 2025 Week 07: [Candystore.com](https://data.world/makeovermonday/2025-week-7-most-popular-valentines-candy-by-state) :::