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add caption example

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gnoblet 2025-07-01 19:48:13 +02:00
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README.Rmd
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@ -32,7 +32,7 @@ You can install the last version of visualizeR from [GitHub](https://github.com/
```{r, eval = FALSE} ```{r, eval = FALSE}
# install.packages("devtools") # install.packages("devtools")
devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE) devtools::install_github('gnoblet/visualizeR', build_vignettes = TRUE)
``` ```
## Roadmap ## Roadmap
@ -52,7 +52,7 @@ library(visualizeR)
color(unname = F)[1:10] color(unname = F)[1:10]
# Extract a color palette as hexadecimal codes and reversed # Extract a color palette as hexadecimal codes and reversed
palette(palette = "cat_5_main", reversed = TRUE, color_ramp_palette = FALSE) palette(palette = 'cat_5_main', reversed = TRUE, color_ramp_palette = FALSE)
# Get all color palettes names # Get all color palettes names
palette(show_palettes = TRUE) palette(show_palettes = TRUE)
@ -62,7 +62,7 @@ palette(show_palettes = TRUE)
### Example 1: Bar chart ### Example 1: Bar chart
```{r example-bar-chart, out.width = "65%", eval = TRUE} ```{r example-bar-chart, out.width = '65%', eval = TRUE}
library(palmerpenguins) library(palmerpenguins)
library(dplyr) library(dplyr)
@ -83,40 +83,40 @@ df_island <- penguins |>
ungroup() ungroup()
# Simple bar chart by group with some alpha transparency # Simple bar chart by group with some alpha transparency
bar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species") bar(df, 'island', 'mean_bl', 'species', x_title = 'Mean of bill length', title = 'Mean of bill length by island and species')
# Flipped / Horizontal # Flipped / Horizontal
hbar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species") hbar(df, 'island', 'mean_bl', 'species', x_title = 'Mean of bill length', title = 'Mean of bill length by island and species')
# Facetted # Facetted
bar(df, "island", "mean_bl", "species", facet = "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species", add_color_guide = FALSE) bar(df, 'island', 'mean_bl', facet = 'species', x_title = 'Mean of bill length', title = 'Mean of bill length by island and species', add_color_guide = FALSE)
# Flipped, with text, smaller width # Flipped, with text, smaller width, and caption
hbar(df = df_island, x = "island", y = "mean_bl", group = "island", title = "Mean of bill length by island", add_text = T, width = 0.6, add_text_suffix = "mm", add_text_expand_limit = 1.3, add_color_guide = FALSE) hbar(df = df_island, x = 'island', y = 'mean_bl', title = 'Mean of bill length by island', add_text = T, width = 0.6, add_text_suffix = 'mm', add_text_expand_limit = 1.3, add_color_guide = FALSE, caption = "Data: palmerpenguins package.")
``` ```
### Example 2: Scatterplot ### Example 2: Scatterplot
```{r example-point-chart, out.width = "65%", eval = TRUE} ```{r example-point-chart, out.width = '65%', eval = TRUE}
# Simple scatterplot # Simple scatterplot
point(penguins, "bill_length_mm", "flipper_length_mm") point(penguins, 'bill_length_mm', 'flipper_length_mm')
# Scatterplot with grouping colors, greater dot size, some transparency # Scatterplot with grouping colors, greater dot size, some transparency
point(penguins, "bill_length_mm", "flipper_length_mm", "island", group_title = "Island", alpha = 0.6, size = 3, title = "Bill vs. flipper length", , add_color_guide = FALSE) point(penguins, 'bill_length_mm', 'flipper_length_mm', 'island', group_title = 'Island', alpha = 0.6, size = 3, title = 'Bill vs. flipper length', , add_color_guide = FALSE)
# Facetted scatterplot by island # Facetted scatterplot by island
point(penguins, "bill_length_mm", "flipper_length_mm", "species", "island", "fixed", group_title = "Species", title = "Bill vs. flipper length by species and island", add_color_guide = FALSE) point(penguins, 'bill_length_mm', 'flipper_length_mm', 'species', 'island', 'fixed', group_title = 'Species', title = 'Bill vs. flipper length by species and island', add_color_guide = FALSE)
``` ```
### Example 3: Dumbbell plot ### Example 3: Dumbbell plot
Remember to ensure that your data are in the long format and you only have two groups on the x-axis; for instance, IDP and returnee and no NA values. Remember to ensure that your data are in the long format and you only have two groups on the x-axis; for instance, IDP and returnee and no NA values.
```{r example-dumbbell-plot, out.width = "65%", eval = TRUE} ```{r example-dumbbell-plot, out.width = '65%', eval = TRUE}
# Prepare long data # Prepare long data
df <- tibble::tibble( df <- tibble::tibble(
admin1 = rep(letters[1:8], 2), admin1 = rep(letters[1:8], 2),
setting = c(rep(c("Rural", "Urban"), 4), rep(c("Urban", "Rural"), 4)), setting = c(rep(c('Rural', 'Urban'), 4), rep(c('Urban', 'Rural'), 4)),
stat = rnorm(16, mean = 50, sd = 18) stat = rnorm(16, mean = 50, sd = 18)
) |> ) |>
dplyr::mutate(stat = round(stat, 0)) dplyr::mutate(stat = round(stat, 0))
@ -126,21 +126,21 @@ df <- tibble::tibble(
# dumbbell( # dumbbell(
# df, # df,
# "stat", # 'stat',
# "setting", # 'setting',
# "admin1", # 'admin1',
# title = "% of HHs that reported open defecation as sanitation facility", # title = '% of HHs that reported open defecation as sanitation facility',
# group_y_title = "Admin 1", # group_y_title = 'Admin 1',
# group_x_title = "Setting" # group_x_title = 'Setting'
# ) # )
``` ```
### Example 4: donut chart ### Example 4: donut chart
```{r example-donut-plot, out.width = "65%", warning = FALSE} ```{r example-donut-plot, out.width = '65%', warning = FALSE}
# Some summarized data: % of HHs by displacement status # Some summarized data: % of HHs by displacement status
df <- tibble::tibble( df <- tibble::tibble(
status = c("Displaced", "Non displaced", "Returnee", "Don't know/Prefer not to say"), status = c('Displaced', 'Non displaced', 'Returnee', 'Don\'t know/Prefer not to say'),
percentage = c(18, 65, 12, 3) percentage = c(18, 65, 12, 3)
) )
@ -149,33 +149,33 @@ df <- tibble::tibble(
# status, # status,
# percentage, # percentage,
# hole_size = 3, # hole_size = 3,
# add_text_suffix = "%", # add_text_suffix = '%',
# add_text_color = color("dark_grey"), # add_text_color = color('dark_grey'),
# add_text_treshold_display = 5, # add_text_treshold_display = 5,
# x_title = "Displacement status", # x_title = 'Displacement status',
# title = "% of HHs by displacement status" # title = '% of HHs by displacement status'
# ) # )
``` ```
### Example 5: Waffle chart ### Example 5: Waffle chart
```{r example-waffle-plot, out.width = "65%", warning = FALSE} ```{r example-waffle-plot, out.width = '65%', warning = FALSE}
# #
# waffle(df, status, percentage, x_title = "A caption", title = "A title", subtitle = "A subtitle") # waffle(df, status, percentage, x_title = 'A caption', title = 'A title', subtitle = 'A subtitle')
``` ```
### Example 6: Alluvial chart ### Example 6: Alluvial chart
```{r example-alluvial-plot, out.width = "65%", warning = FALSE} ```{r example-alluvial-plot, out.width = '65%', warning = FALSE}
# Some summarized data: % of HHs by self-reported status of displacement in 2021 and in 2022 # Some summarized data: % of HHs by self-reported status of displacement in 2021 and in 2022
df <- tibble::tibble( df <- tibble::tibble(
status_from = c( status_from = c(
rep("Displaced", 4), rep('Displaced', 4),
rep("Non displaced", 4), rep('Non displaced', 4),
rep("Returnee", 4), rep('Returnee', 4),
rep("Dnk/Pnts", 4) rep('Dnk/Pnts', 4)
), ),
status_to = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts", "Displaced", "Non displaced", "Returnee", "Dnk/Pnts"), status_to = c('Displaced', 'Non displaced', 'Returnee', 'Dnk/Pnts', 'Displaced', 'Non displaced', 'Returnee', 'Dnk/Pnts', 'Displaced', 'Non displaced', 'Returnee', 'Dnk/Pnts', 'Displaced', 'Non displaced', 'Returnee', 'Dnk/Pnts'),
percentage = c(20, 8, 18, 1, 12, 21, 0, 2, 0, 3, 12, 1, 0, 0, 1, 1) percentage = c(20, 8, 18, 1, 12, 21, 0, 2, 0, 3, 12, 1, 0, 0, 1, 1)
) )