166 lines
5.2 KiB
Markdown
166 lines
5.2 KiB
Markdown
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<!-- README.md is generated from README.Rmd. Please edit that file -->
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# visualizeR <img src="man/figures/logo.png" align="right" alt="" width="120"/>
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> What a color! What a viz!
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`visualizeR` proposes some utils to get REACH and AGORA colors,
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ready-to-go color palettes, and a few visualization functions
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(horizontal hist graph for instance).
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## Installation
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You can install the last version of visualizeR from
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[GitHub](https://github.com/) with:
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``` r
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# install.packages("devtools")
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devtools::install_github("gnoblet/visualizeR", build_vignettes = TRUE)
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```
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## Roadmap
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Roadmap is as follows:
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- [x] Add IMPACT’s colors
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- [x] Add all color palettes from the internal documentation
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- [ ] There remains to be added more-than-7-color palettes and black
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color palettes
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- [ ] Add new types of visualization (e.g. dumbbell plot)
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- [ ] Use examples
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- [ ] Add some ease-map functions
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- [ ] Add some interactive functions (maps and graphs)
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## Request
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Please, do not hesitate to pull request any new viz or colors or color
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palettes, or to email request any change
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(<guillaume.noblet@reach-initiative.org> or <gnoblet@zaclys.net>).
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## Colors
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Color palettes for REACH, AGORA and IMPACT are available. Functions to
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access colors and palettes are `cols_initiative()` or
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`pal_initiative()`. For now, the initiative with the most colors and
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color palettes is REACH. Feel free to pull requests new AGORA and IMPACT
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colors.
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``` r
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library(visualizeR)
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# Get all saved REACH colors, named
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cols_reach(unnamed = F)[1:10]
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#> white black main_grey main_red main_lt_grey main_beige
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#> "#FFFFFF" "#000000" "#58585A" "#EE5859" "#C7C8CA" "#D2CBB8"
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#> iroise_1 iroise_2 iroise_3 iroise_4
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#> "#DFECEF" "#B1D7E0" "#699DA3" "#236A7A"
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# Extract a color palette as hexadecimal codes and reversed
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pal_reach(palette = "main", reversed = TRUE, color_ramp_palette = FALSE)
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#> [1] "#58585A" "#EE5859" "#C7C8CA" "#D2CBB8"
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# Get all color palettes names
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pal_reach(show_palettes = T)
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#> [1] "main" "primary" "secondary" "two_dots"
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#> [5] "two_dots_flashy" "red_main" "red_main_5" "red_alt"
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#> [9] "red_alt_5" "iroise" "iroise_5" "discrete_6"
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#> [13] "red_2" "red_3" "red_4" "red_5"
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#> [17] "red_6" "red_7" "green_2" "green_3"
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#> [21] "green_4" "green_5" "green_6" "green_7"
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#> [25] "artichoke_2" "artichoke_3" "artichoke_4" "artichoke_5"
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#> [29] "artichoke_6" "artichoke_7" "blue_2" "blue_3"
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#> [33] "blue_4" "blue_5" "blue_6" "blue_7"
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```
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## Charts
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### Example 1: Bar chart, already REACH themed
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``` r
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library(visualizeR)
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library(palmerpenguins)
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library(dplyr)
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df <- penguins |>
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group_by(island, species) |>
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summarize(
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mean_bl = mean(bill_length_mm, na.rm = T),
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mean_fl = mean(flipper_length_mm, na.rm = T)) |>
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ungroup()
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# Simple bar chart by group
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bar_reach(df, mean_bl, island, species, percent = FALSE, x_title = "Mean of bill length")
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```
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<img src="man/figures/README-example-bar-chart-1.png" width="100%" />
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``` r
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# Using another color palette
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bar_reach(df, mean_bl, island, species, percent = FALSE, palette = "artichoke_3", legend_rev = TRUE)
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```
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<img src="man/figures/README-example-bar-chart-2.png" width="100%" />
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### Example 2: Point chart, already REACH themed
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At this stage, `point_reach()` only supports categorical grouping colors
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with the `group` arg.
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``` r
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# Simple point chart
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point_reach(penguins, bill_length_mm, flipper_length_mm)
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```
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<img src="man/figures/README-example-point-chart-1.png" width="100%" />
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``` r
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# Point chart with grouping colors, greater dot size, some transparency, reversed color palette
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point_reach(penguins, bill_length_mm, flipper_length_mm, island, alpha = 0.6, size = 3, reverse = TRUE)
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```
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<img src="man/figures/README-example-point-chart-2.png" width="100%" />
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``` r
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# Using another color palettes
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point_reach(penguins, bill_length_mm, flipper_length_mm, island, palette = "artichoke_3")
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```
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<img src="man/figures/README-example-point-chart-3.png" width="100%" />
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## Maps
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``` r
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# Add indicator layer
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# - based on "pretty" classes and title "Proportion (%)"
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# - buffer to add a 10% around the bounding box
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map <- add_indicator_layer(
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indicator_admin1,
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opn_dfc,
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buffer = 0.1) +
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# Layout - some defaults - add the map title
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add_layout("% of HH that reported open defecation as sanitation facility") +
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# Admin boundaries as list of shape files (lines) and colors, line widths and labels as vectors
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add_admin_boundaries(
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lines = list(line_admin1, border_admin0, frontier_admin0),
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colors = cols_reach("main_lt_grey", "dk_grey", "black"),
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lwds = c(0.5, 2, 3),
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labels = c("Department", "Country", "Dominican Rep. frontier"),
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title = "Administrative boundaries") +
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# Add text labels - centered on admin 1 centroids
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add_admin_labels(centroid_admin1, ADM1_FR_UPPER) +
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# Add a compass
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add_compass() +
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# Add a scale bar
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add_scale_bar() +
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# Add credits
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add_credits("Admin. boundaries. : CNIGS \nCoord. system: GCS WGS 1984")
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```
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