Package {ekioplot}

Type:	Package
Title:	EKIO Visual Identity for 'ggplot2'
Version:	1.1.0
Description:	Implements EKIO's visual identity for data visualization with 'ggplot2'. Supplies a coordinated theme, color palettes, discrete and continuous scales, and helpers for accessible text contrast. Includes high-level recipes for common charts so analysts can create consistent, publication-ready graphics with concise code.
URL:	https://viniciusoike.github.io/ekioplot/, https://github.com/viniciusoike/ekioplot
License:	MIT + file LICENSE
Copyright:	file inst/COPYRIGHTS
Depends:	R (≥ 4.1.0)
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	7.3.3
Imports:	cli, ggplot2 (≥ 4.0.0), grDevices, rlang, systemfonts
Suggests:	dplyr, knitr, rmarkdown, testthat (≥ 3.0.0), tibble, yaml
VignetteBuilder:	knitr
Config/testthat/edition:	3
Config/Needs/website:	reactable
NeedsCompilation:	no
Packaged:	2026-08-25 17:53:34 UTC; viniciusreginatto
Author:	Vinicius Oike [aut, cre, cph]
Maintainer:	Vinicius Oike <viniciusor@ekio.io>
Repository:	CRAN
Date/Publication:	2026-09-08 12:30:30 UTC

Brazilian municipal crop production, 2022

Description

Municipal production of soybeans, corn and sugarcane from IBGE's Municipal Agricultural Production Survey (PAM).

Usage

brazil_agriculture

Format

A tibble with 16,689 rows and 12 variables:

code_muni

IBGE municipality code (numeric)

name_muni

Municipality name (character)

name_state

State name (character)

name_region

Brazilian region (character)

crop

Crop name (character)

production_tonnes

Production volume, tonnes (numeric)

area_harvested_ha

Harvested area, hectares (numeric)

yield

Productivity, tonnes per hectare (numeric)

crop_type

Crop cycle (character)

crop_category

Crop category (character)

crop_importance

Economic importance (character)

production_scale

Production-scale category (integer)

Source

IBGE, Table 1612: Municipal Agricultural Production (PAM). https://sidra.ibge.gov.br/tabela/1612

References

IBGE. (2023). Produção Agrícola Municipal - PAM 2022.

Brazilian state crop production, 1974–2023

Description

Annual production of seven major crops by Brazilian state from IBGE's Municipal Agricultural Production Survey (PAM).

Usage

brazil_agriculture_states

Format

A tibble with 9,450 rows and 8 variables:

code_state

IBGE state code (numeric)

name_state

State name (character)

year

Observation year (numeric)

crop

Crop name (character)

production_tonnes

Production volume, tonnes (numeric)

area_harvested_ha

Harvested area, hectares (numeric)

yield_kg_per_ha

Productivity, kilograms per hectare (numeric)

production_value_brl_k

Production value, thousands of Brazilian reais (numeric)

Details

Crops are beans, corn, cotton, rice, soybeans, sugarcane and wheat.

Source

IBGE, Table 1612: Municipal Agricultural Production (PAM). https://sidra.ibge.gov.br/tabela/1612

References

IBGE. (2023). Produção Agrícola Municipal - PAM 2022.

Brazilian municipal GDP, 2021

Description

Municipal GDP for all 5,570 Brazilian municipalities, at current prices.

Usage

brazil_gdp

Format

A tibble with 5,570 rows and 7 variables:

code_muni

IBGE municipality code (numeric)

name_muni

Municipality name (character)

code_state

IBGE state code (numeric)

name_state

State name (character)

year

Observation year (numeric)

gdp_brl_k

GDP, thousands of Brazilian reais (numeric)

gdp_brl_m

GDP, millions of Brazilian reais (numeric)

Source

IBGE, Table 5938: GDP and other aggregates by municipality. https://sidra.ibge.gov.br/tabela/5938

References

IBGE. (2023). Produto Interno Bruto dos Municípios - 2021.

Brazilian municipal population, 2025

Description

Population estimates for Brazil's 338 municipalities with more than 100,000 inhabitants.

Usage

brazil_population

Format

A tibble with 338 rows and 5 variables:

rank

Population rank (numeric)

name_muni

Municipality name (character)

abbrev_state

State abbreviation (character)

population

2025 population estimate (numeric)

category

Ordered city-size category (factor)

Details

Categories are Metropolis (1M+), Large city (500K–1M), Medium city (200K–500K) and Small city (100K–200K).

Source

IBGE, Table 6579: Municipal population estimates. https://sidra.ibge.gov.br/tabela/6579

EKIO Area Plot

Description

Professional area plot with smart aesthetic detection. Supports stacked and filled (proportional) area charts.

Usage

ekio_areaplot(
  data,
  x,
  y,
  fill = NULL,
  palette = NULL,
  position = "stack",
  alpha = 1,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

Value

ggplot2 object

Examples

ekio_areaplot(ggplot2::economics, date, unemploy)

# Stacked area with normalized economic series
economic_series <- subset(
  ggplot2::economics_long,
  variable %in% c("pce", "psavert", "uempmed")
)
ekio_areaplot(economic_series, date, value01, fill = variable)

EKIO Bar Plot

Description

Professional bar plot with smart aesthetic detection.

Usage

ekio_barplot(
  data,
  x,
  y,
  fill = NULL,
  palette = NULL,
  horizontal = FALSE,
  bar_width = 0.8,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

Value

ggplot2 object

Examples

cyl_counts <- as.data.frame(table(cyl = mtcars$cyl))
names(cyl_counts)[2] <- "n"
ekio_barplot(cyl_counts, cyl, n)

WCAG Contrast Ratio Between Two Colors

Description

Computes the contrast ratio between foreground and background colors as defined by WCAG 2.1. Ratios range from 1 (no contrast) to 21 (black on white). WCAG requires at least 4.5 for normal text (level AA), 3.0 for large text (AA), and 7.0 for normal text at level AAA.

Usage

ekio_contrast(color, background = "white")

Arguments

Value

Numeric vector of contrast ratios between 1 and 21

See Also

ekio_text_on() to pick a readable text color for a background

Examples

ekio_contrast("black", "white")
ekio_contrast(ekio_pal("blue")["700"])
ekio_contrast("white", ekio_pal("blue"))

EKIO Histogram

Description

Professional histogram with smart aesthetic detection.

Usage

ekio_histogram(
  data,
  x,
  fill = NULL,
  palette = NULL,
  bins = "sturges",
  binwidth = NULL,
  border_color = "white",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

Value

ggplot2 object

Examples

ekio_histogram(mtcars, mpg)
ekio_histogram(mtcars, mpg, fill = "steelblue")
ekio_histogram(mtcars, mpg, fill = factor(cyl), palette = "full")

EKIO Line Plot

Description

Professional line plot with smart aesthetic detection.

Usage

ekio_lineplot(
  data,
  x,
  y,
  color = NULL,
  palette = NULL,
  add_zero = FALSE,
  line_width = 0.8,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

Value

ggplot2 object

Examples

ekio_lineplot(ggplot2::economics, date, unemploy)

Get Color Palette

Description

Returns colors for data visualization. Includes EKIO brand scales, accent and categorical palettes, and standard scientific palettes. When printed interactively, displays the palette as a colored swatch with hex labels.

Usage

ekio_pal(palette = "full", n = NULL, reverse = FALSE)

Arguments

Details

Brand scales ("blue", "gray", "stone", "teal", "green", "orange", "red") are nine-step ramps running light to dark, named by shade. Position and shade are aligned by construction, so ekio_pal("blue")[7] and ekio_pal("blue")["700"] are the same color.

"gold" is an accent rather than a scale: three colors named "light", "mid" and "deep", because a nine-step gold ramp turns brown at the dark end. They sit on the same lightness rungs as scale shades 300, 400 and 500.

"accent_blue" and "accent_orange" put one main color before a sequence of receding grays. They return four colors by default; n can be set from 2 to 6 to match the number of series while keeping the main color first.

Value

Object of class ekio_palette (a character vector of hex codes). Printing displays a visual swatch. Use as.character() to strip the class.

Source

The brand scales are generated from one OKLCH specification in data-raw/build-ramps.R: a shared lightness spine anchored on the brand navy, a shared chroma arc, and a hue path per family. The scientific palettes come from matplotlib ("viridis", "inferno", "plasma") and from Okabe & Ito ("okabe_ito"). Notices are in inst/COPYRIGHTS.

Examples

ekio_pal("full")
ekio_pal("full", n = 4)
ekio_pal("full", reverse = TRUE)
ekio_pal("accent_blue", n = 5)
ekio_pal("okabe_ito")

# Brand scales are named by shade; position i is shade i * 100
ekio_pal("blue")["700"]
ekio_pal("blue")[7]

# gold is an accent, named rather than numbered
ekio_pal("gold")["mid"]

EKIO Scatter Plot

Description

Professional scatter plot with smart aesthetic detection.

Usage

ekio_scatterplot(
  data,
  x,
  y,
  color = NULL,
  size = NULL,
  palette = NULL,
  add_zero = FALSE,
  add_smooth = FALSE,
  smooth_method = "lm",
  point_size = 2.5,
  point_alpha = 0.8,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ...
)

Arguments

Value

ggplot2 object

Examples

ekio_scatterplot(mtcars, wt, mpg)
ekio_scatterplot(mtcars, wt, mpg, color = factor(cyl))

Pick a Readable Text Color for a Background

Description

Returns the text color (dark or light) with the higher WCAG contrast ratio against each background color. Useful for labels placed on colored fills, e.g. in ggplot2::geom_text().

Usage

ekio_text_on(background, dark = "black", light = "white")

Arguments

Value

Character vector of text colors, one per background. Names of background are preserved.

See Also

ekio_contrast() for the underlying contrast ratios

Examples

ekio_text_on(ekio_pal("blue")["700"])
ekio_text_on(ekio_pal("blue"))
ekio_text_on(ekio_pal("full"), dark = ekio_pal("gray")["900"])

List Available Palettes

Description

Returns names of all available palettes, optionally filtered by type.

Usage

list_ekio_palettes(type = "all")

Arguments

Value

Character vector of palette names, or named list if type = "all".

Examples

list_ekio_palettes()
list_ekio_palettes("categorical")

Continuous Color Scale

Description

Apply sequential or diverging palettes to continuous/numeric data.

Usage

scale_color_ekio_c(palette = "blue", reverse = FALSE, ...)

scale_colour_ekio_c(palette = "blue", reverse = FALSE, ...)

scale_fill_ekio_c(palette = "blue", reverse = FALSE, ...)

Arguments

Value

A ggplot2 scale object

See Also

scale_fill_ekio_c(), list_ekio_palettes()

Examples

library(ggplot2)
ggplot(mtcars, aes(wt, mpg, color = hp)) +
  geom_point(size = 3) +
  scale_color_ekio_c()

ggplot(mtcars, aes(wt, mpg, color = hp)) +
  geom_point(size = 3) +
  scale_color_ekio_c("stone")

Discrete Color Scale

Description

Apply qualitative palettes to discrete/categorical data.

Usage

scale_color_ekio_d(palette = "full", reverse = FALSE, ...)

scale_colour_ekio_d(palette = "full", reverse = FALSE, ...)

scale_fill_ekio_d(palette = "full", reverse = FALSE, ...)

Arguments

Value

A ggplot2 scale object

See Also

ekio_pal(), scale_fill_ekio_d()

Examples

library(ggplot2)
ggplot(mtcars, aes(wt, mpg, color = factor(cyl))) +
  geom_point(size = 3) +
  scale_color_ekio_d()

Apply EKIO Theme to ggplot2 Plots

Description

A minimal, professional theme for EKIO visualizations built on ggplot2::theme_minimal().

Usage

theme_ekio(
  base_size = 11,
  font_title = "Lora",
  font_text = "Lato",
  title_align = "plot",
  grid = "y",
  ticks = "x",
  background = "offwhite",
  ...
)

Arguments

Value

A ggplot2 theme object

Examples

ggplot2::ggplot(mtcars, ggplot2::aes(wt, mpg)) +
  ggplot2::geom_point() +
  theme_ekio(font_title = "serif", font_text = "sans")