ribbon
economics
brazil
line graph
Author

Ana Luisa Bodevan

Published

January 27, 2026

This week challenge dataset in on Brazilian Companies. Check the TidyTuesday GitHub repo for the data.

1. SETUP

Code 
library(pacman)

pacman::p_load(tidytuesdayR, tidyverse, dplyr, janitor,
                ggtext, showtext, glue, ggbranding)

tuesdata <- tidytuesdayR::tt_load('2026-01-27')

companies <- tuesdata$companies |>
  janitor :: clean_names()

rm(tuesdata)

2. DATA ANALYSIS AND TIDYING

For this week, we will be looking into the GINI index to try to answer how unequal is the distribution of share capital among Brazilian firms.

Code 
library(ineq)

companies_clean <- companies |>
  filter(capital_stock > 0)

gini_overall <- ineq(companies_clean$capital_stock, type = "Gini")

gini_by_size <- companies_clean |>
  group_by(company_size) |>
  summarise(
    gini = ineq(capital_stock, type = "Gini"),
    n_firms = n(),
    .groups = "drop"
  )

gini_overall
[1] 0.9976102
Code 
gini_by_size
# A tibble: 3 × 3
  company_size      gini n_firms
  <chr>            <dbl>   <int>
1 micro-enterprise 0.986   66202
2 other            0.997   42520
3 small-enterprise 0.995   32610

Nearly perfectly unequal.

Code 
lorenz_obj <- Lc(companies_clean$capital_stock)

lorenz_df <- tibble(
  firm_share = lorenz_obj$p,
  capital_share = lorenz_obj$L
)

# Capital share held by top 10% of firms
top_10_capital <- 1 -
  lorenz_df$capital_share[
    which.min(abs(lorenz_df$firm_share - 0.9))
  ]

3. PLOT

Code 
background_col <- "#f9f9f9" #"#FDFDFD",  #"#f5f5f2"
title_col <- "gray20"
subtitle_col <- "gray30"
text_col <- "gray30"

# col <- c("name1" = "color1", "name2" = "color2")

font_add_google("Libre Franklin", "libre")

showtext_auto()

title <- "Brazilian Corporate Capital is Highly Unequal"
subtitle <- "Lorenz curve of declared share capital across Brazilian companies"

title_font <- "libre"
body_font <- "libre"

brand <- add_branding(
  github = "anabodevan",
  bluesky = "1141bode.bsky.social",
  text_size = "13pt",
  icon_size = "13pt",
  text_color = "black",
  icon_color = "black",
  line_spacing = 2L,
  text_position = "after",
  additional_text = "Data: CNPJ/Receita Federal, via dados.gov.br\n#TidyTuesday 2026 W4",
  additional_text_size = "10pt",
  additional_text_color = "black",
  text_family = body_font)
Code 
library(grid)

ggplot(lorenz_df, aes(x = firm_share, y = capital_share)) +
  # Inequality area
  geom_ribbon(
    aes(ymin = firm_share, ymax = capital_share),
    fill = "#C8E6C9",
    alpha = 0.6
  ) +
  # Lorenz curve
  geom_line(linewidth = 1.2, color = "#1B5E20") +
  # Equality line
  geom_abline(
    intercept = 0,
    slope = 1,
    linetype = "dashed",
    color = "gray60"
  ) +

  # Annotation explaining inequality
  annotate(
    "text",
    x = 0.55,
    y = 0.24,
    label = glue(
      "Top 10% of firms hold ~{round(top_10_capital * 100, 1)}%\n",
      "of declared corporate capital"
    ),
    family = body_font,
    size = 4,
    color = text_col,
    hjust = 0
  ) +

  labs(
    title = title,
    subtitle = subtitle,
    x = "Cumulative share of firms",
    y = "Cumulative share of capital stock"
  ) +

  coord_equal(clip = "off") +
  scale_x_continuous(expand = expansion(mult = c(0.02, 0.08))) +
  scale_y_continuous(expand = expansion(mult = c(0.02, 0.08))) +

  theme_minimal(base_family = body_font) +
  theme(
    plot.background = element_rect(fill = background_col, color = NA),
    panel.background = element_rect(fill = background_col, color = NA),
    plot.title = element_text(
      family = title_font,
      color = title_col,
      face = "bold",
      size = 20
    ),
    plot.subtitle = element_text(
      family = body_font,
      color = subtitle_col,
      size = 13
    ),
    axis.text = element_text(color = text_col),
    axis.title = element_text(color = text_col),
    plot.margin = margin(t = 20, r = 30, b = 40, l = 20)
  ) +

  add_branding(
    github = "anabodevan",
    bluesky = "1141bode.bsky.social",
    text_size = "10pt",
    icon_size = "10pt",
    text_color = "gray30",
    icon_color = "gray20",
    line_spacing = 1L,
    text_position = "after",
    additional_text = "Data: CNPJ/Receita Federal, via dados.gov.br | #TidyTuesday 2026 W4",
    additional_text_size = "10pt",
    additional_text_color = "gray30",
    text_family = body_font,
    caption_halign = 1,
    caption_margin = margin(t = 15, b = 5)
  )