Meteorite Mass Distribution and Uncertainty

Observed falls show less uncertainty than found meteorites across all classes

30DayChartChallenge

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

Data Sources:
- Pandit, Aabha; Romanowski, Alois; Owen, Heather (2024). Meteorite Landings. University of Rochester.

--- 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", "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" 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) :::