• Steven Ponce
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  • Steps to Create this Graphic
    • 1. Load Packages & Setup
    • 2. Read in the Data
    • 3. Examine the Data
    • 4. Tidy Data
    • 5. Visualization Parameters
    • 6. Plot
    • 7. Save
    • 8. Session Info
    • 9. GitHub Repository
    • 10. References

Meteorite Mass Distribution and Uncertainty

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Observed falls show less uncertainty than found meteorites across all classes

30DayChartChallenge
Data Visualization
R Programming
2025
An exploration of uncertainty in extraterrestrial meteorite mass measurements, comparing observed meteorite falls versus those found later. This visualization reveals how discovery conditions impact measurement precision across different meteorite classes.
Published

April 29, 2025

Figure 1: A halfeye plot showing meteorite mass distribution by class (H Chondrite, L Chondrite, Pallasite, and Iron) with confidence intervals. Each class is split by discovery type (Observed Fall in purple, Found Later in teal).

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
  lubridate,      # Make Dealing with Dates a Little Easier
  ggdist,         # Visualizations of Distributions and Uncertainty 
  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
meteorite_landings <- read_csv(
  here::here(
    "data/30DayChartChallenge/2025/Meteorite_Landings_20240731.csv")) |> 
  clean_names() 

3. Examine the Data

Show code
glimpse(meteorite_landings)
skim(meteorite_landings)

4. Tidy Data

Show code
### |- Tidy ----
meteorites <- meteorite_landings |> 
  mutate(
    fall = if_else(tolower(fall) == "fell", "Observed Fall", "Found Later"),
    mass_g = as.numeric(mass_g),
    year = as.numeric(year),
    class_simplified = case_when(
      str_detect(recclass, "^H") ~ "H Chondrite",
      str_detect(recclass, "^L") ~ "L Chondrite",
      str_detect(recclass, "^LL") ~ "LL Chondrite",
      str_detect(recclass, "Iron") ~ "Iron",
      str_detect(recclass, "Pallasite") ~ "Pallasite",
      TRUE ~ "Other"
    )
  ) |>
  filter(
    !is.na(mass_g) & !is.na(year) & !is.na(recclass),
    class_simplified %in% c("H Chondrite", "L Chondrite", "Iron", "Pallasite"),
    mass_g >= 10 & mass_g <= 100000
  ) 

# Class statistics 
class_stats <- meteorites |>
  group_by(class_simplified) |>
  summarize(
    median_mass = median(mass_g),
    count = n(),
    .groups = "drop"
  ) |>
  arrange(desc(median_mass))

# Reorder class factor levels based on median mass
meteorites <- meteorites |>
  mutate(
    class_simplified = factor(
      class_simplified, 
      levels = class_stats$class_simplified)
    )

5. Visualization Parameters

Show code
### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = c(
    "Observed Fall" = "#593C8F", "Found Later" = "#1B9AAA", "Other" = 'gray'
    )
  )          
 
### |-  titles and caption ----
# text
title_text    <- str_glue("Meteorite Mass Distribution and Uncertainty")

subtitle_text <- str_glue("Observed falls show less uncertainty than found meteorites across all classes")

caption_text <- create_dcc_caption(
  dcc_year = 2025,
  dcc_day = 29,
  source_text =  "Meteorite Landings. University of Rochester" 
)

### |-  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$title, size = rel(1.14), margin = margin(b = 10)),
    plot.subtitle = element_text(family = fonts$subtitle, color = colors$text, size = rel(0.78), margin = margin(b = 20)),
    
    # Legend
    legend.position = "bottom",
    
    # Axis elements
    axis.text = element_text(color = colors$text, size = rel(0.7)),
    axis.title.y = element_text(color = colors$text, size = rel(0.8), 
                                hjust = 0.5, margin = margin(r = 10)),
    axis.title.x = element_text(color = colors$text, size = rel(0.8), 
                                hjust = 0.5, margin = margin(t = 10)),
    
    axis.line.x = element_line(color = "gray50", linewidth = .2),
    
    # Grid elements
    panel.grid.minor.x = element_blank(),
    panel.grid.minor.y = element_blank(),
    panel.grid.major.y = element_line(color = "gray65", linewidth = 0.05),
    panel.grid.major.x = element_line(color = "gray65", linewidth = 0.05),
    
    # Plot margins 
    plot.margin = margin(t = 10, r = 20, b = 10, l = 20),
  )
)

# Set theme
theme_set(weekly_theme) 

6. Plot

Show code
### |-  Plot ----
p <- ggplot(meteorites, aes(x = class_simplified, y = mass_g, fill = fall)) +
  # Geoms
  stat_halfeye(
    aes(fill = fall),
    .width = c(0.50, 0.80, 0.95),
    interval_alpha = 0.8,
    slab_alpha = 0.7,
    point_alpha = 1.0,
    scale = 0.8,
    position = position_dodge(width = 0.6),
    color = "black"
  ) +
  # Scales
  scale_y_log10(
    labels = function(x) paste0(x / 1000, " kg"),
    breaks = c(10, 100, 1000, 10000, 100000)
  ) +
  scale_fill_manual(
    values = colors$palette,
    name = "Discovery Type"
  ) +
  scale_x_discrete(
    labels = function(x) {
      counts <- class_stats$count[match(x, class_stats$class_simplified)]
      paste0(x, "\n(n= ", scales::comma(counts), ")")
    }
  ) +
  coord_flip() +
  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text,
    x = NULL,
    y = "Mass (kilograms, log scale)"
  ) +
  # Theme
  theme(
    plot.title = element_text(
      size = rel(1.9),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.85),
      family = fonts$subtitle,
      color = colors$subtitle,
      lineheight = 0.8,
      margin = margin(t = 5, b = 20)
    ),
    plot.caption = element_markdown(
      size = rel(0.6),
      family = fonts$caption,
      color = colors$caption,
      lineheight = 0.65,
      hjust = 0.5,
      halign = 0.5,
      margin = margin(t = 10, b = 5)
    ),
  )

7. Save

Show code
### |-  plot image ----  
save_plot(
  p, 
  type = "30daychartchallenge", 
  year = 2025, 
  day = 29, 
  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] here_1.0.1      camcorder_0.1.0 ggdist_3.3.2    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   
 [4] tzdb_0.5.0           vctrs_0.6.5          tools_4.4.0         
 [7] generics_0.1.3       curl_6.0.0           parallel_4.4.0      
[10] gifski_1.32.0-1      fansi_1.0.6          pacman_0.5.1        
[13] pkgconfig_2.0.3      distributional_0.5.0 lifecycle_1.0.4     
[16] farver_2.1.2         compiler_4.4.0       textshaping_0.4.0   
[19] munsell_0.5.1        repr_1.1.7           codetools_0.2-20    
[22] snakecase_0.11.1     htmltools_0.5.8.1    yaml_2.3.10         
[25] crayon_1.5.3         pillar_1.9.0         magick_2.8.5        
[28] commonmark_1.9.2     tidyselect_1.2.1     digest_0.6.37       
[31] stringi_1.8.4        labeling_0.4.3       rsvg_2.6.1          
[34] rprojroot_2.0.4      fastmap_1.2.0        grid_4.4.0          
[37] colorspace_2.1-1     cli_3.6.4            magrittr_2.0.3      
[40] base64enc_0.1-3      utf8_1.2.4           withr_3.0.2         
[43] bit64_4.5.2          timechange_0.3.0     rmarkdown_2.29      
[46] bit_4.5.0            ragg_1.3.3           hms_1.1.3           
[49] evaluate_1.0.1       knitr_1.49           markdown_1.13       
[52] rlang_1.1.6          gridtext_0.1.5       Rcpp_1.0.13-1       
[55] glue_1.8.0           xml2_1.3.6           renv_1.0.3          
[58] vroom_1.6.5          svglite_2.1.3        rstudioapi_0.17.1   
[61] jsonlite_1.8.9       R6_2.5.1             systemfonts_1.1.0   

9. GitHub Repository

Expand for GitHub Repo

The complete code for this analysis is available in 30dcc_2025_29.qmd.

For the full repository, click here.

10. References

Expand for References
  1. Data Sources:
    • Pandit, Aabha; Romanowski, Alois; Owen, Heather (2024). Meteorite Landings. University of Rochester.
Back to top
Source Code
---
title: "Meteorite Mass Distribution and Uncertainty"
subtitle: "Observed falls show less uncertainty than found meteorites across all classes"
description: "An exploration of uncertainty in extraterrestrial meteorite mass measurements, comparing observed meteorite falls versus those found later. This visualization reveals how discovery conditions impact measurement precision across different meteorite classes."
date: "2025-04-29" 
categories: ["30DayChartChallenge", "Data Visualization", "R Programming", "2025"]
tags: [
"meteorites", "uncertainty", "extraterrestrial", "ggdist", "halfeye plot", "confidence intervals", "statistical uncertainty", "celestial objects", "space rocks", "astronomy"
  ]
image: "thumbnails/30dcc_2025_29.png"
format:
  html:
    toc: true
    toc-depth: 5
    code-link: true
    code-fold: true
    code-tools: true
    code-summary: "Show code"
    self-contained: true
    theme: 
      light: [flatly, assets/styling/custom_styles.scss]
      dark: [darkly, assets/styling/custom_styles_dark.scss]
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/30DayChartChallenge/2025/30dcc_2025_29.html"
#   description: "Day 29 of #30DayChartChallenge: Uncertainties & Extraterrestrial. Visualizing how discovery methods affect measurement uncertainty in meteorite masses."
#   twitter: true
#   linkedin: true
#   email: true
#   facebook: false
#   reddit: false
#   stumble: false
#   tumblr: false
#   mastodon: true
#   bsky: true
---

![A halfeye plot showing meteorite mass distribution by class (H Chondrite, L Chondrite, Pallasite, and Iron) with confidence intervals. Each class is split by discovery type (Observed Fall in purple, Found Later in teal).](30dcc_2025_29.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
  lubridate,      # Make Dealing with Dates a Little Easier
  ggdist,         # Visualizations of Distributions and Uncertainty 
  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

meteorite_landings <- read_csv(
  here::here(
    "data/30DayChartChallenge/2025/Meteorite_Landings_20240731.csv")) |> 
  clean_names() 
```

#### 3. Examine the Data

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

glimpse(meteorite_landings)
skim(meteorite_landings)
```

#### 4. Tidy Data

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

### |- Tidy ----
meteorites <- meteorite_landings |> 
  mutate(
    fall = if_else(tolower(fall) == "fell", "Observed Fall", "Found Later"),
    mass_g = as.numeric(mass_g),
    year = as.numeric(year),
    class_simplified = case_when(
      str_detect(recclass, "^H") ~ "H Chondrite",
      str_detect(recclass, "^L") ~ "L Chondrite",
      str_detect(recclass, "^LL") ~ "LL Chondrite",
      str_detect(recclass, "Iron") ~ "Iron",
      str_detect(recclass, "Pallasite") ~ "Pallasite",
      TRUE ~ "Other"
    )
  ) |>
  filter(
    !is.na(mass_g) & !is.na(year) & !is.na(recclass),
    class_simplified %in% c("H Chondrite", "L Chondrite", "Iron", "Pallasite"),
    mass_g >= 10 & mass_g <= 100000
  ) 

# Class statistics 
class_stats <- meteorites |>
  group_by(class_simplified) |>
  summarize(
    median_mass = median(mass_g),
    count = n(),
    .groups = "drop"
  ) |>
  arrange(desc(median_mass))

# Reorder class factor levels based on median mass
meteorites <- meteorites |>
  mutate(
    class_simplified = factor(
      class_simplified, 
      levels = class_stats$class_simplified)
    )
```

#### 5. Visualization Parameters

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

### |-  plot aesthetics ----
colors <- get_theme_colors(
  palette = c(
    "Observed Fall" = "#593C8F", "Found Later" = "#1B9AAA", "Other" = 'gray'
    )
  )          
 
### |-  titles and caption ----
# text
title_text    <- str_glue("Meteorite Mass Distribution and Uncertainty")

subtitle_text <- str_glue("Observed falls show less uncertainty than found meteorites across all classes")

caption_text <- create_dcc_caption(
  dcc_year = 2025,
  dcc_day = 29,
  source_text =  "Meteorite Landings. University of Rochester" 
)

### |-  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$title, size = rel(1.14), margin = margin(b = 10)),
    plot.subtitle = element_text(family = fonts$subtitle, color = colors$text, size = rel(0.78), margin = margin(b = 20)),
    
    # Legend
    legend.position = "bottom",
    
    # Axis elements
    axis.text = element_text(color = colors$text, size = rel(0.7)),
    axis.title.y = element_text(color = colors$text, size = rel(0.8), 
                                hjust = 0.5, margin = margin(r = 10)),
    axis.title.x = element_text(color = colors$text, size = rel(0.8), 
                                hjust = 0.5, margin = margin(t = 10)),
    
    axis.line.x = element_line(color = "gray50", linewidth = .2),
    
    # Grid elements
    panel.grid.minor.x = element_blank(),
    panel.grid.minor.y = element_blank(),
    panel.grid.major.y = element_line(color = "gray65", linewidth = 0.05),
    panel.grid.major.x = element_line(color = "gray65", linewidth = 0.05),
    
    # Plot margins 
    plot.margin = margin(t = 10, r = 20, b = 10, l = 20),
  )
)

# Set theme
theme_set(weekly_theme) 
```

#### 6. Plot

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

### |-  Plot ----
p <- ggplot(meteorites, aes(x = class_simplified, y = mass_g, fill = fall)) +
  # Geoms
  stat_halfeye(
    aes(fill = fall),
    .width = c(0.50, 0.80, 0.95),
    interval_alpha = 0.8,
    slab_alpha = 0.7,
    point_alpha = 1.0,
    scale = 0.8,
    position = position_dodge(width = 0.6),
    color = "black"
  ) +
  # Scales
  scale_y_log10(
    labels = function(x) paste0(x / 1000, " kg"),
    breaks = c(10, 100, 1000, 10000, 100000)
  ) +
  scale_fill_manual(
    values = colors$palette,
    name = "Discovery Type"
  ) +
  scale_x_discrete(
    labels = function(x) {
      counts <- class_stats$count[match(x, class_stats$class_simplified)]
      paste0(x, "\n(n= ", scales::comma(counts), ")")
    }
  ) +
  coord_flip() +
  # Labs
  labs(
    title = title_text,
    subtitle = subtitle_text,
    caption = caption_text,
    x = NULL,
    y = "Mass (kilograms, log scale)"
  ) +
  # Theme
  theme(
    plot.title = element_text(
      size = rel(1.9),
      family = fonts$title,
      face = "bold",
      color = colors$title,
      margin = margin(t = 5, b = 5)
    ),
    plot.subtitle = element_markdown(
      size = rel(0.85),
      family = fonts$subtitle,
      color = colors$subtitle,
      lineheight = 0.8,
      margin = margin(t = 5, b = 20)
    ),
    plot.caption = element_markdown(
      size = rel(0.6),
      family = fonts$caption,
      color = colors$caption,
      lineheight = 0.65,
      hjust = 0.5,
      halign = 0.5,
      margin = margin(t = 10, b = 5)
    ),
  )
```

#### 7. Save

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

### |-  plot image ----  
save_plot(
  p, 
  type = "30daychartchallenge", 
  year = 2025, 
  day = 29, 
  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 [`30dcc_2025_29.qmd`](https://github.com/poncest/personal-website/blob/master/data_visualizations/TidyTuesday/2025/30dcc_2025_29.qmd).

For the full repository, [click here](https://github.com/poncest/personal-website/).
:::


#### 10. References
::: {.callout-tip collapse="true"}
##### Expand for References

1. Data Sources:
   - Pandit, Aabha; Romanowski, Alois; Owen, Heather (2024). [Meteorite Landings. University of Rochester.](https://doi.org/10.60593/ur.d.26462452.v1)
  
:::

© 2024 Steven Ponce

Source Issues