bckp

.gitignore

@@ -1,6 +1,7 @@
-.Rproj.user
+.Rproj.user
-.Rhistory
+.Rhistory
-.Rdata
+.Rdata
-.httr-oauth
+.httr-oauth
-.DS_Store
+.DS_Store
 R/test.R
+inst/doc

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: visualizeR
 Type: Package
 Title: What a color! What a viz!
-Version: 0.8.9000
+Version: 1.0
 Authors@R: c(
         person(
             'Noblet', 'Guillaume',
@@ -32,11 +32,13 @@ Imports:
     viridisLite,
     waffle,
     stringr,
-    checkmate,
+    checkmate
-    data.table
 Suggests: 
     knitr,
+    rmarkdown,
     roxygen2,
-    sf,
+    rio,
-    tmap
+    testthat (>= 3.0.0),
+    vdiffr
 VignetteBuilder: knitr
+Config/testthat/edition: 3

R/bar.R

@@ -3,11 +3,13 @@
 #' @inheritParams bar
 #' 
 #' @export
-hbar <- function(...) bar(flip = TRUE, theme_fun = theme_bar(flip = TRUE, add_text = FALSE), ...)
+hbar <- function(..., flip = TRUE, add_text = FALSE, theme_fun = theme_bar(flip = flip, add_text = add_text)) {
+  bar(flip = flip, add_text = add_text, theme_fun = theme_fun, ...)
+}
 
 #' Simple bar chart
 #' 
-#' [bar()] is a simple bar chart with some customization allowed, in particular the `theme_fun` argument for theming. [hbar()] uses [bar()] with sane defaults for a horizontal bar chart.
+#' `bar()` is a simple bar chart with some customization allowed, in particular the `theme_fun` argument for theming. `hbar()` uses `bar()` with sane defaults for a horizontal bar chart.
 #'
 #' @param df A data frame.
 #' @param x A quoted numeric column.
@@ -18,7 +20,10 @@ hbar <- function(...) bar(flip = TRUE, theme_fun = theme_bar(flip = TRUE, add_te
 #' @param x_rm_na Remove NAs in x?
 #' @param y_rm_na Remove NAs in y?
 #' @param group_rm_na Remove NAs in group?
+#' @param facet_rm_na Remove NAs in facet?
+#' @param y_expand Multiplier to expand the y axis.
 #' @param add_color Add a color to bars (if no grouping).
+#' @param add_color_guide Should a legend be added?
 #' @param flip TRUE or FALSE (default). Default to TRUE or horizontal bar plot.
 #' @param wrap Should x-labels be wrapped? Number of characters.
 #' @param position Should the chart be stacked? Default to "dodge". Can take "dodge" and "stack".
@@ -36,11 +41,13 @@ hbar <- function(...) bar(flip = TRUE, theme_fun = theme_bar(flip = TRUE, add_te
 #' @param add_text_font_face Text font_face.
 #' @param add_text_threshold_display Minimum value to add the text label.
 #' @param add_text_suffix If percent is FALSE, should we add a suffix to the text label?
-#' @param add_text_expand_limit Default to adding 10% on top of the bar.
+#' @param add_text_expand_limit Default to adding 10\% on top of the bar.
 #' @param add_text_round Round the text label.
 #' @param theme_fun Whatever theme function. For no custom theme, use theme_fun = NULL.
 #'
-#' @inheritParams reorder
+#' @inheritParams reorder_by
+#' 
+#' @importFrom rlang `:=`
 #'
 #' @export
 bar <- function(
@@ -54,7 +61,9 @@ bar <- function(
   y_rm_na = TRUE,
   group_rm_na = TRUE,
   facet_rm_na = TRUE,
+  y_expand = 0.1,
   add_color = color("cat_5_main_1"),
+  add_color_guide = TRUE,
   flip = FALSE,
   wrap = NULL,
   position = "dodge",
@@ -65,24 +74,24 @@ bar <- function(
   title = NULL,
   subtitle = NULL,
   caption = NULL,
-  width = 0.7,
+  width = 0.8,
   add_text = FALSE,
-  add_text_size = 4,
+  add_text_size = 4.5,
   add_text_color = color("dark_grey"),
-  add_text_font_face = "plain",
+  add_text_font_face = "bold",
   add_text_threshold_display = 0.05,
   add_text_suffix = "%",
   add_text_expand_limit = 1.2,
   add_text_round = 1,
   theme_fun = theme_bar(
-    flip = FALSE,
+    flip = flip,
-    add_text = FALSE,
+    add_text = add_text,
-    axis_text_x_angle = 45,
+    axis_text_x_angle = 0,
-    axis_text_x_vjust = 1,
+    axis_text_x_vjust = 0.5,
-    axis_text_x_hjust = 1
+    axis_text_x_hjust = 0.5
   ),
-  scale_fill_fun = scale_fill_impact_discrete,
+  scale_fill_fun = scale_fill_visualizer_discrete(),
-  scale_color_fun = scale_color_impact_discrete
+  scale_color_fun = scale_color_visualizer_discrete()
 ){
 
   
@@ -105,10 +114,26 @@ if (group != "") checkmate::assert_choice(group, colnames(df))
 checkmate::assert_logical(x_rm_na, len = 1)
 checkmate::assert_logical(y_rm_na, len = 1)
 checkmate::assert_logical(group_rm_na, len = 1)
+checkmate::assert_logical(facet_rm_na, len = 1)
   
 # flip is a logical scalar
 checkmate::assert_logical(flip, len = 1)
   
+# wrap is a numeric scalar or NULL
+if (!is.null(wrap)) checkmate::assert_numeric(wrap, len = 1, null.ok = TRUE)
+
+# alpha is a numeric scalar between 0 and 1
+checkmate::assert_numeric(alpha, lower = 0, upper = 1, len = 1)
+  
+# add_text is a logical scalar
+checkmate::assert_logical(add_text, len = 1)
+  
+# add_text_size is a numeric scalar
+checkmate::assert_numeric(add_text_size, len = 1)
+   
+# add_text_font_face is a character scalar in bold plain or italic
+checkmate::assert_choice(add_text_font_face, c("bold", "plain", "italic"))
+  
 # add_text_threshold_display is a numeric scalar
 checkmate::assert_numeric(add_text_threshold_display, len = 1)
   
@@ -121,8 +146,7 @@ checkmate::assert_numeric(add_text_expand_limit, len = 1)
 # add_text_round is a numeric scalar
 checkmate::assert_numeric(add_text_round, len = 1)
   
-  
+# x and y are numeric or character
-# Check if numeric and character
 if (class(df[[y]]) %notin% c("integer", "numeric")) rlang::abort(paste0(y, " must be numeric."))
 if (!any(class(df[[x]]) %in% c("character", "factor"))) rlang::abort(paste0(x, " must be character or factor"))
 
@@ -131,22 +155,36 @@ if (position %notin% c("stack", "dodge")) rlang::abort("Position should be eithe
 
 #----- Data wrangling
   
-# want to use df as a data.table
+# facets over group
-if (!checkmate::test_data_table(df)) {
+if (group != "" && facet != "" && group == facet) {
-  rlang::warn("Converting df to data.table.")
+  rlang::warn("'group' and 'facet' are the same identical.")
-  data.table::setDT(df)
 }
+
+# remove NAs using base R
+if (x_rm_na) df <- df[!(is.na(df[[x]])),]
+if (y_rm_na) df <- df[!(is.na(df[[y]])),]
+if (group != "" && group_rm_na) df <- df[!(is.na(df[[group]])),]
+if (facet != "" && facet_rm_na) df <- df[!(is.na(df[[facet]])),]
+
   
-# Remove NAs using data.table
+# reorder
-if (x_rm_na) df[, (x) := na.omit(get(x))]
+dir_order <- if(flip && order %in% c("x", "grouped_x")) {
-if (y_rm_na) df[, (y) := na.omit(get(y))]
+  -1 
-if (group != "" && group_rm_na) df[, (group) := na.omit(get(group))]
+} else if (!flip && order %in% c("x", "grouped_x")) {
+  1
+} else if (flip) {
+  1
+} else {
+  -1
+}
+group_order <- if (group != "" || (group == "" && facet == "")) {
+  group 
+} else if (group == "" && facet != "") {
+  facet
+}
+df <- reorder_by(df = df, x = x, y = y, group = group_order, order = order, dir_order = dir_order)
   
-# Reorder
+# prepare aes
-dir_order = ifelse(flip, 1, -1)
-df <- reorder(df, x, y, group, order, dir_order)
-  
-# Prepare aes
 if(group != "") {
 
   g <- ggplot2::ggplot(
@@ -170,7 +208,7 @@ if(group != "") {
   )
 }
 
-# Add title, subtitle, caption, x_title, y_title
+# add title, subtitle, caption, x_title, y_title
 g <- g + ggplot2::labs(
   title = title,
   subtitle = subtitle,
@@ -181,14 +219,19 @@ g <- g + ggplot2::labs(
   fill = group_title
 )
 
-# Width
+# width
 width <- width
 dodge_width <- width
 
-#Facets
+# facets
 if (facet != "") {
-  g <- g + ggforce::facet_row(facet, scales = "free_x", space = "free")
+  if (flip) {
+    g <- g + ggplot2::facet_grid(rows = ggplot2::vars(!!rlang::sym(facet)), scales = "free", space = "free_y")
+  } else {
+    g <- g + ggplot2::facet_grid(cols = ggplot2::vars(!!rlang::sym(facet)), scales = "free", space = "free_x")
+  }
 }
+
   
 # Guides for legend
 # g <- g + ggplot2::guides(
@@ -206,7 +249,7 @@ if (facet != "") {
 #     direction = "horizontal")
 # )
 
-# Should the graph use position_fill?
+# should the graph use position_fill?
 if(group != "") {
 
   if (position == "stack"){
@@ -260,35 +303,53 @@ if(group != "") {
   }
 }
 
-# Wrap labels on the x scale?
+# wrap labels on the x scale?
 if (!is.null(wrap)) {
   g <- g + ggplot2::scale_x_discrete(labels = scales::label_wrap(wrap))
 }
 
 
-# Because a text legend should always be horizontal, especially for an horizontal bar graph
+# because a text legend should always be horizontal, especially for an horizontal bar graph
 if (flip) g <- g + ggplot2::coord_flip()
 # Add text to bars
 if (flip) hjust_flip <- -0.5 else hjust_flip <- 0.5
 if (flip) vjust_flip <- 0.5 else vjust_flip <- -0.5
 
+# Function for interaction
+interaction_f <- function(group, facet, data) {
+  if (group == "" && facet == "") {
+    return(NULL)
+  } else if (group != "" && facet != "") {
+    return(interaction(data[[group]], data[[facet]]))
+  } else if (group != "") {
+    return(data[[group]])
+  } else if (facet != "") {
+    return(data[[facet]])
+  } else {
+    return(NULL)
+  }
+}
 
-# Add text labels
+
+# add text labels
 if (add_text & position == "dodge") {
 
   df <- dplyr::mutate(df, "y_threshold" := ifelse(!!rlang::sym(y) >= add_text_threshold_display, !!rlang::sym(y), NA ))
 
-  # Expand limits
+  # expand limits
   g <- g + ggplot2::geom_blank(
     data = df,
-    ggplot2::aes(x = !!rlang::sym(x), y = !!rlang::sym(y) * add_text_expand_limit, group = !!rlang::sym(group))
+    ggplot2::aes(
+      x = !!rlang::sym(x), 
+      y = !!rlang::sym(y) * add_text_expand_limit, 
+      group = interaction_f(group, facet, df)
+    )
   )
-
   g <- g + ggplot2::geom_text(
     data = df,
     ggplot2::aes(
       label = ifelse(is.na(!!rlang::sym("y_threshold")), NA, paste0(round(!!rlang::sym("y_threshold"), add_text_round), add_text_suffix)),
-      group = !!rlang::sym(group)),
+      group = interaction_f(group, facet, df)),
     hjust = hjust_flip,
     vjust = vjust_flip,
     color = add_text_color,
@@ -304,12 +365,16 @@ if (add_text & position == "dodge") {
   g <- g + ggplot2::geom_text(
     data = df,
     ggplot2::aes(
-      label = ifelse(is.na(!!rlang::sym("y_threshold")), NA, paste0(round(!!rlang::sym("y_threshold"), add_text_round), add_text_suffix)),
+      label = ifelse(is.na(!!rlang::sym("y_threshold")), NA, 
-      group = !!rlang::sym(group)),
+                     paste0(round(!!rlang::sym("y_threshold"), add_text_round), add_text_suffix)),
+      group = interaction_f(group, facet, df)
+    ),
+    hjust = hjust_flip,
+    vjust = vjust_flip,
     color = add_text_color,
     fontface = add_text_font_face,
     size = add_text_size,
-    position = ggplot2::position_stack(vjust = 0.5)
+    position = ggplot2::position_dodge2(width = dodge_width)
   )
 
   }
@@ -318,7 +383,7 @@ if (add_text & position == "dodge") {
   g <- g +
     ggplot2::scale_y_continuous(
       # start at 0
-      expand = c(0, 0),
+      expand = ggplot2::expansion(mult = c(0, y_expand)),
       # remove trailing 0 and choose accuracy of y labels
       labels =  scales::label_number(
         accuracy = 0.1,
@@ -327,9 +392,16 @@ if (add_text & position == "dodge") {
         decimal.mark = "."),
     ) 
 
+  # Remove guides for legend if !add_color_guide
+  if (!add_color_guide) g <- g + ggplot2::guides(fill = "none", color = "none")
+
   # Add theme fun
   if (!is.null(theme_fun)) g <- g + theme_fun
 
-return(g)
+  # Add scale fun
+  if (!is.null(scale_fill_fun)) g <- g + scale_fill_fun
+  
+  if (!is.null(scale_color_fun)) g <- g + scale_color_fun
+
+  return(g)
 }
-  

R/color.R

@@ -25,8 +25,11 @@ color <- function(..., unname = TRUE) {
   # Defined colors
   colors <- c(
     white = "#FFFFFF"
+    , lighter_grey = "#F5F5F5"
     , light_grey = "#E3E3E3"
     , dark_grey = "#464647"
+    , light_blue_grey = "#B3C6D1"
+    , grey = "#71716F"
     , black = "#000000"
     , cat_2_yellow_1 = "#ffc20a"
     , cat_2_yellow_2 = "#0c7bdc"
@@ -46,7 +49,7 @@ color <- function(..., unname = TRUE) {
     , seq_5_main_3 = "#6b8bad"
     , seq_5_main_4 = "#9cb1c9"
     , seq_5_main_5 = "#ced8e4"
-    , cat_5_ibm_1 = "#648fff" 
+    , cat_5_ibm_1 = "#648fff"
     , cat_5_ibm_2 = "#785ef0"
     , cat_5_ibm_3 = "#dc267f"
     , cat_5_ibm_4 = "#fe6100"
@@ -96,7 +99,7 @@ color <- function(..., unname = TRUE) {
 
   if (is.null(cols)) {
     cols_to_return <- colors
-  } else { 
+  } else {
     cols_to_return <- colors[cols]
   }
 

R/dumbbell.R

@@ -0,0 +1,189 @@
+#' Make dumbbell chart.
+#'
+#' @param df A data frame.
+#' @param col A numeric column.
+#' @param group_x The grouping column on the x-axis; only two groups.
+#' @param group_y The grouping column on the y-axis.
+#' @param point_size Point size.
+#' @param point_alpha Point alpha.
+#' @param segment_size Segment size.
+#' @param segment_color Segment color.
+#' @param group_x_title X-group and legend title.
+#' @param group_y_title Y-axis and group title.
+#' @param x_title X-axis title.
+#' @param title Title.
+#' @param subtitle Subtitle.
+#' @param caption Caption.
+#' @param line_to_y_axis TRUE or FALSE; add a line connected points and Y-axis.
+#' @param line_to_y_axis_type Line to Y-axis type.
+#' @param line_to_y_axis_width Line to Y-axis width.
+#' @param line_to_y_axis_color Line to Y-axis color.
+#' @param add_text TRUE or FALSE; add text at the points.
+#' @param add_text_vjust Vertical adjustment.
+#' @param add_text_size Text size.
+#' @param add_text_color Text color.
+#' @param theme_fun A ggplot2 theme, default to `theme_dumbbell()`
+#' @param scale_fill_fun A ggplot2 scale_fill function, default to `scale_fill_visualizer_discrete()`
+#' @param scale_color_fun A ggplot2 scale_color function, default to `scale_color_visualizer_discrete()`
+#'
+#' @return A dumbbell chart.
+#' @export
+#'
+dumbbell <- function(df,
+                     col,
+                     group_x,
+                     group_y,
+                     point_size = 5,
+                     point_alpha = 1,
+                     segment_size = 2.5,
+                     segment_color = color("light_blue_grey"),
+                     group_x_title = NULL,
+                     group_y_title = NULL,
+                     x_title = NULL,
+                     title = NULL,
+                     subtitle = NULL,
+                     caption = NULL,
+                     line_to_y_axis = FALSE,
+                     line_to_y_axis_type = 3,
+                     line_to_y_axis_width = 0.5,
+                     line_to_y_axis_color = color("dark_grey"),
+                     add_text = FALSE,
+                     add_text_vjust = 2,
+                     add_text_size = 3.5,
+                     add_text_color = color("dark_grey"),
+                     theme_fun = theme_dumbbell(),
+                     scale_fill_fun = scale_fill_visualizer_discrete(),
+                     scale_color_fun = scale_color_visualizer_discrete()){
+
+  #------ Checks
+
+  # df is a data frame
+  checkmate::assert_data_frame(df)
+
+  # col, group_x, group_y are character
+  checkmate::assert_character(col, len = 1)
+  checkmate::assert_character(group_x, len = 1)
+  checkmate::assert_character(group_y, len = 1)
+
+  # col, group_x, group_y are columns in df
+  checkmate::assert_choice(col, colnames(df))
+  checkmate::assert_choice(group_x, colnames(df))
+  checkmate::assert_choice(group_y, colnames(df))
+
+  # Check numeric/logical values
+  checkmate::assert_numeric(point_size, len = 1)
+  checkmate::assert_numeric(point_alpha, lower = 0, upper = 1, len = 1)
+  checkmate::assert_numeric(segment_size, len = 1)
+  checkmate::assert_logical(line_to_y_axis, len = 1)
+  checkmate::assert_numeric(line_to_y_axis_type, len = 1)
+  checkmate::assert_numeric(line_to_y_axis_width, len = 1)
+  checkmate::assert_logical(add_text, len = 1)
+  checkmate::assert_numeric(add_text_vjust, len = 1)
+  checkmate::assert_numeric(add_text_size, len = 1)
+
+  # Get group keys
+  group_x_keys <- df |>
+    dplyr::group_by(!!rlang::sym(group_x)) |>
+    dplyr::group_keys() |>
+    dplyr::pull()
+
+  # Check if only two groups
+  if (length(group_x_keys) > 2) rlang::abort("Cannot draw a dumbbell plot for `group_x` with more than 2 groups")
+
+  # Pivot long data
+  df_pivot <- df |>
+    tidyr::pivot_wider(
+      id_cols = c(!!rlang::sym(group_y)),
+      values_from = !!rlang::sym(col),
+      names_from = !!rlang::sym(group_x)
+    )
+
+  df_pivot <- df_pivot |>
+    dplyr::rowwise() |>
+    dplyr::mutate(
+      min = min(!!rlang::sym(group_x_keys[[1]]), !!rlang::sym(group_x_keys[[2]]), na.rm = T),
+      max = max(!!rlang::sym(group_x_keys[[1]]), !!rlang::sym(group_x_keys[[2]]), na.rm = T)) |>
+    dplyr::ungroup() |>
+    dplyr::mutate(diff = max - min)
+
+  g <- ggplot2::ggplot(df_pivot)
+
+  # Add line
+  if(line_to_y_axis) {
+
+    xend <- min(dplyr::pull(df, !!rlang::sym(col)))
+
+    g <- g +
+      ggplot2::geom_segment(
+        ggplot2::aes(
+          x = min,
+          y = !!rlang::sym(group_y),
+          yend = !!rlang::sym(group_y)),
+        xend = xend,
+        linetype = line_to_y_axis_type,
+        linewidth = line_to_y_axis_width,
+        color = line_to_y_axis_color)
+  }
+
+  # Add segment
+  g <-  g +
+    ggplot2::geom_segment(
+      ggplot2::aes(
+        x = !!rlang::sym(group_x_keys[[1]]),
+        y = !!rlang::sym(group_y),
+        xend = !!rlang::sym(group_x_keys[[2]]),
+        yend = !!rlang::sym(group_y)),
+      linewidth = segment_size,
+      color = segment_color
+    )
+
+  # Add points
+  g <- g +
+    ggplot2::geom_point(
+      data = df,
+      ggplot2::aes(
+        x = !!rlang::sym(col),
+        y = !!rlang::sym(group_y),
+        color = !!rlang::sym(group_x),
+        fill = !!rlang::sym(group_x)
+      ),
+      size = point_size,
+      alpha = point_alpha
+    )
+
+  # Add title, subtitle, caption, x_title, y_title
+  g <- g + ggplot2::labs(
+    title = title,
+    subtitle = subtitle,
+    caption = caption,
+    x = x_title,
+    y = group_y_title,
+    color = group_x_title,
+    fill = group_x_title
+  )
+
+  # Add stat labels to points
+  if(add_text) g <- g +
+    ggrepel::geom_text_repel(
+      data = df,
+      ggplot2::aes(
+        x = !!rlang::sym(col),
+        y = !!rlang::sym(group_y),
+        label = !!rlang::sym(col)
+      ),
+      vjust = add_text_vjust,
+      size = add_text_size,
+      color = add_text_color
+    )
+
+  # Add theme
+  g <- g + theme_fun
+
+  # Add scale fun
+  if (!is.null(scale_fill_fun)) g <- g + scale_fill_fun
+
+  if (!is.null(scale_color_fun)) g <- g + scale_color_fun
+
+  return(g)
+
+}

R/point.R

@@ -1,11 +1,18 @@
-#' @title Simple point chart
+#' @title Simple scatterplot
 #'
 #' @param df A data frame.
-#' @param x A numeric column.
+#' @param x A quoted numeric column.
-#' @param y Another numeric column.
+#' @param y A quoted numeric column.
-#' @param group Some grouping categorical column, e.g. administrative areas or population groups.
+#' @param group Some quoted grouping categorical column, e.g. administrative areas or population groups.
-#' @param add_color Add a color to bars (if no grouping).
+#' @param facet Some quoted grouping categorical column.
-#' @param flip TRUE or FALSE. Default to TRUE or horizontal bar plot.
+#' @param facet_scales Character. Either "free" (default) or "fixed" for facet scales.
+#' @param x_rm_na Remove NAs in x?
+#' @param y_rm_na Remove NAs in y?
+#' @param group_rm_na Remove NAs in group?
+#' @param facet_rm_na Remove NAs in facet?
+#' @param add_color Add a color to points (if no grouping).
+#' @param add_color_guide Should a legend be added?
+#' @param flip TRUE or FALSE.
 #' @param alpha Fill transparency.
 #' @param size Point size.
 #' @param x_title The x scale title. Default to NULL.
@@ -14,77 +21,167 @@
 #' @param title Plot title. Default to NULL.
 #' @param subtitle Plot subtitle. Default to NULL.
 #' @param caption Plot caption. Default to NULL.
-#' @param theme_fun Whatever theme. Default to theme_reach(). NULL if no theming needed.
+#' @param theme_fun Whatever theme. Default to theme_point(). NULL if no theming needed.
-#' @param scale_impact Use the package custom scales for fill and color.
 #'
-#' @inheritParams scale_color_impact_discrete
+#' @inheritParams scale_color_visualizer_discrete
 #'
 #' @export
-point <- function(df, x, y, group = "", add_color = color("branding_reach_red"), flip = TRUE, alpha = 1, size = 2, x_title = NULL, y_title = NULL, group_title = NULL, title = NULL, subtitle = NULL, caption = NULL, theme_fun = theme_reach(grid_major_y = TRUE), palette = "cat_5_ibm", scale_impact = TRUE, direction = 1, reverse_guide = TRUE) {
+point <- function(
-  # # Check if numeric and character
+  df,
-  if (!any(c("numeric", "integer") %in% class(df[[x]]))) rlang::abort(paste0(x, " must be numeric."))
+  x,
-  if (!any(c("numeric", "integer") %in% class(df[[y]]))) rlang::abort(paste0(x, " must be numeric."))
+  y,
+  group = "",
+  facet = "",
+  facet_scales = "free",
+  x_rm_na = TRUE,
+  y_rm_na = TRUE,
+  group_rm_na = TRUE,
+  facet_rm_na = TRUE,
+  add_color = color("cat_5_main_1"),
+  add_color_guide = TRUE,
+  flip = TRUE,
+  alpha = 1,
+  size = 2,
+  x_title = NULL,
+  y_title = NULL,
+  group_title = NULL,
+  title = NULL,
+  subtitle = NULL,
+  caption = NULL,
+  theme_fun = theme_point(),
+  scale_fill_fun = scale_fill_visualizer_discrete(),
+  scale_color_fun = scale_color_visualizer_discrete()
+) {
+  
+  #------ Checks
+  
+  # df is a data frame
+  checkmate::assert_data_frame(df)
+  
+  # x and y and group are character
+  checkmate::assert_character(x, len = 1)
+  checkmate::assert_character(y, len = 1)
+  checkmate::assert_character(group, len = 1)
+  
+  # x and y are columns in df
+  checkmate::assert_choice(x, colnames(df))
+  checkmate::assert_choice(y, colnames(df))
+  if (group != "") checkmate::assert_choice(group, colnames(df))
+  
+  # x_rm_na, y_rm_na and group_rm_na are logical scalar
+  checkmate::assert_logical(x_rm_na, len = 1)
+  checkmate::assert_logical(y_rm_na, len = 1)
+  checkmate::assert_logical(group_rm_na, len = 1)
+  checkmate::assert_logical(facet_rm_na, len = 1)
 
-  # Mapping
+  # facet_scales is a character scalar in c("free", "fixed")
+  checkmate::assert_choice(facet_scales, c("free", "fixed"))
+  
+  # flip is a logical scalar
+  checkmate::assert_logical(flip, len = 1)
+  
+  # alpha is a numeric scalar between 0 and 1
+  checkmate::assert_numeric(alpha, lower = 0, upper = 1, len = 1)
+  
+  # size is a numeric scalar
+  checkmate::assert_numeric(size, len = 1)
+  
+  # x and y are numeric
+  if (!any(c("numeric", "integer") %in% class(df[[x]]))) rlang::abort(paste0(x, " must be numeric."))
+  if (!any(c("numeric", "integer") %in% class(df[[y]]))) rlang::abort(paste0(y, " must be numeric."))
+  
+  
+  #----- Data wrangling
+  
+  # facets over group
+  if (group != "" && facet != "" && group == facet) {
+      rlang::warn("'group' and 'facet' are the same identical.")
+  }
+  
+  # remove NAs using base R
+  if (x_rm_na) df <- df[!(is.na(df[[x]])),]
+  if (y_rm_na) df <- df[!(is.na(df[[y]])),]
+  if (group != "" && group_rm_na) df <- df[!(is.na(df[[group]])),]
+  if (facet != "" && facet_rm_na) df <- df[!(is.na(df[[facet]])),]
+
+  # prepare aes
   if (group != "") {
-    g <- ggplot2::ggplot(
+      g <- ggplot2::ggplot(
-      df,
+          df,
-      mapping = ggplot2::aes(
+          mapping = ggplot2::aes(
-        x = !!rlang::sym(x),
+              x = !!rlang::sym(x),
-        y = !!rlang::sym(y),
+              y = !!rlang::sym(y),
-        fill = !!rlang::sym(group),
+              fill = !!rlang::sym(group),
-        color = !!rlang::sym(group)
+              color = !!rlang::sym(group)
+          )
       )
+  } else {
+      g <- ggplot2::ggplot(
+          df,
+          mapping = ggplot2::aes(
+              x = !!rlang::sym(x),
+              y = !!rlang::sym(y)
+          )
+      )
+  }
+  
+  # add title, subtitle, caption, x_title, y_title
+  g <- g + ggplot2::labs(
+      title = title,
+      subtitle = subtitle,
+      caption = caption,
+      x = x_title,
+      y = y_title,
+      color = group_title,
+      fill = group_title
+  )
+  
+  # facets
+# facets
+if (facet != "") {
+  if (flip) {
+    g <- g + ggplot2::facet_grid(
+      rows = ggplot2::vars(!!rlang::sym(facet)), 
+      scales = facet_scales, 
+      space = if(facet_scales == "free") "free_y" else "fixed"
     )
   } else {
-    g <- ggplot2::ggplot(
+    g <- g + ggplot2::facet_grid(
-      df,
+      cols = ggplot2::vars(!!rlang::sym(facet)), 
-      mapping = ggplot2::aes(
+      scales = facet_scales, 
-        x = !!rlang::sym(x),
+      space = if(facet_scales == "free") "free_x" else "fixed"
-        y = !!rlang::sym(y)
-      )
     )
   }
-
+}
-
+  
-  # Add title, subtitle, caption, x_title, y_title
-  g <- g + ggplot2::labs(
-    title = title,
-    subtitle = subtitle,
-    caption = caption,
-    x = x_title,
-    y = y_title,
-    color = group_title,
-    fill = group_title
-  )
-
   # Should the graph use position_fill?
   if (group != "") {
-    g <- g + ggplot2::geom_point(
+      g <- g + ggplot2::geom_point(
-      alpha = alpha,
+          alpha = alpha,
-      size = size
+          size = size
-    )
+      )
   } else {
-    g <- g + ggplot2::geom_point(
+      g <- g + ggplot2::geom_point(
-      alpha = alpha,
+          alpha = alpha,
-      size = size,
+          size = size,
-      color = add_color
+          color = add_color
-    )
+      )
   }
-
+  
   if (flip) {
-    g <- g + ggplot2::coord_flip()
+      g <- g + ggplot2::coord_flip()
   }
-
+  
-  # Add theme
+  # Remove guides for legend if !add_color_guide
-  g <- g + theme_fun
+  if (!add_color_guide) g <- g + ggplot2::guides(fill = "none", color = "none")
-
+  
-
   # Add theme
   if (!is.null(theme_fun)) g <- g + theme_fun
-
+  
-  # Add scale
+  # Add scale fun
-  if (scale_impact) g <- g + scale_fill_impact_discrete(palette, direction, reverse_guide) + scale_color_impact_discrete(palette, direction, reverse_guide)
+  if (!is.null(scale_fill_fun)) g <- g + scale_fill_fun
-
+  
+  if (!is.null(scale_color_fun)) g <- g + scale_color_fun
+  
   return(g)
 }

R/reorder_by.R

@@ -1,6 +1,5 @@
-
+#' Reorder a Data Frame
-#' Reorder a Data Frame Factoring Column x
+#' 
-#'
 #' @param df A data frame to be reordered.
 #' @param x A character scalar specifying the column to be reordered.
 #' @param y A character scalar specifying the column to order by if ordering by values.
@@ -22,21 +21,16 @@
 #' @examples
 #' # Example usage
 #' df <- data.frame(col1 = c("b", "a", "c"), col2 = c(10, 25, 3))
-#' reorder(df, "col1", "col2")
+#' reorder_by(df, "col1", "col2")
+#' 
 #' @export
-reorder <- function(df, x, y, group = "", order = "y", dir_order = 1){
+reorder_by <- function(df, x, y, group = "", order = "y", dir_order = 1){
 
   #------ Checks
 
   # df is a data frame
   checkmate::assert_data_frame(df)
 
-  # df is data.table, if not convert
-  if (!checkmate::test_data_table(df)) {
-    rlang::warn("Converting df to data.table.")
-    data.table::setDT(df)
-  }
-
   # x and y are character scalar and in df
   checkmate::assert_character(x, len = 1)
   checkmate::assert_character(y, len = 1)
@@ -53,52 +47,44 @@ reorder <- function(df, x, y, group = "", order = "y", dir_order = 1){
   # dir_order is 1 or -1 (numeric scalar)
   checkmate::assert_subset(dir_order, c(1, -1))
 
-
+ #------ Reorder
-  #------ Reorder
 
   # droplevels first
   if (is.factor(df[[x]])) {
-    df[, (x) := droplevels(get(x))]
+    df[[x]] <- droplevels(df[[x]])
   }
 
   # reording options
   if (order == "y") {
-
+    # Order by values of y
-    data.table::setorderv(df, y, order = dir_order)
+    df <- df[order(df[[y]] * dir_order), ]
-    df[, (x) := forcats::fct_inorder(get(x))]
+    df[[x]] <- forcats::fct_inorder(df[[x]])
-    
-  } else if (order == "grouped" && group == "") {
-
-    rlang::warn("Group is empty. Ordering by y only.")
-    
-    data.table::setorderv(df, y, order = dir_order)
-    df[, (x) := forcats::fct_inorder(get(x))]
-    
   } else if (order == "grouped_y" && group != "") {
-
+    # Order by group first, then by values of y
-    data.table::setorderv(df, c(group, y), order = dir_order)
+    df <- df[order(df[[group]], df[[y]] * dir_order), ]
-    df[, (x) := forcats::fct_inorder(get(x))]
+    df[[x]] <- forcats::fct_inorder(df[[x]])
-    
+  } else if (order == "grouped_y" && group == "") {
+    # Fallback to ordering by y if group is empty
+    rlang::warn("Group is empty. Ordering by y only.")
+    df <- df[order(df[[y]] * dir_order), ]
+    df[[x]] <- forcats::fct_inorder(df[[x]])
   } else if (order == "x") {
-
+    # Order alphabetically by x
-    data.table::setorderv(df, x, order = dir_order)
+    df <- df[order(df[[x]] * dir_order), ]
-    df[, (x) := forcats::fct_inorder(get(x))]
+    df[[x]] <- forcats::fct_inorder(df[[x]])
-    
   } else if (order == "grouped_x" && group != "") {
-
+    # Order by group first, then alphabetically by x
-    data.table::setorderv(df, c(group, x), order = dir_order)
+    df <- df[order(df[[group]], df[[x]] * dir_order), ]
-    df[, (x) := forcats::fct_inorder(get(x))]
+    df[[x]] <- forcats::fct_inorder(df[[x]])
-    
   } else if (order == "grouped_x" && group == "") {
-
+    # Fallback to ordering by x if group is empty
     rlang::warn("Group is empty. Ordering by x only.")
-    
+    df <- df[order(df[[x]] * dir_order), ]
-    data.table::setorderv(df, x, order = dir_order)
+    df[[x]] <- forcats::fct_inorder(df[[x]])
-    df[, (x) := forcats::fct_inorder(get(x))]
-    
   }
 
-  return(df)
+  # Reset row names
+  rownames(df) <- NULL
 
+  return(df)
 }
-  

R/scale.R

@@ -1,35 +1,3 @@
-
-#' One scale for all
-#' 
-#' This function is based on [palette()]. If palette is NULL, the used palette will be magma from gpplot2's viridis scale constructors.
-#'
-#' @inheritParams palette_gen
-#'
-#' @param reverse_guide Boolean indicating whether the guide should be reversed.
-#' @param ... Additional arguments passed to [ggplot2::discrete_scale()] if discrete or [ggplot2::scale_fill_gradient()] if continuous.
-#'
-#' @export
-scale_visualizer_discrete <- function(palette = "cat_5_main", direction = 1, reverse_guide = TRUE, title_position = NULL, ...) {
-
-  s <- scale_color_visualizer_discrete(palette, direction, reverse_guide, ...) +  
-    scale_fill_visualizer_discrete(palette, direction, reverse_guide, ...)
-
-  return(s)
-
-}
-
-#' @rdname scale_visualizer_dicscrete
-#' 
-#' @export
-scale_visualizer_continuous <- function(palette = "seq_5_main", direction = 1, reverse_guide = TRUE, title_position = NULL, ...) {
-
-  s <- scale_color_visualizer_continuous(palette, direction, reverse_guide, ...) +  
-    scale_fill_visualizer_continuous(palette, direction, reverse_guide, ...)
-
-  return(s)
-
-}
-
 #' Scale constructors for fill and colors
 #'
 #' This function is based on [palette()]. If palette is NULL, the used palette will be magma from gpplot2's viridis scale constructors.

R/theme_bar.R

@@ -1,59 +1,86 @@
 #' Custom Theme for Bar Charts
 #'
 #' @return A custom theme object.
-#' 
+#'
+#' @rdname theme_default
+#'
 #' @export
 theme_bar <- function(flip = TRUE, add_text = FALSE, axis_text_x_angle = 0, axis_text_x_vjust = 0.5, axis_text_x_hjust = 0.5) {
 
   # If add_text is TRUE, flip is FALSE
   if (!flip && !add_text){
+    par_axis_text_font_face <- "plain"
+    par_axis_x <- TRUE
+    par_axis_y <- TRUE
     par_axis_line_y <- FALSE
-    par_axis_ticks_y <- FALSE
+    par_axis_ticks_y <- TRUE
+    par_axis_text_y <- TRUE
     par_axis_line_x <- TRUE
     par_axis_ticks_x <- TRUE
+    par_axis_text_x <- TRUE
     par_grid_major_y <- TRUE
     par_grid_major_x <- FALSE
     par_grid_minor_y <- TRUE
     par_grid_minor_x <- FALSE
   } else if (flip && !add_text){
+    par_axis_text_font_face <- "plain"
+    par_axis_x <- TRUE
+    par_axis_y <- TRUE
     par_axis_line_y <- TRUE
     par_axis_ticks_y <- TRUE
+    par_axis_text_y <- TRUE
     par_axis_line_x <- FALSE
-    par_axis_ticks_x <- FALSE
+    par_axis_ticks_x <- TRUE
+    par_axis_text_x <- TRUE
     par_grid_major_y <- FALSE
     par_grid_major_x <- TRUE
     par_grid_minor_y <- FALSE
     par_grid_minor_x <- TRUE
   } else if (!flip && add_text){
+    par_axis_text_font_face <- "bold"
+    par_axis_x <- TRUE
+    par_axis_y <- TRUE
     par_axis_line_y <- FALSE
     par_axis_ticks_y <- FALSE
-    par_axis_line_x <- TRUE
+    par_axis_text_y <- FALSE
+    par_axis_line_x <- FALSE
     par_axis_ticks_x <- TRUE
+    par_axis_text_x <- TRUE
     par_grid_major_y <- FALSE
     par_grid_major_x <- FALSE
     par_grid_minor_y <- FALSE
     par_grid_minor_x <- FALSE
   } else if (flip && add_text){
-    par_axis_line_y <- TRUE
+    par_axis_text_font_face <- "bold"
+    par_axis_x <- TRUE
+    par_axis_y <- TRUE
+    par_axis_line_y <- FALSE
     par_axis_ticks_y <- TRUE
+    par_axis_text_y <- TRUE
     par_axis_line_x <- FALSE
     par_axis_ticks_x <- FALSE
+    par_axis_text_x <- FALSE
     par_grid_major_y <- FALSE
-    par_grid_major_x <- FALSE 
+    par_grid_major_x <- FALSE
     par_grid_minor_y <- FALSE
     par_grid_minor_x <- FALSE
   }
-  
+
   # Theme
   t <- theme_default(
-    grid_major_y = par_grid_major_y
+    axis_text_font_face = par_axis_text_font_face
-    , axis_line_y = par_axis_line_y
+    , axis_x = par_axis_x
-    , axis_ticks_y = par_axis_ticks_y
+    , axis_y = par_axis_y
-    , axis_ticks_x = par_axis_ticks_x
+    , grid_major_y = par_grid_major_y
-    , axis_line_x = par_axis_line_x
     , grid_major_x = par_grid_major_x
     , grid_minor_y = par_grid_minor_y
     , grid_minor_x = par_grid_minor_x
+    , axis_text_y = par_axis_text_y
+    , axis_line_y = par_axis_line_y
+    , axis_ticks_y = par_axis_ticks_y
+    , axis_text_x = par_axis_text_x
+    , axis_line_x = par_axis_line_x
+    , axis_ticks_x = par_axis_ticks_x
     , axis_text_x_angle = axis_text_x_angle
     , axis_text_x_vjust = axis_text_x_vjust
     , axis_text_x_hjust = axis_text_x_hjust

R/theme_default.R

@@ -86,15 +86,16 @@ theme_default <- function(
   legend_title_size = 13,
   legend_title_color = color("dark_grey"),
   legend_title_font_face = "plain",
+  legend_title_font_family = "Carlito",
   legend_text_size = 13,
   legend_text_color = color("dark_grey"),
   legend_text_font_face = "plain",
-  facet_title_size = 13,
+  legend_text_font_family = "Carlito",
-  facet_title_color = color("dark_grey"),
+  facet_size = 14,
-  facet_title_font_face = "bold",
+  facet_color = color("dark_grey"),
-  facet_title_font_family = "Carlito",
+  facet_font_face = "bold",
-  facet_title_position = "bottom",
+  facet_font_family = "Carlito",
-  facet_background_color = color("light_grey"),
+  facet_bg_color = color("lighter_grey"),
   axis_x = TRUE,
   axis_y = TRUE,
   axis_text_x = TRUE,
@@ -182,20 +183,18 @@ theme_default <- function(
       color = caption_color,
       margin = ggplot2::margin(t = 5)
     ),
-    # legend.title = ggplot2::element_text(
+    legend.title = ggplot2::element_text(
-    #   size = legend_title_size,
+      size = legend_title_size,
-    #   face = legend_title_font_face,
+      face = legend_title_font_face,
-    #   family = font_family,
+      family = legend_title_font_family,
-    #   color = legend_title_color
+      color = legend_title_color
-    #   #, vjust = 0.5
+    ),
-    # ),
+    legend.text = ggplot2::element_text(
-    # legend.text = ggplot2::element_text(
+      size = legend_text_size,
-    #   size = legend_text_size,
+      face = legend_text_font_face,
-    #   face = legend_text_font_face,
+      family = legend_text_font_family,
-    #   family = font_family,
+      color = legend_text_color
-    #   color = legend_text_color
+    ),
-  #   #   #, hjust = 0.5
-  #   # ),
     axis.text.x = ggplot2::element_text(
       angle = axis_text_x_angle,
       vjust = axis_text_x_vjust,
@@ -365,13 +364,13 @@ theme_default <- function(
   # Add facet title text size
   theme <- theme + ggplot2::theme(
     strip.text = ggplot2::element_text(
-      size = facet_title_size,
+      size = facet_size,
-      family = facet_title_font_family,
+      family = facet_font_family,
-      face = facet_title_font_face,
+      face = facet_font_face,
-      color = facet_title_color
+      color = facet_color
     ),
     strip.background = ggplot2::element_rect(
-      fill = facet_background_color,
+      fill = facet_bg_color,
       linewidth = 0
     )
   )

R/theme_dumbbell.R

@@ -0,0 +1,13 @@
+#' @title Dumbbell Theme
+
+#' @description Theme for dumbbell charts based on theme_default.
+#'
+#' @rdname theme_default
+#'
+#' @export
+theme_dumbbell <- function() {
+  theme_default(
+    axis_line_x = TRUE,
+    grid_)
+}
+

R/theme_point.R

@@ -0,0 +1,32 @@
+#' Custom Theme for Point Charts
+#'
+#' @param flip Logical. Whether the plot is flipped (horizonal).
+#' @param axis_text_x_angle Angle for x-axis text.
+#' @param axis_text_x_vjust Vertical justification for x-axis text.
+#' @param axis_text_x_hjust Horizontal justification for x-axis text.
+#'
+#' @rdname theme_default
+#'
+#' @return A custom theme object.
+#'
+#' @export
+theme_point <- function(
+) {
+  t <- theme_default(
+      axis_text_font_face = "plain",
+      axis_x = TRUE,
+      axis_y = TRUE,
+      grid_major_y = TRUE,
+      grid_major_x = TRUE,
+      grid_minor_y = FALSE,
+      grid_minor_x = FALSE,
+      axis_text_x = TRUE,
+      axis_line_x = TRUE,
+      axis_ticks_x = TRUE,
+      axis_text_x_angle = 0,
+      axis_text_x_vjust = 0.5,
+      axis_text_x_hjust = 0
+  )
+
+  return(t)
+}

R/theme_visualizer_bar.R

@@ -1,49 +0,0 @@
-#' Dynamic Theme for ggplot2
-#'
-#' A dynamic theme that adjusts axis text styles based on whether the plot is flipped.
-#'
-#' This function dynamically applies different axis text styles depending on
-#' the coordinate system of the plot. If the plot is flipped (e.g., using
-#' `coord_flip()`), the x-axis and y-axis text styles are adjusted accordingly.
-#'
-#' @return A ggproto object that applies a dynamic theme to a ggplot2 plot.
-#' @examples
-#' library(ggplot2)
-#'
-#' # Example with a regular plot
-#' p <- ggplot(mpg, aes(displ, hwy)) +
-#'   geom_col()
-#'
-#' # Add the dynamic theme
-#' p + theme_visualizer_bar()
-#'
-#' # Add the dynamic theme with a flipped coordinate system
-#' p + theme_visualizer_bar() + coord_flip()
-#'
-#' @export
-theme_visualizer_bar <- function() {
-  out <- theme_grey()
-  class(out) <- c("ThemeVisualizerBar", class(out))
-
-  #structure(list(), class = c("ThemeVisualizerBar", "theme", "gg"))
-  return(out)
-}
-
-
-
-ggplot_add.theme_visualizer_bar <- function(object, p, object_name) {
-   # Check if the plot is flipped
-   is_flipped <- inherits(p$coordinates, "CoordFlip")
-
-   if (!is_flipped) {
-    object <- object +
-      theme_minimal()
-  } else {
-      object <- object +
-      theme(
-        panel.grid.major = ggplot2::element_line(color = "blue")
-      )
-  }
-
-  return(object)
-}

R/visualizeR-package.R

@@ -0,0 +1,6 @@
+#' @keywords internal
+"_PACKAGE"
+
+## usethis namespace: start
+## usethis namespace: end
+NULL

README.Rmd

@@ -20,16 +20,15 @@ desc <- read.dcf("DESCRIPTION")
 desc <- setNames(as.list(desc), colnames(desc))
 ```
 
-# `r desc$Package` <img src="man/figures/logo.png" align="right" alt="" width="120"/>
+# `r desc$Package` <img src="man/figures/logo.png" align="right" width="120"/>
 
 > `r desc$Title`
 
-`visualizeR` proposes some utils to get REACH and AGORA colors, ready-to-go color palettes, and a few visualization functions (horizontal hist graph for instance).
+`visualizeR` proposes some utils to sane colors, ready-to-go color palettes, and a few visualization functions.
 
 ## Installation
 
-You can install the last version of visualizeR from
+You can install the last version of visualizeR from [GitHub](https://github.com/) with:
-[GitHub](https://github.com/) with:
 
 ```{r, eval = FALSE}
 # install.packages("devtools")
@@ -38,44 +37,32 @@ devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)
 
 ## Roadmap
 
-Roadmap is as follows:
+Roadmap is as follows: - [ ] Full revamp \## Request
 
-- [X] Add IMPACT's colors
+Please, do not hesitate to pull request any new viz or colors or color palettes, or to email request any change ([gnoblet\@zaclys.net](mailto:gnoblet@zaclys.net){.email}).
-- [X] Add all color palettes from the internal documentation
-- [ ] There remains to be added more-than-7-color palettes and black color palettes
-- [X] Add new types of visualization (e.g. dumbbell plot, lollipop plot, etc.)
-- [X] Use examples
-- [ ] Add some ease-map functions
-- [ ] Add some interactive functions (maps and graphs)
-- [ ] Consolidate and make errors transparent
 
-## Request
+## Colors
 
-Please, do not hesitate to pull request any new viz or colors or color palettes, or to email request any change (guillaume.noblet@reach-initiative.org or gnoblet@zaclys.net).
+Functions to access colors and palettes are `color()` or `palette()`. Feel free to pull request new colors.
-
-## Colors 
-
-Color palettes for REACH, AGORA and IMPACT are available. Functions to access colors and palettes are `cols_initiative()` or `pal_initiative()`. For now, the initiative with the most colors and color palettes is REACH. Feel free to pull requests new AGORA and IMPACT colors.
 
 ```{r example-colors, eval = TRUE}
 library(visualizeR)
 
-# Get all saved REACH colors, named
+# Get all saved colors, named
-cols_reach(unnamed = F)[1:10]
+color(unname = F)[1:10]
 
 # Extract a color palette as hexadecimal codes and reversed
-pal_reach(palette = "main", reversed = TRUE, color_ramp_palette = FALSE)
+palette(palette = "cat_5_main", reversed = TRUE, color_ramp_palette = FALSE)
 
 # Get all color palettes names
-pal_reach(show_palettes = T)
+palette(show_palettes = TRUE)
 ```
 
 ## Charts
 
-### Example 1: Bar chart, already REACH themed
+### Example 1: Bar chart
 
 ```{r example-bar-chart, out.width = "65%", eval = TRUE}
-library(visualizeR)
 library(palmerpenguins)
 library(dplyr)
 
@@ -87,33 +74,41 @@ df <- penguins |>
   ) |>
   ungroup()
 
+df_island <- penguins |>
+  group_by(island) |>
+  summarize(
+    mean_bl = mean(bill_length_mm, na.rm = T),
+    mean_fl = mean(flipper_length_mm, na.rm = T)
+  ) |>
+  ungroup()
+
 # Simple bar chart by group with some alpha transparency
-bar(df, island, mean_bl, species, percent = FALSE, alpha = 0.6, x_title = "Mean of bill length")
+bar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
 
-# Using another color palette through `theme_reach()` and changing scale to percent
+# Flipped / Horizontal
-bar(df, island, mean_bl, species, percent = TRUE, theme = theme_reach(palette = "artichoke_3"))
+hbar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
 
-# Not flipped, with text added, group_title, no y-axis and no bold for legend
+# Facetted
-bar(df, island, mean_bl, species, group_title = "Species", flip = FALSE, add_text = TRUE, add_text_suffix = "%", percent = FALSE, theme = theme_reach(text_font_face = "plain", axis_y = FALSE))
+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)
+
+#  Flipped, with text, smaller width
+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)
 ```
 
-### Example 2: Point chart, already REACH themed
+### Example 2: Scatterplot
-
-At this stage, `point_reach()` only supports categorical grouping colors with the `group` arg.
 
 ```{r example-point-chart, out.width = "65%", eval = TRUE}
-# Simple point chart
+# Simple scatterplot
-point(penguins, bill_length_mm, flipper_length_mm)
+point(penguins, "bill_length_mm", "flipper_length_mm")
 
-# Point chart with grouping colors, greater dot size, some transparency, reversed color palette
+# Scatterplot with grouping colors, greater dot size, some transparency
-point(penguins, bill_length_mm, flipper_length_mm, island, alpha = 0.6, size = 3, theme = theme_reach(reverse = TRUE))
+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)
 
-# Using another color palettes
+# Facetted scatterplot by island
-point(penguins, bill_length_mm, flipper_length_mm, island, size = 1.5, x_title = "Bill", y_title = "Flipper", title = "Length (mm)", theme = theme_reach(palette = "artichoke_3", text_font_face = , grid_major_x = TRUE, title_position_to_plot = 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, REACH themed
 
 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.
 
@@ -126,32 +121,22 @@ df <- tibble::tibble(
 ) |>
   dplyr::mutate(stat = round(stat, 0))
 
-# Example, adding a parameter to `theme_reach()` passed on `ggplot2::theme()` to align legend title
 
-dumbbell(df,
+
-  stat,
+
-  setting,
+# dumbbell(
-  admin1,
+#   df,
-  title = "% of HHs that reported open defecation as sanitation facility",
+#   "stat",
-  group_y_title = "Admin 1",
+#   "setting",
-  group_x_title = "Setting",
+#   "admin1",
-  theme = theme_reach(
+#   title = "% of HHs that reported open defecation as sanitation facility",
-    legend_position = "bottom",
+#   group_y_title = "Admin 1",
-    legend_direction = "horizontal",
+#   group_x_title = "Setting"
-    legend_title_font_face = "bold",
+# )
-    palette = "primary",
-    title_position_to_plot = FALSE,
-    legend.title.align = 0.5
-  )
-) +
-  # Change legend title position (could be included as part of the function)
-  ggplot2::guides(
-    color = ggplot2::guide_legend(title.position = "left"),
-    fill =  ggplot2::guide_legend(title.position = "left")
-  )
 ```
 
-### Example 4: donut chart, REACH themed (to used once, not twice)
+### Example 4: donut chart
+
 ```{r example-donut-plot, out.width = "65%", warning = FALSE}
 # Some summarized data: % of HHs by displacement status
 df <- tibble::tibble(
@@ -160,28 +145,27 @@ df <- tibble::tibble(
 )
 
 # Donut
-donut(df,
+# donut(df,
-  status,
+#   status,
-  percentage,
+#   percentage,
-  hole_size = 3,
+#   hole_size = 3,
-  add_text_suffix = "%",
+#   add_text_suffix = "%",
-  add_text_color = cols_reach("dk_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"
-  theme = theme_reach(legend_reverse = TRUE)
+# )
-)
 ```
 
+### Example 5: Waffle chart
 
-### Example 5: waffle chart
 ```{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, REACH themed
 ```{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
 df <- tibble::tibble(
@@ -197,23 +181,20 @@ df <- tibble::tibble(
 
 # Alluvial, here the group is the status for 2021
 
-alluvial(df,
+# alluvial(df,
-  status_from,
+#   status_from,
-  status_to,
+#   status_to,
-  percentage,
+#   percentage,
-  status_from,
+#   status_from,
-  from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
+#   from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
-  alpha = 0.8,
+#   alpha = 0.8,
-  group_title = "Status for 2021",
+#   group_title = "Status for 2021",
-  title = "% of HHs by self-reported status from 2021 to 2022",
+#   title = "% of HHs by self-reported status from 2021 to 2022"
-  theme = theme_reach(
+# )
-    axis_y = FALSE,
-    legend_position = "none"
-  )
-)
 ```
 
-### Example 7: lollipop chart
+### Example 7: Lollipop chart
+
 ```{r example-lollipop-chart, out.width = "65%", warning = FALSE}
 library(tidyr)
 # Prepare long data
@@ -223,80 +204,15 @@ df <- tibble::tibble(
 ) |>
   dplyr::mutate(stat = round(stat, 0))
 
-# Make lollipop plot, REACH themed, vertical with 45 degrees angle X-labels
+# Make lollipop plot, vertical with 45 degrees angle X-labels
-lollipop(df,
+# lollipop(df,
-  admin1,
+#   admin1,
-  stat,
+#   stat,
-  arrange = FALSE,
+#   arrange = FALSE,
-  add_text = FALSE,
+#   add_text = FALSE,
-  flip = FALSE,
+#   flip = FALSE,
-  y_title = "% of HHs",
+#   y_title = "% of HHs",
-  x_title = "Admin 1",
+#   x_title = "Admin 1",
-  title = "% of HHs that reported having received a humanitarian assistance",
+#   title = "% of HHs that reported having received a humanitarian assistance"
-  theme = theme_reach(
+# )
-    axis_text_x_angle = 45,
-    grid_major_y = TRUE,
-    grid_major_y_size = 0.2,
-    grid_major_x = TRUE,
-    grid_minor_y = TRUE
-  )
-)
-
-# Horizontal, greater point size, arranged by value, no grid, and text labels added
-lollipop(df,
-  admin1,
-  stat,
-  arrange = TRUE,
-  point_size = 10,
-  point_color = cols_reach("main_beige"),
-  segment_size = 2,
-  add_text = TRUE,
-  add_text_suffix = "%",
-  y_title = "% of HHs",
-  x_title = "Admin 1",
-  title = "% of HHs that reported having received a humanitarian assistance in the 12 months prior to the assessment",
-  theme = theme_reach(title_position_to_plot = FALSE)
-)
 ```
-
-
-## Maps
-
-```{r example-map, out.width = "50%"}
-# Add indicator layer
-# - based on "pretty" classes and title "Proportion (%)"
-# - buffer to add a 10% around the bounding box
-map <- add_indicator_layer(
-  indicator_admin1,
-  opn_dfc,
-  buffer = 0.1
-) +
-  # Layout - some defaults - add the map title
-  add_layout("% of HH that reported open defecation as sanitation facility") +
-  # Admin boundaries as list of shape files (lines) and colors, line widths and labels as vectors
-  add_admin_boundaries(
-    lines = list(line_admin1, border_admin0, frontier_admin0),
-    colors = cols_reach("main_lt_grey", "dk_grey", "black"),
-    lwds = c(0.5, 2, 3),
-    labels = c("Department", "Country", "Dominican Rep. frontier"),
-    title = "Administrative boundaries"
-  ) +
-  # Add text labels - centered on admin 1 centroids
-  add_admin_labels(centroid_admin1, ADM1_FR_UPPER) +
-  # Add a compass
-  add_compass() +
-  # Add a scale bar
-  add_scale_bar() +
-  # Add credits
-  add_credits("Admin. boundaries. : CNIGS \nCoord. system: GCS WGS 1984")
-```
-
-```{r map-save, eval = TRUE, include = FALSE, echo = TRUE}
-tmap::tmap_save(map,
-  "man/figures/README-example-map.png",
-  height = 4.5,
-  width = 6
-)
-```
-
-![Once exported with `tmap::tmap_save()`.](man/figures/README-example-map.png)

README.md

@@ -1,13 +1,12 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# visualizeR <img src="man/figures/logo.png" align="right" alt="" width="120"/>
+# visualizeR <img src="man/figures/logo.png" align="right" width="120"/>
 
-> What a color\! What a viz\!
+> What a color! What a viz!
 
-`visualizeR` proposes some utils to get REACH and AGORA colors,
+`visualizeR` proposes some utils to sane colors, ready-to-go color
-ready-to-go color palettes, and a few visualization functions
+palettes, and a few visualization functions.
-(horizontal hist graph for instance).
 
 ## Installation
 
@@ -21,128 +20,122 @@ devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)
 
 ## Roadmap
 
-Roadmap is as follows:
+Roadmap is as follows: - \[ \] Full revamp \## Request
-
-  - \[X\] Add IMPACT’s colors
-  - \[X\] Add all color palettes from the internal documentation
-  - \[ \] There remains to be added more-than-7-color palettes and black
-    color palettes
-  - \[X\] Add new types of visualization (e.g. dumbbell plot, lollipop
-    plot, etc.)
-  - \[X\] Use examples
-  - \[ \] Add some ease-map functions
-  - \[ \] Add some interactive functions (maps and graphs)
-  - \[ \] Consolidate and make errors transparent
-
-## Request
 
 Please, do not hesitate to pull request any new viz or colors or color
-palettes, or to email request any change
+palettes, or to email request any change (<gnoblet@zaclys.net>).
-(<guillaume.noblet@reach-initiative.org> or <gnoblet@zaclys.net>).
 
 ## Colors
 
-Color palettes for REACH, AGORA and IMPACT are available. Functions to
+Functions to access colors and palettes are `color()` or `palette()`.
-access colors and palettes are `cols_initiative()` or
+Feel free to pull request new colors.
-`pal_initiative()`. For now, the initiative with the most colors and
-color palettes is REACH. Feel free to pull requests new AGORA and IMPACT
-colors.
 
 ``` r
 library(visualizeR)
 
-# Get all saved REACH colors, named
+# Get all saved colors, named
-cols_reach(unnamed = F)[1:10]
+color(unname = F)[1:10]
-#>        white        black    main_grey     main_red main_lt_grey   main_beige 
+#>          white   lighter_grey     light_grey      dark_grey          black 
-#>    "#FFFFFF"    "#000000"    "#58585A"    "#EE5859"    "#C7C8CA"    "#D2CBB8" 
+#>      "#FFFFFF"      "#F5F5F5"      "#E3E3E3"      "#464647"      "#000000" 
-#>     iroise_1     iroise_2     iroise_3     iroise_4 
+#> cat_2_yellow_1 cat_2_yellow_2  cat_2_light_1  cat_2_light_2  cat_2_green_1 
-#>    "#DFECEF"    "#B1D7E0"    "#699DA3"    "#236A7A"
+#>      "#ffc20a"      "#0c7bdc"      "#fefe62"      "#d35fb7"      "#1aff1a"
 
 # Extract a color palette as hexadecimal codes and reversed
-pal_reach(palette = "main", reversed = TRUE, color_ramp_palette = FALSE)
+palette(palette = "cat_5_main", reversed = TRUE, color_ramp_palette = FALSE)
-#> [1] "#58585A" "#EE5859" "#C7C8CA" "#D2CBB8"
+#> [1] "#083d77" "#4ecdc4" "#f4c095" "#b47eb3" "#ffd5ff"
 
 # Get all color palettes names
-pal_reach(show_palettes = T)
+palette(show_palettes = TRUE)
-#>  [1] "main"            "primary"         "secondary"       "two_dots"       
+#>  [1] "cat_2_yellow"            "cat_2_light"            
-#>  [5] "two_dots_flashy" "red_main"        "red_main_5"      "red_alt"        
+#>  [3] "cat_2_green"             "cat_2_blue"             
-#>  [9] "red_alt_5"       "iroise"          "iroise_5"        "discrete_6"     
+#>  [5] "cat_5_main"              "cat_5_ibm"              
-#> [13] "red_2"           "red_3"           "red_4"           "red_5"          
+#>  [7] "cat_3_aquamarine"        "cat_3_tol_high_contrast"
-#> [17] "red_6"           "red_7"           "green_2"         "green_3"        
+#>  [9] "cat_8_tol_adapted"       "cat_3_custom_1"         
-#> [21] "green_4"         "green_5"         "green_6"         "green_7"        
+#> [11] "cat_4_custom_1"          "cat_5_custom_1"         
-#> [25] "artichoke_2"     "artichoke_3"     "artichoke_4"     "artichoke_5"    
+#> [13] "cat_6_custom_1"          "div_5_orange_blue"      
-#> [29] "artichoke_6"     "artichoke_7"     "blue_2"          "blue_3"         
+#> [15] "div_5_green_purple"
-#> [33] "blue_4"          "blue_5"          "blue_6"          "blue_7"
 ```
 
 ## Charts
 
-### Example 1: Bar chart, already REACH themed
+### Example 1: Bar chart
 
 ``` r
-library(visualizeR)
 library(palmerpenguins)
 library(dplyr)
 
-df <- penguins |> 
+df <- penguins |>
-  group_by(island, species) |> 
+  group_by(island, species) |>
   summarize(
     mean_bl = mean(bill_length_mm, na.rm = T),
-    mean_fl = mean(flipper_length_mm, na.rm = T)) |> 
+    mean_fl = mean(flipper_length_mm, na.rm = T)
+  ) |>
+  ungroup()
+
+df_island <- penguins |>
+  group_by(island) |>
+  summarize(
+    mean_bl = mean(bill_length_mm, na.rm = T),
+    mean_fl = mean(flipper_length_mm, na.rm = T)
+  ) |>
   ungroup()
 
 # Simple bar chart by group with some alpha transparency
-bar(df, island, mean_bl, species, percent = FALSE, alpha = 0.6, x_title = "Mean of bill length")
+bar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
 ```
 
 <img src="man/figures/README-example-bar-chart-1.png" width="65%" />
 
 ``` r
 
-# Using another color palette through `theme_reach()` and changing scale to percent
+# Flipped / Horizontal
-bar(df, island,mean_bl, species, percent = TRUE, theme = theme_reach(palette = "artichoke_3"))
+hbar(df, "island", "mean_bl", "species", x_title = "Mean of bill length", title = "Mean of bill length by island and species")
 ```
 
 <img src="man/figures/README-example-bar-chart-2.png" width="65%" />
 
 ``` r
 
-# Not flipped, with text added, group_title, no y-axis and no bold for legend
+# Facetted
-bar(df, island, mean_bl, species, group_title = "Species", flip = FALSE, add_text = TRUE, add_text_suffix = "%", percent = FALSE, theme = theme_reach(text_font_face = "plain", axis_y = FALSE))
+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)
 ```
 
 <img src="man/figures/README-example-bar-chart-3.png" width="65%" />
 
-### Example 2: Point chart, already REACH themed
-
-At this stage, `point_reach()` only supports categorical grouping colors
-with the `group` arg.
-
 ``` r
 
-# Simple point chart
+#  Flipped, with text, smaller width
-point(penguins, bill_length_mm, flipper_length_mm)
+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)
+```
+
+<img src="man/figures/README-example-bar-chart-4.png" width="65%" />
+
+### Example 2: Scatterplot
+
+``` r
+# Simple scatterplot
+point(penguins, "bill_length_mm", "flipper_length_mm")
 ```
 
 <img src="man/figures/README-example-point-chart-1.png" width="65%" />
 
 ``` r
 
-# Point chart with grouping colors, greater dot size, some transparency, reversed color palette
+# Scatterplot with grouping colors, greater dot size, some transparency
-point(penguins, bill_length_mm, flipper_length_mm, island, alpha = 0.6, size = 3, theme = theme_reach(reverse = TRUE))
+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)
 ```
 
 <img src="man/figures/README-example-point-chart-2.png" width="65%" />
 
 ``` r
 
-# Using another color palettes
+# Facetted scatterplot by island
-point(penguins, bill_length_mm, flipper_length_mm, island, size = 1.5, x_title = "Bill", y_title = "Flipper", title = "Length (mm)", theme = theme_reach(palette = "artichoke_3", text_font_face = , grid_major_x = TRUE,  title_position_to_plot = 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)
 ```
 
 <img src="man/figures/README-example-point-chart-3.png" width="65%" />
 
-### Example 3: Dumbbell plot, REACH themed
+### 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
@@ -157,34 +150,23 @@ df <- tibble::tibble(
 ) |>
   dplyr::mutate(stat = round(stat, 0))
 
-# Example, adding a parameter to `theme_reach()` passed on `ggplot2::theme()` to align legend title
 
-dumbbell(df,
+
-         stat,
+
-         setting,
+# dumbbell(
-         admin1,
+#   df,
-         title = "% of HHs that reported open defecation as sanitation facility",
+#   "stat",
-         group_y_title = "Admin 1",
+#   "setting",
-         group_x_title = "Setting",
+#   "admin1",
-         theme = theme_reach(legend_position =  "bottom",
+#   title = "% of HHs that reported open defecation as sanitation facility",
-                             legend_direction = "horizontal",
+#   group_y_title = "Admin 1",
-                             legend_title_font_face = "bold",
+#   group_x_title = "Setting"
-                             palette = "primary",
+# )
-                             title_position_to_plot = FALSE,
-                             legend.title.align = 0.5)) +
-  # Change legend title position (could be included as part of the function)
-  ggplot2::guides(  
-    color = ggplot2::guide_legend(title.position = "left"),
-    fill =  ggplot2::guide_legend(title.position = "left")
-  )
 ```
 
-<img src="man/figures/README-example-dumbbell-plot-1.png" width="65%" />
+### Example 4: donut chart
-
-### Example 4: donut chart, REACH themed (to used once, not twice)
 
 ``` r
-
 # Some summarized data: % of HHs by displacement status
 df <- tibble::tibble(
   status = c("Displaced", "Non displaced", "Returnee", "Don't know/Prefer not to say"),
@@ -192,139 +174,74 @@ df <- tibble::tibble(
 )
 
 # Donut
-donut(df, 
+# donut(df,
-      status, 
+#   status,
-      percentage, 
+#   percentage,
-      hole_size  = 3, 
+#   hole_size = 3,
-      add_text_suffix = "%", 
+#   add_text_suffix = "%",
-      add_text_color = cols_reach("dk_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"
-      theme = theme_reach(legend_reverse = TRUE))
+# )
 ```
 
-<img src="man/figures/README-example-donut-plot-1.png" width="65%" />
+### Example 5: Waffle chart
-
-### Example 5: waffle chart
 
 ``` r
 #
-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")
 ```
 
-<img src="man/figures/README-example-waffle-plot-1.png" width="65%" />
+### Example 6: Alluvial chart
-
-### Example 6: alluvial chart, REACH themed
 
 ``` r
-
 # Some summarized data: % of HHs by self-reported status of displacement in 2021 and in 2022
 df <- tibble::tibble(
-  status_from = c(rep("Displaced", 4),
+  status_from = c(
-                  rep("Non displaced", 4),
+    rep("Displaced", 4),
-                  rep("Returnee", 4),
+    rep("Non displaced", 4),
-                  rep("Dnk/Pnts", 4)),
+    rep("Returnee", 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"),
   percentage = c(20, 8, 18, 1, 12, 21, 0, 2, 0, 3, 12, 1, 0, 0, 1, 1)
 )
 
 # Alluvial, here the group is the status for 2021
 
-alluvial(df, 
+# alluvial(df,
-         status_from, 
+#   status_from,
-         status_to,
+#   status_to,
-         percentage, 
+#   percentage,
-         status_from,
+#   status_from,
-         from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"), 
+#   from_levels = c("Displaced", "Non displaced", "Returnee", "Dnk/Pnts"),
-         alpha = 0.8, 
+#   alpha = 0.8,
-         group_title = "Status for 2021",
+#   group_title = "Status for 2021",
-         title = "% of HHs by self-reported status from 2021 to 2022", 
+#   title = "% of HHs by self-reported status from 2021 to 2022"
-         theme = theme_reach(
+# )
-           axis_y = FALSE, 
-           legend_position = "none"))
 ```
 
-<img src="man/figures/README-example-alluvial-plot-1.png" width="65%" />
+### Example 7: Lollipop chart
-
-### Example 7: lollipop chart
 
 ``` r
 library(tidyr)
 # Prepare long data
 df <- tibble::tibble(
- admin1 = replicate(15, sample(letters, 8)) |> t() |> as.data.frame() |> unite("admin1", sep = "") |> dplyr::pull(admin1),  
+  admin1 = replicate(15, sample(letters, 8)) |> t() |> as.data.frame() |> unite("admin1", sep = "") |> dplyr::pull(admin1),
- stat = rnorm(15, mean = 50, sd = 15)) |>
+  stat = rnorm(15, mean = 50, sd = 15)
+) |>
   dplyr::mutate(stat = round(stat, 0))
 
-# Make lollipop plot, REACH themed, vertical with 45 degrees angle X-labels
+# Make lollipop plot, vertical with 45 degrees angle X-labels
-lollipop(df,
+# lollipop(df,
-         admin1,
+#   admin1,
-         stat,
+#   stat,
-         arrange = FALSE,
+#   arrange = FALSE,
-         add_text = FALSE,
+#   add_text = FALSE,
-         flip = FALSE,
+#   flip = FALSE,
-         y_title = "% of HHs",
+#   y_title = "% of HHs",
-         x_title = "Admin 1",
+#   x_title = "Admin 1",
-         title = "% of HHs that reported having received a humanitarian assistance",
+#   title = "% of HHs that reported having received a humanitarian assistance"
-         theme = theme_reach(axis_text_x_angle = 45, 
+# )
-                             grid_major_y = TRUE, 
-                             grid_major_y_size = 0.2, 
-                             grid_major_x = TRUE, 
-                             grid_minor_y = TRUE))
 ```
-
-<img src="man/figures/README-example-lollipop-chart-1.png" width="65%" />
-
-``` r
-
-# Horizontal, greater point size, arranged by value, no grid, and text labels added
-lollipop(df,
-         admin1,
-         stat,
-         arrange = TRUE,
-         point_size = 10,
-         point_color = cols_reach("main_beige"),
-         segment_size = 2,
-         add_text = TRUE,
-         add_text_suffix = "%",
-         y_title = "% of HHs",
-         x_title = "Admin 1",
-         title = "% of HHs that reported having received a humanitarian assistance in the 12 months prior to the assessment",
-         theme = theme_reach(title_position_to_plot = FALSE))
-```
-
-<img src="man/figures/README-example-lollipop-chart-2.png" width="65%" />
-
-## Maps
-
-``` r
-
-# Add indicator layer 
-# - based on "pretty" classes and title "Proportion (%)" 
-# - buffer to add a 10% around the bounding box
-map <- add_indicator_layer(
-  indicator_admin1, 
-  opn_dfc,
-  buffer = 0.1) + 
-  # Layout - some defaults - add the map title
-  add_layout("% of HH that reported open defecation as sanitation facility") + 
-  # Admin boundaries as list of shape files (lines) and colors, line widths and labels as vectors
-  add_admin_boundaries(
-    lines = list(line_admin1, border_admin0, frontier_admin0),
-    colors = cols_reach("main_lt_grey", "dk_grey", "black"),
-    lwds = c(0.5, 2, 3),
-    labels = c("Department", "Country", "Dominican Rep. frontier"),
-    title = "Administrative boundaries") + 
-  # Add text labels - centered on admin 1 centroids
-  add_admin_labels(centroid_admin1, ADM1_FR_UPPER) +
-  # Add a compass
-  add_compass() +
-  # Add a scale bar
-  add_scale_bar() +
-  # Add credits
-  add_credits("Admin. boundaries. : CNIGS \nCoord. system: GCS WGS 1984")
-```
-
-![Once exported with
-`tmap::tmap_save()`.](man/figures/README-example-map.png)

data-raw/border_admin0.prj

@@ -1 +0,0 @@
-PROJCS["WGS_1984_UTM_Zone_18N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-75.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["m",1.0]]

data-raw/centroid_admin1.prj

@@ -1 +0,0 @@
-GEOGCS["GCS_unknown",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

data-raw/frontier_admin0.prj

@@ -1 +0,0 @@
-GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

data-raw/indicator_admin1.prj

@@ -1 +0,0 @@
-GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

data-raw/line_admin1.prj

@@ -1 +0,0 @@
-GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

data-raw/shapefiles.R

@@ -1,20 +0,0 @@
-#------ Border - admin 0
-border_admin0 <- sf::st_read("data-raw/border_admin0.shp")
-usethis::use_data(border_admin0, overwrite = TRUE)
-
-#------ Frontier - admin 0
-frontier_admin0 <- sf::st_read("data-raw/frontier_admin0.shp")
-usethis::use_data(frontier_admin0, overwrite = TRUE)
-
-#------ Line - admin 1
-line_admin1 <- sf::st_read("data-raw/line_admin1.shp")
-usethis::use_data(line_admin1, overwrite = TRUE)
-
-#------ Centroid - admin 1
-centroid_admin1 <- sf::st_read("data-raw/centroid_admin1.shp") |>
-  dplyr::rename(ADM1_FR_UPPER = ADM1_FR_)
-usethis::use_data(centroid_admin1, overwrite = TRUE)
-
-#------ Indicator polygon  - admin 1
-indicator_admin1 <- sf::st_read("data-raw/indicator_admin1.shp")
-usethis::use_data(indicator_admin1, overwrite = TRUE)

man/bar.Rd

@@ -1,16 +1,32 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/bar.R
-\name{bar}
+\name{hbar}
+\alias{hbar}
 \alias{bar}
 \title{Simple bar chart}
 \usage{
+hbar(
+  ...,
+  flip = TRUE,
+  add_text = FALSE,
+  theme_fun = theme_bar(flip = flip, add_text = add_text)
+)
+
 bar(
   df,
   x,
   y,
   group = "",
-  add_color = color("dark_grey"),
+  facet = "",
-  flip = TRUE,
+  order = "none",
+  x_rm_na = TRUE,
+  y_rm_na = TRUE,
+  group_rm_na = TRUE,
+  facet_rm_na = TRUE,
+  y_expand = 0.1,
+  add_color = color("cat_5_main_1"),
+  add_color_guide = TRUE,
+  flip = FALSE,
   wrap = NULL,
   position = "dodge",
   alpha = 1,
@@ -20,18 +36,28 @@ bar(
   title = NULL,
   subtitle = NULL,
   caption = NULL,
-  width = 0.5,
+  width = 0.8,
-  add_text = TRUE,
+  add_text = FALSE,
-  add_text_size = 5,
+  add_text_size = 4.5,
   add_text_color = color("dark_grey"),
-  add_text_font_face = "plain",
+  add_text_font_face = "bold",
   add_text_threshold_display = 0.05,
   add_text_suffix = "\%",
   add_text_expand_limit = 1.2,
-  add_text_round = 1
+  add_text_round = 1,
+  theme_fun = theme_bar(flip = flip, add_text = add_text, axis_text_x_angle = 0,
+    axis_text_x_vjust = 0.5, axis_text_x_hjust = 0.5),
+  scale_fill_fun = scale_fill_visualizer_discrete(),
+  scale_color_fun = scale_color_visualizer_discrete()
 )
 }
 \arguments{
+\item{flip}{TRUE or FALSE (default). Default to TRUE or horizontal bar plot.}
+
+\item{add_text}{TRUE or FALSE. Add values as text.}
+
+\item{theme_fun}{Whatever theme function. For no custom theme, use theme_fun = NULL.}
+
 \item{df}{A data frame.}
 
 \item{x}{A quoted numeric column.}
@@ -40,9 +66,23 @@ bar(
 
 \item{group}{Some quoted grouping categorical column, e.g. administrative areas or population groups.}
 
+\item{facet}{Some quoted grouping categorical column, e.g. administrative areas or population groups.}
+
+\item{order}{Should bars be ordered? "none" if no, "y" if yes based on y, "grouped" if yes based on y and group.}
+
+\item{x_rm_na}{Remove NAs in x?}
+
+\item{y_rm_na}{Remove NAs in y?}
+
+\item{group_rm_na}{Remove NAs in group?}
+
+\item{facet_rm_na}{Remove NAs in facet?}
+
+\item{y_expand}{Multiplier to expand the y axis.}
+
 \item{add_color}{Add a color to bars (if no grouping).}
 
-\item{flip}{TRUE or FALSE. Default to TRUE or horizontal bar plot.}
+\item{add_color_guide}{Should a legend be added?}
 
 \item{wrap}{Should x-labels be wrapped? Number of characters.}
 
@@ -64,8 +104,6 @@ bar(
 
 \item{width}{Bar width.}
 
-\item{add_text}{TRUE or FALSE. Add values as text.}
-
 \item{add_text_size}{Text size.}
 
 \item{add_text_color}{Text color.}
@@ -76,14 +114,10 @@ bar(
 
 \item{add_text_suffix}{If percent is FALSE, should we add a suffix to the text label?}
 
-\item{add_text_expand_limit}{Default to adding 10% on top of the bar.}
+\item{add_text_expand_limit}{Default to adding 10\% on top of the bar.}
 
 \item{add_text_round}{Round the text label.}
-
-\item{theme_fun}{Whatever theme function. For no custom theme, use theme_fun = NULL.}
-
-\item{scale_impact}{Use the package custom scales for fill and color.}
 }
 \description{
-Simple bar chart
+`bar()` is a simple bar chart with some customization allowed, in particular the `theme_fun` argument for theming. `hbar()` uses `bar()` with sane defaults for a horizontal bar chart.
 }

man/dumbbell.Rd

@@ -0,0 +1,85 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/dumbbell.R
+\name{dumbbell}
+\alias{dumbbell}
+\title{Make dumbbell chart.}
+\usage{
+dumbbell(
+  df,
+  col,
+  group_x,
+  group_y,
+  point_size = 5,
+  point_alpha = 1,
+  segment_size = 2.5,
+  segment_color = cols_reach("main_lt_grey"),
+  group_x_title = NULL,
+  group_y_title = NULL,
+  x_title = NULL,
+  title = NULL,
+  subtitle = NULL,
+  caption = NULL,
+  line_to_y_axis = TRUE,
+  line_to_y_axis_type = 3,
+  line_to_y_axis_width = 0.5,
+  line_to_y_axis_color = cols_reach("main_grey"),
+  add_text = TRUE,
+  add_text_vjust = 2,
+  add_text_size = 3.5,
+  add_text_color = cols_reach("main_grey"),
+  theme = theme_reach(palette = "primary")
+)
+}
+\arguments{
+\item{df}{A data frame.}
+
+\item{col}{A numeric column.}
+
+\item{group_x}{The grouping column on the x-axis; only two groups.}
+
+\item{group_y}{The grouping column on the y-axis.}
+
+\item{point_size}{Point size.}
+
+\item{point_alpha}{Point alpha.}
+
+\item{segment_size}{Segment size.}
+
+\item{segment_color}{Segment color.}
+
+\item{group_x_title}{X-group and legend title.}
+
+\item{group_y_title}{Y-axis and group title.}
+
+\item{x_title}{X-axis title.}
+
+\item{title}{Title.}
+
+\item{subtitle}{Subtitle.}
+
+\item{caption}{Caption.}
+
+\item{line_to_y_axis}{TRUE or FALSE; add a line connected points and Y-axis.}
+
+\item{line_to_y_axis_type}{Line to Y-axis type.}
+
+\item{line_to_y_axis_width}{Line to Y-axis width.}
+
+\item{line_to_y_axis_color}{Line to Y-axis color.}
+
+\item{add_text}{TRUE or FALSE; add text at the points.}
+
+\item{add_text_vjust}{Vertical adjustment.}
+
+\item{add_text_size}{Text size.}
+
+\item{add_text_color}{Text color.}
+
+\item{theme}{A ggplot2 theme, default to `theme_reach()`}
+}
+\value{
+A dumbbell chart.
+}
+\description{
+Make dumbbell chart.
+}

man/point.Rd

@@ -2,14 +2,21 @@
 % Please edit documentation in R/point.R
 \name{point}
 \alias{point}
-\title{Simple point chart}
+\title{Simple scatterplot}
 \usage{
 point(
   df,
   x,
   y,
   group = "",
-  add_color = color("branding_reach_red"),
+  facet = "",
+  facet_scales = "free",
+  x_rm_na = TRUE,
+  y_rm_na = TRUE,
+  group_rm_na = TRUE,
+  facet_rm_na = TRUE,
+  add_color = color("cat_5_main_1"),
+  add_color_guide = TRUE,
   flip = TRUE,
   alpha = 1,
   size = 2,
@@ -19,25 +26,37 @@ point(
   title = NULL,
   subtitle = NULL,
   caption = NULL,
-  theme_fun = theme_reach(grid_major_y = TRUE),
+  theme_fun = theme_point(),
-  palette = "cat_5_ibm",
+  scale_fill_fun = scale_fill_visualizer_discrete(),
-  scale_impact = TRUE,
+  scale_color_fun = scale_color_visualizer_discrete()
-  direction = 1,
-  reverse_guide = TRUE
 )
 }
 \arguments{
 \item{df}{A data frame.}
 
-\item{x}{A numeric column.}
+\item{x}{A quoted numeric column.}
 
-\item{y}{Another numeric column.}
+\item{y}{A quoted numeric column.}
 
-\item{group}{Some grouping categorical column, e.g. administrative areas or population groups.}
+\item{group}{Some quoted grouping categorical column, e.g. administrative areas or population groups.}
 
-\item{add_color}{Add a color to bars (if no grouping).}
+\item{facet}{Some quoted grouping categorical column.}
 
-\item{flip}{TRUE or FALSE. Default to TRUE or horizontal bar plot.}
+\item{facet_scales}{Character. Either "free" (default) or "fixed" for facet scales.}
+
+\item{x_rm_na}{Remove NAs in x?}
+
+\item{y_rm_na}{Remove NAs in y?}
+
+\item{group_rm_na}{Remove NAs in group?}
+
+\item{facet_rm_na}{Remove NAs in facet?}
+
+\item{add_color}{Add a color to points (if no grouping).}
+
+\item{add_color_guide}{Should a legend be added?}
+
+\item{flip}{TRUE or FALSE.}
 
 \item{alpha}{Fill transparency.}
 
@@ -55,10 +74,8 @@ point(
 
 \item{caption}{Plot caption. Default to NULL.}
 
-\item{theme_fun}{Whatever theme. Default to theme_reach(). NULL if no theming needed.}
+\item{theme_fun}{Whatever theme. Default to theme_point(). NULL if no theming needed.}
-
-\item{scale_impact}{Use the package custom scales for fill and color.}
 }
 \description{
-Simple point chart
+Simple scatterplot
 }

man/reorder_by.Rd

@@ -0,0 +1,42 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/reorder_by.R
+\name{reorder_by}
+\alias{reorder_by}
+\title{Reorder a Data Frame}
+\usage{
+reorder_by(df, x, y, group = "", order = "y", dir_order = 1)
+}
+\arguments{
+\item{df}{A data frame to be reordered.}
+
+\item{x}{A character scalar specifying the column to be reordered.}
+
+\item{y}{A character scalar specifying the column to order by if ordering by values.}
+
+\item{group}{A character scalar specifying the grouping column (optional).}
+
+\item{order}{A character scalar specifying the order type (one of "none", "y", "grouped"). See details.}
+
+\item{dir_order}{A logical scalar specifying whether to flip the order.}
+}
+\value{
+The reordered data frame.
+}
+\description{
+Reorder a Data Frame
+}
+\details{
+Ordering takes the following possible values:
+
+* "none": No reordering.
+* "y": Order by values of y.
+* "grouped_y": Order by values of y and group.
+* "x": Order alphabetically by x.
+* "grouped_x": Order alphabetically by x and group.
+}
+\examples{
+# Example usage
+df <- data.frame(col1 = c("b", "a", "c"), col2 = c(10, 25, 3))
+reorder_by(df, "col1", "col2")
+
+}

man/scale_color_visualizer_discrete.Rd

@@ -11,6 +11,7 @@ scale_color_visualizer_discrete(
   palette = "cat_5_main",
   direction = 1,
   reverse_guide = TRUE,
+  title_position = NULL,
   ...
 )
 
@@ -18,6 +19,7 @@ scale_fill_visualizer_discrete(
   palette = "cat_5_main",
   direction = 1,
   reverse_guide = TRUE,
+  title_position = NULL,
   ...
 )
 
@@ -25,6 +27,7 @@ scale_fill_visualizer_continuous(
   palette = "seq_5_main",
   direction = 1,
   reverse_guide = TRUE,
+  title_position = NULL,
   ...
 )
 
@@ -32,6 +35,7 @@ scale_color_visualizer_continuous(
   palette = "seq_5_main",
   direction = 1,
   reverse_guide = TRUE,
+  title_position = NULL,
   ...
 )
 }

man/scale_visualizer_discrete.Rd

@@ -1,25 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/scale.R
-\name{scale_visualizer_discrete}
-\alias{scale_visualizer_discrete}
-\title{One scale for all}
-\usage{
-scale_visualizer_discrete(
-  palette = "cat_5_main",
-  direction = 1,
-  reverse_guide = TRUE,
-  ...
-)
-}
-\arguments{
-\item{palette}{Palette name from [palette()].}
-
-\item{direction}{1 or -1; should the order of colors be reversed?}
-
-\item{reverse_guide}{Boolean indicating whether the guide should be reversed.}
-
-\item{...}{Additional arguments passed to [ggplot2::discrete_scale()] if discrete or [ggplot2::scale_fill_gradient()] if continuous.}
-}
-\description{
-This function is based on [palette()]. If palette is NULL, the used palette will be magma from gpplot2's viridis scale constructors.
-}

man/theme_bar.Rd

@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/theme_bar.R
+\name{theme_bar}
+\alias{theme_bar}
+\title{Custom Theme for Bar Charts}
+\usage{
+theme_bar(
+  flip = TRUE,
+  add_text = FALSE,
+  axis_text_x_angle = 0,
+  axis_text_x_vjust = 0.5,
+  axis_text_x_hjust = 0.5
+)
+}
+\value{
+A custom theme object.
+}
+\description{
+Custom Theme for Bar Charts
+}

man/theme_custom.Rd

@@ -1,14 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/theme_bar.R
-\name{theme_custom}
-\alias{theme_custom}
-\title{Custom Theme}
-\usage{
-theme_custom()
-}
-\value{
-A custom theme object.
-}
-\description{
-Create a custom theme for ggplot2.
-}

man/theme_default.Rd

@@ -1,21 +1,23 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/theme.R
+% Please edit documentation in R/theme_default.R
-\name{theme_visualizer_default}
+\name{theme_default}
-\alias{theme_visualizer_default}
+\alias{theme_default}
 \title{ggplot2 theme wrapper with fonts and colors}
 \usage{
-theme_visualizer_default(
+theme_default(
-  font_family = "Carlito",
+  title_font_family = "Carlito",
-  title_size = 14,
+  title_size = 16,
   title_color = color("dark_grey"),
   title_font_face = "bold",
   title_hjust = NULL,
   title_position_to_plot = TRUE,
-  title_font_family = "Carlito",
-  subtitle_size = 13,
-  subtitle_font_face = "plain",
   subtitle_font_family = "Carlito",
-  text_size = 12,
+  subtitle_size = 15,
+  subtitle_color = color("dark_grey"),
+  subtitle_font_face = "plain",
+  subtitle_hjust = NULL,
+  text_font_family = "Carlito",
+  text_size = 13,
   text_color = color("dark_grey"),
   text_font_face = "plain",
   panel_background_color = "#FFFFFF",
@@ -25,21 +27,29 @@ theme_visualizer_default(
   legend_direction = "horizontal",
   legend_justification = "center",
   legend_reverse = TRUE,
-  legend_title_size = 12,
+  legend_title_size = 13,
   legend_title_color = color("dark_grey"),
   legend_title_font_face = "plain",
-  legend_text_size = 12,
+  legend_title_font_family = "Carlito",
+  legend_text_size = 13,
   legend_text_color = color("dark_grey"),
   legend_text_font_face = "plain",
+  legend_text_font_family = "Carlito",
+  facet_size = 14,
+  facet_color = color("dark_grey"),
+  facet_font_face = "bold",
+  facet_font_family = "Carlito",
+  facet_bg_color = color("lighter_grey"),
   axis_x = TRUE,
   axis_y = TRUE,
   axis_text_x = TRUE,
-  axis_line_x = TRUE,
+  axis_line_x = FALSE,
-  axis_ticks_x = TRUE,
+  axis_ticks_x = FALSE,
   axis_text_y = TRUE,
   axis_line_y = TRUE,
   axis_ticks_y = TRUE,
-  axis_text_size = 12,
+  axis_text_font_family = "Carlito",
+  axis_text_size = 13,
   axis_text_color = color("dark_grey"),
   axis_text_font_face = "plain",
   axis_title_size = 15,
@@ -53,19 +63,21 @@ theme_visualizer_default(
   grid_major_color = color("dark_grey"),
   grid_major_x_size = 0.1,
   grid_major_y_size = 0.1,
-  grid_minor_x = FALSE,
+  grid_minor_x = TRUE,
   grid_minor_y = FALSE,
   grid_minor_color = color("dark_grey"),
   grid_minor_x_size = 0.05,
   grid_minor_y_size = 0.05,
+  caption_font_family = "Carlito",
+  caption_font_face = "plain",
   caption_position_to_plot = TRUE,
-  caption_text_size = 10,
+  caption_size = 11,
-  caption_text_color = color("dark_grey"),
+  caption_color = color("dark_grey"),
   ...
 )
 }
 \arguments{
-\item{font_family}{The font family for all plot's texts. Default to "Segoe UI".}
+\item{title_font_family}{Title font family. Default to "Roboto Condensed".}
 
 \item{title_size}{The size of the legend title. Defaults to 11.}
 
@@ -77,8 +89,6 @@ theme_visualizer_default(
 
 \item{title_position_to_plot}{TRUE or FALSE. Positioning to plot or to panel?}
 
-\item{title_font_family}{Title font family. Default to "Roboto Condensed".}
-
 \item{text_size}{The size of all text other than the title, subtitle and caption. Defaults to 10.}
 
 \item{text_color}{Text color.}
@@ -169,7 +179,7 @@ theme_visualizer_default(
 
 \item{...}{Additional arguments passed to [ggplot2::theme()].}
 
-\item{p}{A ggplot2 object.}
+\item{font_family}{The font family for all plot's texts. Default to "Segoe UI".}
 }
 \description{
 Give some reach colors and fonts to a ggplot.

man/theme_point.Rd

@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/theme_point.R
+\name{theme_point}
+\alias{theme_point}
+\title{Custom Theme for Point Charts}
+\usage{
+theme_point()
+}
+\arguments{
+\item{flip}{Logical. Whether the plot is flipped (horizonal).}
+
+\item{axis_text_x_angle}{Angle for x-axis text.}
+
+\item{axis_text_x_vjust}{Vertical justification for x-axis text.}
+
+\item{axis_text_x_hjust}{Horizontal justification for x-axis text.}
+}
+\value{
+A custom theme object.
+}
+\description{
+Custom Theme for Point Charts
+}

man/theme_visualizer.Rd

@@ -1,16 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/theme_visualizer_bar.R
-\docType{data}
-\name{ThemeVisualizerBar}
-\alias{ThemeVisualizerBar}
-\title{ggplot2 theme for bar charts with sane defaults}
-\format{
-An object of class \code{ThemeVisualizerBar} (inherits from \code{ggproto}, \code{gg}) of length 1.
-}
-\usage{
-ThemeVisualizerBar
-}
-\description{
-ggplot2 theme for bar charts with sane defaults
-}
-\keyword{datasets}

man/theme_visualizer_bar.Rd

@@ -1,33 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/theme_visualizer_bar.R
-\name{theme_visualizer_bar}
-\alias{theme_visualizer_bar}
-\title{Dynamic Theme for ggplot2}
-\usage{
-theme_visualizer_bar()
-}
-\value{
-A ggproto object that applies a dynamic theme to a ggplot2 plot.
-}
-\description{
-A dynamic theme that adjusts axis text styles based on whether the plot is flipped.
-}
-\details{
-This function dynamically applies different axis text styles depending on 
-the coordinate system of the plot. If the plot is flipped (e.g., using 
-`coord_flip()`), the x-axis and y-axis text styles are adjusted accordingly.
-}
-\examples{
-library(ggplot2)
-
-# Example with a regular plot
-p <- ggplot(mpg, aes(displ, hwy)) +
-  geom_col()
-
-# Add the dynamic theme
-p + theme_visualizer_bar()
-
-# Add the dynamic theme with a flipped coordinate system
-p + theme_visualizer_bar() + coord_flip()
-
-}

man/visualizeR-package.Rd

@@ -0,0 +1,25 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/visualizeR-package.R
+\docType{package}
+\name{visualizeR-package}
+\alias{visualizeR}
+\alias{visualizeR-package}
+\title{visualizeR: What a color! What a viz!}
+\description{
+\if{html}{\figure{logo.png}{options: style='float: right' alt='logo' width='120'}}
+
+It basically provides colors as hex codes, color palettes, and some viz functions (graphs and maps).
+}
+\seealso{
+Useful links:
+\itemize{
+  \item \url{https://github.com/gnoblet/visualizeR}
+  \item \url{https://gnoblet.github.io/visualizeR/}
+}
+
+}
+\author{
+\strong{Maintainer}: Noblet Guillaume \email{gnoblet@zaclys.net}
+
+}
+\keyword{internal}

plot.svg

@@ -1,97 +0,0 @@
-<?xml version='1.0' encoding='UTF-8' ?>
-<svg xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' class='svglite' width='717.08pt' height='586.70pt' viewBox='0 0 717.08 586.70'>
-<defs>
-  <style type='text/css'><![CDATA[
-    .svglite line, .svglite polyline, .svglite polygon, .svglite path, .svglite rect, .svglite circle {
-      fill: none;
-      stroke: #000000;
-      stroke-linecap: round;
-      stroke-linejoin: round;
-      stroke-miterlimit: 10.00;
-    }
-    .svglite text {
-      white-space: pre;
-    }
-  ]]></style>
-</defs>
-<rect width='100%' height='100%' style='stroke: none; fill: none;'/>
-<defs>
-  <clipPath id='cpMC4wMHw3MTcuMDh8MC4wMHw1ODYuNzA='>
-    <rect x='0.00' y='0.00' width='717.08' height='586.70' />
-  </clipPath>
-</defs>
-<g clip-path='url(#cpMC4wMHw3MTcuMDh8MC4wMHw1ODYuNzA=)'>
-</g>
-<defs>
-  <clipPath id='cpNjIuOTV8NzExLjYwfDYxLjExfDU2OC40OQ=='>
-    <rect x='62.95' y='61.11' width='648.65' height='507.37' />
-  </clipPath>
-</defs>
-<g clip-path='url(#cpNjIuOTV8NzExLjYwfDYxLjExfDU2OC40OQ==)'>
-<polyline points='62.95,568.49 62.95,61.11 ' style='stroke-width: 0.21; stroke: #464647; stroke-linecap: butt;' />
-<polyline points='301.22,568.49 301.22,61.11 ' style='stroke-width: 0.21; stroke: #464647; stroke-linecap: butt;' />
-<polyline points='539.49,568.49 539.49,61.11 ' style='stroke-width: 0.21; stroke: #464647; stroke-linecap: butt;' />
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test-example.R

@@ -27,8 +27,17 @@ library(visualizeR)
 library(rio)
 dat <- import("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/11_SevCatOneNumNestedOneObsPerGroup.csv")
 
+dumbbell(
+  df,
+  "stat",
+  "setting",
+  "admin1",
+  title = "% of HHs that reported open defecation as sanitation facility",
+  group_y_title = "Admin 1",
+  group_x_title = "Setting"
+)
+
 library(dplyr)
-library(ggplot2)
 library(data.table)
 # dat as a data.table if it4s not
 if (!checkmate::test_data_table(dat)) {
@@ -46,52 +55,43 @@ dat[, value := fifelse(value == -1, NA_real_, value)]
 # remove lines where value is NA (in place)
 dat <- dat[!is.na(value), ]
 
-dat 
+dat
   # arrange(value) |>
   # group_by(region) |>
   # mutate(key = forcats::fct_reorder(key, value)) |>
 
-df =  dat |> arrange(value) |> tail(20) |> mutate(
+
-  value = value/1000000,
+
-    key = ifelse(key == "Democratic Republic of the Congo", "DRC", key))
+dumbbell(
+  dat |> arrange(value) |> tail(50) |> mutate(
+    value = value/1000000,
+    key = ifelse(key == "Democratic Republic of the Congo", "DRC", key)) |>
+    filter(region %in% c("Europe", "Americas")),
+  "value",
+  "region",
+  "key",
+  title = "% of HHs that reported open defecation as sanitation facility",
+  group_y_title = "Admin 1",
+  group_x_title = "Setting", point_size = 3, line_to_y_axis = T
+
+)
+
+
 bar(
-  df,
+  df =  dat |> arrange(value) |> tail(20) |> mutate(
+    value = value/1000000,
+  key = ifelse(key == "Democratic Republic of the Congo", "DRC", key)),
   x = "key",
   y = "value",
   group = "region",
   group_title = "Region",
-  facet = "region",
+  order = "grouped",
-  order = "grouped_y",
+  x_rm_na = T,
-  title = "Population of Global Regions in Million"
-) + scale_fill_visualizer_discrete(title_position = "top") + scale_color_visualizer_discrete()
-
-
-
-hbar(
-  df,
-  x = "key",
-  y = "value",
-  group = "region",
-  group_title = "Region",
-  facet = "region",
-  order = "none",
-  x_rm_na = T, 
   y_rm_na = T,
-  group_rm_na = T,   
+  group_rm_na = T,
-  title = "Population of Global Regions (in Million)"
+    flip = F,
-) + scale_fill_visualizer_discrete(title_position = "left") + scale_color_visualizer_discrete()
+  title = "Population of Global Regions in Million",
-  
+) +
-ggplot2::ggsave(
+theme_bar(flip = F, axis_text_x_angle = 45) +
-    "plot.svg",
+scale_color_visualizer_discrete() +
-    gg
+scale_fill_visualizer_discrete()
-  )
-  # ggplot2::theme(
-  #   #legend.direction = "horizontal",
-  #   legend.position = "top"
-  # )
-
-
-#
-#theme_bar(flip = F, axis_text_x_angle = 45) +
-#scale_color_visualizer_discrete() +
-#scale_fill_visualizer_discrete()

tests/testthat.R

@@ -0,0 +1,12 @@
+# # This file is part of the standard setup for testthat.
+# # It is recommended that you do not modify it.
+# #
+# # Where should you do additional test configuration?
+# # Learn more about the roles of various files in:
+# # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
+# # * https://testthat.r-lib.org/articles/special-files.html
+
+# library(testthat)
+# library(visualizeR)
+
+# test_check("visualizeR")

tests/testthat/test-bar.R

@@ -0,0 +1,125 @@
+# testthat::test_that("bar() function handles various edge cases", {
+#   # Setup minimal test data
+#   test_df <- data.frame(
+#     category =c("A", "B", "C"),
+#     value = c(10, 20, 30),
+#     group = c("X", "X", "Y"),
+#     facet_var = c("F1", "F1", "F2")
+#   )
+
+#   # Test 1: Basic functionality with all parameters
+#   testthat::expect_s3_class({
+#     bar(test_df, x = "category", y = "value", 
+#         position = "dodge", add_text = TRUE, flip = FALSE)
+#   }, "ggplot")
+
+#   # Test 2: Missing group parameter
+#   testthat::expect_s3_class({
+#     bar(test_df, x = "category", y = "value", facet = "facet_var")
+#   }, "ggplot")
+
+#   # Test 3: Missing facet parameter
+#   testthat::expect_s3_class({
+#     bar(test_df, x = "category", y = "value", group = "group")
+#   }, "ggplot")
+
+#   # Test 4: Identical group and facet
+#   testthat::expect_warning({
+#     bar(test_df, x = "category", y = "value", group = "facet_var", facet = "facet_var")
+#   }, "Using 'facet' for grouping")
+
+#   # Test 5: NA handling scenarios
+#   na_df <- data.table::data.table(
+#     category = c("A", "B", NA),
+#     value = c(10, NA, 30),
+#     group = c("X", NA, "Y")
+#   )
+  
+#   # Test 5a: NA removal enabled
+#   testthat::expect_silent({
+#     bar(na_df, x = "category", y = "value", group = "group",
+#         x_rm_na = TRUE, y_rm_na = TRUE, group_rm_na = TRUE)
+#   })
+
+#   # Test 5b: NA removal disabled
+#   testthat::expect_warning({
+#     bar(na_df, x = "category", y = "value", group = "group",
+#         x_rm_na = FALSE, y_rm_na = FALSE, group_rm_na = FALSE)
+#   }, "Converting df to data.table")
+
+#   # Test 6: Ordering scenarios
+#   # Test 6a: Natural order
+#   testthat::expect_equal(
+#     levels(bar(test_df, x = "category", y = "value", order = "none")$data$category),
+#     c("A", "B", "C")
+#   )
+
+#   # Test 6b: Ordered by y
+#   testthat::expect_equal(
+#     levels(bar(test_df, x = "category", y = "value", order = "y")$data$category),
+#     c("A", "B", "C")  # Should be ordered by value
+#   )
+
+#   # Test 7: Faceting edge cases
+#   # Test 7a: Single facet level
+#   single_facet <- data.table::data.table(
+#     category = c("A", "B"),
+#     value = c(10, 20),
+#     facet_var = c("F1", "F1")
+#   )
+#   testthat::expect_s3_class({
+#     bar(single_facet, x = "category", y = "value", facet = "facet_var")
+#   }, "ggplot")
+
+#   # Test 8: Text labeling thresholds
+#   small_values <- data.table::data.table(
+#     category = c("A", "B"),
+#     value = c(0.03, 0.04),  # Below default 0.05 threshold
+#     group = c("X", "Y")
+#   )
+#   plot_data <- bar(small_values, x = "category", y = "value", group = "group", add_text = TRUE)
+#   testthat::expect_true(all(is.na(plot_data$layers[[2]]$data$y_threshold)))
+
+#   # Test 9: Invalid parameter combinations
+#   testthat::expect_error(
+#     bar(test_df, x = "value", y = "category"),  # Reversed numeric/character
+#     "must be character or factor"
+#   )
+
+#   # Test 10: Facet/group interaction with insufficient data
+#   sparse_data <- data.table::data.table(
+#     category = "A",
+#     value = 10,
+#     group = "X",
+#     facet_var = "F1"
+#   )
+#   testthat::expect_s3_class({
+#     bar(sparse_data, x = "category", y = "value", group = "group", facet = "facet_var")
+#   }, "ggplot")
+# })
+
+# # Visual regression tests (requires vdiffr)
+# testthat::test_that("Visual appearance remains consistent", {
+#   test_df <- data.table::data.table(
+#     category = factor(c("A", "B", "C")),
+#     value = c(10, 20, 30),
+#     group = c("X", "X", "Y"),
+#     facet_var = c("F1", "F1", "F2")
+#   )
+
+#   # Basic plot
+#   basic <- bar(test_df, x = "category", y = "value")
+#   vdiffr::expect_doppelganger("basic-bar", basic)
+
+#   # Grouped+dodged
+#   grouped <- bar(test_df, x = "category", y = "value", group = "group")
+#   vdiffr::expect_doppelganger("grouped-dodged-bar", grouped)
+
+#   # Faceted
+#   faceted <- bar(test_df, x = "category", y = "value", facet = "facet_var")
+#   vdiffr::expect_doppelganger("faceted-bar", faceted)
+
+#   # Stacked
+#   stacked <- bar(test_df, x = "category", y = "value", group = "group", position = "stack")
+#   vdiffr::expect_doppelganger("stacked-bar", stacked)
+# })

vignettes/.gitignore

@@ -0,0 +1,4 @@
+*.html
+*.R
+
+/.quarto/

vignettes/bar_charts.Rmd

@@ -0,0 +1,57 @@
+---
+title: "Bar charts"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{Bar charts}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+Let's start by importing some data and running some data wrangling:
+```{r data-import}
+library(rio)
+library(data.table)
+dat <- import("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/11_SevCatOneNumNestedOneObsPerGroup.csv", data.table = TRUE)
+setDT(dat)
+
+# in all character columns, tranform empty string to NA
+vars_chr <- colnames(dat)[sapply(dat, is.character)]
+dat[, (vars_chr) := lapply(.SD, function(x) fifelse(x == "", NA_character_, x)), .SDcols = vars_chr]
+
+# in value, if -1 replace with NA
+dat[, value := fifelse(value == -1, NA_real_, value)]
+
+# remove lines where value is NA (in place)
+dat <- dat[!is.na(value), ]
+
+# kepp only top 20 values and divide data to get million units
+df <- dat[
+  !is.na(value), ][
+  order(value, decreasing = TRUE), ][
+  1:20, ][
+  , value := value/1000000, ][
+  , key := ifelse(key == "Democratic Republic of the Congo", "DRC", key)]
+```
+
+Now, let's see the defaults for a horizontal bar diagram without any grouping and ordering values from highest to smallest:
+
+```{r hbar}
+library(visualizeR)
+
+hbar(
+  df,
+  x = "key",
+  y = "value",
+  facet = "region",
+  order = "y",
+  title = "Top 20 countries by population (in Million)"
+)
+```
+
+Moving on to a vertical bar chart, with country facets and groups