add caption example
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68
README.Rmd
68
README.Rmd
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@ -32,7 +32,7 @@ You can install the last version of visualizeR from [GitHub](https://github.com/
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```{r, eval = FALSE}
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# install.packages("devtools")
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devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)
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devtools::install_github('gnoblet/visualizeR', build_vignettes = TRUE)
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```
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## Roadmap
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@ -52,7 +52,7 @@ library(visualizeR)
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color(unname = F)[1:10]
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# Extract a color palette as hexadecimal codes and reversed
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palette(palette = "cat_5_main", reversed = TRUE, color_ramp_palette = FALSE)
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palette(palette = 'cat_5_main', reversed = TRUE, color_ramp_palette = FALSE)
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# Get all color palettes names
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palette(show_palettes = TRUE)
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@ -62,7 +62,7 @@ palette(show_palettes = TRUE)
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### Example 1: Bar chart
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```{r example-bar-chart, out.width = "65%", eval = TRUE}
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```{r example-bar-chart, out.width = '65%', eval = TRUE}
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library(palmerpenguins)
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library(dplyr)
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@ -83,40 +83,40 @@ df_island <- penguins |>
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ungroup()
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# Simple bar chart by group with some alpha transparency
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bar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
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bar(df, 'island', 'mean_bl', 'species', x_title = 'Mean of bill length', title = 'Mean of bill length by island and species')
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# Flipped / Horizontal
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hbar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
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hbar(df, 'island', 'mean_bl', 'species', x_title = 'Mean of bill length', title = 'Mean of bill length by island and species')
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# Facetted
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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)
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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)
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# Flipped, with text, smaller width
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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)
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# Flipped, with text, smaller width, and caption
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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.")
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```
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### Example 2: Scatterplot
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```{r example-point-chart, out.width = "65%", eval = TRUE}
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```{r example-point-chart, out.width = '65%', eval = TRUE}
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# Simple scatterplot
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point(penguins, "bill_length_mm", "flipper_length_mm")
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point(penguins, 'bill_length_mm', 'flipper_length_mm')
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# Scatterplot with grouping colors, greater dot size, some transparency
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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)
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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)
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# Facetted scatterplot by island
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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)
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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)
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```
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### Example 3: Dumbbell plot
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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.
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```{r example-dumbbell-plot, out.width = "65%", eval = TRUE}
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```{r example-dumbbell-plot, out.width = '65%', eval = TRUE}
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# Prepare long data
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df <- tibble::tibble(
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admin1 = rep(letters[1:8], 2),
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setting = c(rep(c("Rural", "Urban"), 4), rep(c("Urban", "Rural"), 4)),
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setting = c(rep(c('Rural', 'Urban'), 4), rep(c('Urban', 'Rural'), 4)),
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stat = rnorm(16, mean = 50, sd = 18)
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) |>
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dplyr::mutate(stat = round(stat, 0))
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@ -126,21 +126,21 @@ df <- tibble::tibble(
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# dumbbell(
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# df,
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# "stat",
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# "setting",
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# "admin1",
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# title = "% of HHs that reported open defecation as sanitation facility",
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# group_y_title = "Admin 1",
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# group_x_title = "Setting"
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# 'stat',
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# 'setting',
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# 'admin1',
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# title = '% of HHs that reported open defecation as sanitation facility',
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# group_y_title = 'Admin 1',
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# group_x_title = 'Setting'
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# )
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```
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### Example 4: donut chart
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```{r example-donut-plot, out.width = "65%", warning = FALSE}
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```{r example-donut-plot, out.width = '65%', warning = FALSE}
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# Some summarized data: % of HHs by displacement status
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df <- tibble::tibble(
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status = c("Displaced", "Non displaced", "Returnee", "Don't know/Prefer not to say"),
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status = c('Displaced', 'Non displaced', 'Returnee', 'Don\'t know/Prefer not to say'),
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percentage = c(18, 65, 12, 3)
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)
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@ -149,33 +149,33 @@ df <- tibble::tibble(
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# status,
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# percentage,
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# hole_size = 3,
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# add_text_suffix = "%",
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# add_text_color = color("dark_grey"),
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# add_text_suffix = '%',
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# add_text_color = color('dark_grey'),
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# add_text_treshold_display = 5,
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# x_title = "Displacement status",
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# title = "% of HHs by displacement status"
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# x_title = 'Displacement status',
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# title = '% of HHs by displacement status'
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# )
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```
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### Example 5: Waffle chart
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```{r example-waffle-plot, out.width = "65%", warning = FALSE}
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```{r example-waffle-plot, out.width = '65%', warning = FALSE}
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#
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# waffle(df, status, percentage, x_title = "A caption", title = "A title", subtitle = "A subtitle")
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# waffle(df, status, percentage, x_title = 'A caption', title = 'A title', subtitle = 'A subtitle')
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```
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### Example 6: Alluvial chart
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```{r example-alluvial-plot, out.width = "65%", warning = FALSE}
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```{r example-alluvial-plot, out.width = '65%', warning = FALSE}
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# Some summarized data: % of HHs by self-reported status of displacement in 2021 and in 2022
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df <- tibble::tibble(
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status_from = c(
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rep("Displaced", 4),
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rep("Non displaced", 4),
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rep("Returnee", 4),
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rep("Dnk/Pnts", 4)
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rep('Displaced', 4),
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rep('Non displaced', 4),
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rep('Returnee', 4),
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rep('Dnk/Pnts', 4)
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),
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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"),
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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'),
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percentage = c(20, 8, 18, 1, 12, 21, 0, 2, 0, 3, 12, 1, 0, 0, 1, 1)
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)
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