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## packages | |
library(ggplot2) | |
library(dplyr) | |
library(tidyr) | |
library(ggbraid) | |
library(colorspace) | |
library(owidR) | |
# plus ggtext via namespace | |
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library(tidyverse) | |
library(sf) | |
library(terra) | |
library(stars) | |
library(ggspatial) | |
library(systemfonts) | |
library(patchwork) | |
register_variant( | |
name = "Input Mono Light", |
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library(dplyr) | |
library(forcats) | |
library(ggplot2) | |
library(palmerpenguins) | |
library(ggtext) | |
library(colorspace) | |
library(ragg) | |
url <- "https://raw.githubusercontent.com/allisonhorst/palmerpenguins/master/man/figures/lter_penguins.png" | |
img <- magick::image_read((url)) |
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library(tidyverse) | |
## data: | |
## https://www.kaggle.com/datasets/sudalairajkumar/daily-temperature-of-major-cities?resource=download | |
temp <- read_csv(here::here("city_temperature.csv")) | |
## select a few interesting city around the world | |
temp_selected <- | |
temp %>% | |
#filter(str_detect(City, "New York|London|Helsinki|Shanghai|Rio|Jakarta|Cairo|Canberra|Delhi|Capetown|Hong Kong|Reykjavik")) %>% |
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--- | |
title: "Gender Pay Gap: Dumbbell Plot (EU only)" | |
author: | |
- name: "Cédric Scherer" | |
url: www.cedricscherer.com | |
output: | |
distill::distill_article: | |
highlight: kate | |
code_folding: false | |
toc: true |
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#' Function to extract Jupiter colors as hex codes | |
#' | |
#' @param ... Character names of colors | |
#' | |
#' @examples | |
#' jupiter_colors() | |
#' jupiter_colors("petrol") | |
#' | |
#' @export | |
jupiter_colors <- function(...) { |
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library(tidyverse) | |
library(systemfonts) | |
mpg_sum <- mpg %>% | |
## just use 2008 data | |
dplyr::filter(year == 2008) %>% | |
## turn into lumped factors with capitalized names | |
dplyr::mutate( | |
manufacturer = stringr::str_to_title(manufacturer), | |
manufacturer = forcats::fct_lump(manufacturer, n = 10) |
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library(tidyverse) | |
library(systemfonts) | |
## data | |
## via https://projects.oregonlive.com/weather/temps/ | |
df <- | |
readr::read_csv("https://projects.oregonlive.com/weather/pdx_temps.csv") %>% | |
mutate(yday = lubridate::yday(date), | |
year = lubridate::year(date), | |
decade = year %/% 10 * 10, |
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set.seed(2021) | |
data <- tibble( | |
group = factor(c(rep("Group 1", 100), rep("Group 2", 250), rep("Group 3", 25))), | |
value = c( | |
## Group 1 | |
seq(0, 20, length.out = 100), | |
## Group 2 | |
c(rep(0, 5), rnorm(30, 2, .1), rnorm(90, 5.4, .1), rnorm(90, 14.6, .1), rnorm(30, 18, .1), rep(20, 5)), | |
## Group 3 |
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#' Download data to draw Berlin template map | |
#' @examples download_data_berlin() | |
download_data_berlin <- function() { | |
## SETUP --------------------------------------------------------------------- | |
## output dir for raw geo files | |
dir <- here::here("data-raw", "geo-raw") | |
if (!dir.exists(dir)) dir.create(dir, showWarnings = TRUE, recursive = TRUE) | |
## DISTRICTS ----------------------------------------------------------------- |
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