Recipe Complexity Correlates with Higher Ratings

Analysis of 14,426 AllRecipes.com recipes shows consistent rating patterns

A heat map analysis revealing that recipe complexity—measured by ingredient count and cooking time—correlates with higher user ratings across 14,426 AllRecipes.com recipes. The visualization shows a clear pattern where more complex recipes consistently achieve better ratings.

Figure 1: Heat map showing recipe ratings by complexity, with cooking time on y-axis (≤30 min to 4+ hours) and ingredient count on x-axis (1-5 to 20+ ingredients). Color scale from dark blue (4.45 rating) to light green (4.63 rating) reveals higher ratings for recipes with more ingredients and longer cooking times. Each cell shows the average rating and recipe count from 14,426 AllRecipes.com recipes.

Steps to Create this Graphic

1. Load Packages & Setup

```{r}
#| label: load
#| warning: false
#| message: false
#| results: "hide"

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
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
    scales,      # Scale Functions for Visualization
    glue,        # Interpreted String Literals,
    viridis      # Colorblind-Friendly Color Maps for R
  )})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 8,
  height = 8,
  units  = "in",
  dpi    = 300
)

# 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

tt <- tidytuesdayR::tt_load(2025, week = 37)

all_recipes <- tt$all_recipes |> clean_names()
cuisines <- tt$cuisines |> clean_names()

tidytuesdayR::readme(tt)
rm(tt)
```

3. Examine the Data

```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(all_recipes)
glimpse(cuisines)
```

4. Tidy Data

```{r}
#| label: tidy
#| warning: false

complexity_analysis <- all_recipes |>
  # Drop rows with missing key fields
  filter(
    !is.na(ingredients),
    !is.na(prep_time),
    !is.na(cook_time),
    !is.na(avg_rating)
  ) |>
  mutate(
    # Count ingredients (#commas + 1)
    ingredient_count = str_count(ingredients, ",") + 1,

    # Bin total time (minutes)
    total_time_binned = cut(
      total_time,
      breaks = c(0, 30, 60, 120, 240, Inf),
      labels = c("≤30 min", "31-60 min", "1-2 hours", "2-4 hours", "4+ hours"),
      include.lowest = TRUE
    ),

    # Bin ingredient count
    ingredient_binned = cut(
      ingredient_count,
      breaks = c(0, 5, 10, 15, 20, Inf),
      labels = c("1-5", "6-10", "11-15", "16-20", "20+"),
      include.lowest = TRUE
    )
  ) |>
  # Keep only rows with valid bins
  filter(!is.na(total_time_binned), !is.na(ingredient_binned)) |>
  # Aggregate by bins
  group_by(total_time_binned, ingredient_binned) |>
  summarise(
    avg_rating = mean(avg_rating, na.rm = TRUE),
    recipe_count = n(),
    median_rating = median(avg_rating, na.rm = TRUE),
    .groups = "drop"
  ) |>
  # Keep cells with ≥10 recipes
  filter(recipe_count >= 10)
```

5. Visualization Parameters

```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
# Get basic theme colors
colors <- get_theme_colors()

### |- titles and caption ----
title_text <- str_glue("Recipe Complexity Correlates with Higher Ratings")

subtitle_text <- str_glue(
  "Analysis of **14,426 AllRecipes.com recipes** shows consistent rating patterns<br><br>",
  "Cells show average rating and recipe count• Color scale = observed range: 4.45-4.63"
)

caption_text <- create_social_caption(
  tt_year = 2025,
  tt_week = 37,
  source_text = "tastyR (AllRecipes.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(
    # Text styling
    plot.title = element_text(face = "bold", family = fonts$title, size = rel(1.2), color = colors$title, margin = margin(b = 10)),
    plot.subtitle = element_text(family = fonts$subtitle, lineheight = 1.2, color = colors$subtitle, size = rel(0.78), margin = margin(b = 20)),

    # Axis elements
    axis.line = element_blank(),
    axis.ticks = element_blank(),

    # Grid elements
    panel.grid.major = element_line(color = "gray90", linetype = "solid", linewidth = 0.3),
    # panel.grid.major.y = element_blank(),
    panel.grid.minor.x = element_blank(),
    panel.grid.minor.y = element_blank(),

    # Axis elements
    axis.text = element_text(color = colors$text, size = rel(0.7)),
    axis.title.x = element_text(color = colors$text, face = "bold", size = rel(0.8), margin = margin(t = 15)),
    axis.title.y = element_text(color = colors$text, face = "bold", size = rel(0.8), margin = margin(r = 10)),

    # Legend elements
    legend.position = "right",
    legend.title = element_text(family = fonts$tsubtitle, color = colors$text, size = rel(0.8), face = "bold"),
    legend.text = element_text(family = fonts$tsubtitle, color = colors$text, size = rel(0.7)),
    legend.margin = margin(t = 15),

    # Plot margin
    plot.margin = margin(t = 15, r = 15, b = 15, l = 15),
  )
)

# Set theme
theme_set(weekly_theme)

# Viz parameters for heatmap color scale 

# Min and max observed average ratings
r_min <- min(complexity_analysis$avg_rating, na.rm = TRUE)
r_max <- max(complexity_analysis$avg_rating, na.rm = TRUE)

# Padding to avoid clipping at legend edges
pad   <- 0.005

# Scale limits (min/max + padding)
limits <- c(r_min - pad, r_max + pad)

# Midpoint (useful for diverging palettes)
r_mid <- mean(limits)
```

6. Plot

```{r}
#| label: plot
#| warning: false

### |-  Final plot ----
p <- complexity_analysis |>
  ggplot(aes(x = ingredient_binned, y = total_time_binned, fill = avg_rating)) +

  # Geoms
  geom_tile(color = "white", linewidth = 0.6) +
  geom_text(
    aes(
      label = paste0(sprintf("%.2f", avg_rating), "\n(n=", comma(recipe_count), ")"),
      color = ifelse(avg_rating <= r_mid, "white", "#1a1a1a")
    ),
    fontface = "bold", size = 3.2, lineheight = 0.9, show.legend = FALSE
  ) +

  # Scales
  scale_color_identity() +
  scale_fill_viridis_c(
    option = "mako",
    limits = limits,
    oob = squish,
    breaks = pretty_breaks(4),
    labels = number_format(accuracy = 0.01),
    name = "Average Rating"
  ) +

  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text,
    x = "Number of Ingredients",
    y = "Total Cooking Time",
  ) +

  # Theme
  theme(
    panel.grid = element_blank(),
    legend.title = element_text(size = 10, face = "bold"),
    legend.key.width = unit(0.7, "cm"),
    legend.key.height = unit(1.0, "cm"),
    plot.title = element_text(
      size = rel(1.4),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      lineheight = 1.1,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.80),
      family = fonts$subtitle,
      color = alpha(colors$subtitle, 0.9),
      lineheight = 1.2,
      margin = margin(t = 5, b = 10)
    ),
    plot.caption = element_markdown(
      size = rel(0.55),
      family = fonts$caption,
      color = colors$caption,
      hjust = 0.5,
      margin = margin(t = 10)
    )
  )
```

7. Save

```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot(
  plot = p, 
  type = "tidytuesday", 
  year = 2025, 
  week = 37, 
  width  = 8,
  height = 8
  )
```

8. Session Info

TipExpand 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] here_1.0.1        viridis_0.6.5     viridisLite_0.4.2 glue_1.8.0       
 [5] scales_1.3.0      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  
[21] pacman_0.5.1     

loaded via a namespace (and not attached):
 [1] gtable_0.3.6       httr2_1.0.6        xfun_0.49          htmlwidgets_1.6.4 
 [5] gh_1.4.1           tzdb_0.5.0         vctrs_0.6.5        tools_4.4.0       
 [9] generics_0.1.3     parallel_4.4.0     curl_6.0.0         gifski_1.32.0-1   
[13] fansi_1.0.6        pkgconfig_2.0.3    lifecycle_1.0.4    farver_2.1.2      
[17] compiler_4.4.0     textshaping_0.4.0  munsell_0.5.1      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_3.6.4          magrittr_2.0.3     utf8_1.2.4         withr_3.0.2       
[41] rappdirs_0.3.3     bit64_4.5.2        timechange_0.3.0   rmarkdown_2.29    
[45] tidytuesdayR_1.1.2 gitcreds_0.1.2     bit_4.5.0          gridExtra_2.3     
[49] ragg_1.3.3         hms_1.1.3          evaluate_1.0.1     knitr_1.49        
[53] markdown_1.13      rlang_1.1.6        gridtext_0.1.5     Rcpp_1.0.13-1     
[57] xml2_1.3.6         renv_1.0.3         vroom_1.6.5        svglite_2.1.3     
[61] rstudioapi_0.17.1  jsonlite_1.8.9     R6_2.5.1           systemfonts_1.1.0 

9. GitHub Repository

TipExpand for GitHub Repo

The complete code for this analysis is available in tt_2025_37.qmd.

For the full repository, click here.

10. References

TipExpand for References

1. Data Sources:

• TidyTuesday 2025 Week 36: [Allrecipes Data](https://github.com/rfordatascience/tidytuesday/blob/main/data/2025/2025-09-16