visualizeR

What a color! What a viz!

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).

Installation

You can install the last version of visualizeR from GitHub with:

# install.packages("devtools")
devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)

Roadmap

Roadmap is as follows:

Add IMPACT’s colors
Add all color palettes from the internal documentation
There remains to be added more-than-7-color palettes and black color palettes
Add new types of visualization (e.g. dumbbell plot)
Use examples
Add some ease-map functions
Add some interactive functions (maps and graphs)

Request

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).

Example 1: extracting 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.

library(visualizeR)

# Get all saved REACH colors, named
cols_reach(unnamed = F)[1:10]
#>        white        black    main_grey     main_red main_lt_grey   main_beige 
#>    "#FFFFFF"    "#000000"    "#58585A"    "#EE5859"    "#C7C8CA"    "#D2CBB8" 
#>     iroise_1     iroise_2     iroise_3     iroise_4 
#>    "#DFECEF"    "#B1D7E0"    "#699DA3"    "#236A7A"

# Extract a color palette as hexadecimal codes and reversed
pal_reach(palette = "main", reversed = TRUE, color_ramp_palette = FALSE)
#> [1] "#58585A" "#EE5859" "#C7C8CA" "#D2CBB8"

# Get all color palettes names
pal_reach(show_palettes = T)
#>  [1] "main"            "primary"         "secondary"       "two_dots"       
#>  [5] "two_dots_flashy" "red_main"        "red_main_5"      "red_alt"        
#>  [9] "red_alt_5"       "iroise"          "iroise_5"        "discrete_6"     
#> [13] "red_2"           "red_3"           "red_4"           "red_5"          
#> [17] "red_6"           "red_7"           "green_2"         "green_3"        
#> [21] "green_4"         "green_5"         "green_6"         "green_7"        
#> [25] "artichoke_2"     "artichoke_3"     "artichoke_4"     "artichoke_5"    
#> [29] "artichoke_6"     "artichoke_7"     "blue_2"          "blue_3"         
#> [33] "blue_4"          "blue_5"          "blue_6"          "blue_7"

Example 2: Bar chart, already REACH themed

library(visualizeR)
library(palmerpenguins)
library(dplyr)

df <- penguins |> 
  group_by(island, species) |> 
  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
bar_reach(df, mean_bl, island, species, percent = FALSE, x_title = "Mean of bill length")


# Using another color palette
bar_reach(df, mean_bl, island, species, percent = FALSE, palette = "artichoke_3", legend_rev = TRUE)

Example 3: Point chart, already REACH themed

At this stage, point_reach() only supports categorical grouping colors with the group arg.


# Simple point chart
point_reach(penguins, bill_length_mm, flipper_length_mm)


# Point chart with grouping colors, greater dot size, some transparency, reversed color palette
point_reach(penguins, bill_length_mm, flipper_length_mm, island, alpha = 0.6, size = 3, reverse = TRUE)


# Using another color palettes
point_reach(penguins, bill_length_mm, flipper_length_mm, island, palette = "artichoke_3")

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