z3tt

#### 1. Sign up at GitHub.com ################################################

## If you do not have a GitHub account, sign up here:
## https://github.com/join

# ----------------------------------------------------------------------------

#### 2. Install git ##########################################################

## If you do not have git installed, please do so: 

z3tt

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)

z3tt

library(ggplot2)

gm_2023 <- readr::read_csv("https://www.cedricscherer.com/data/gapminder-2023.csv")
pal <- c(Africa = "#00D9EE", Americas = "#4CF101", Asia = "#FF4670", Europe = "#FFE702", Oceania = "#CA4ADC")

# base plot
g <-
  ggplot(gm_2023, aes(x = gdp_pcap, y = life_exp, size = pop)) +
  geom_point(
    color = "white", 

z3tt

library(ggplot2)
library(treemapify)
library(ggtext)
library(prismatic)

owid_urban <- readr::read_csv("https://www.ggplot2-uncharted.com/data/hyde.csv")

treemap <- owid_urban |> 
  sf::st_drop_geometry() |> 
  filter(!is.na(continent)) |> 

z3tt

library(ggplot2)
library(patchwork)

# get photo
img <- magick::image_read("https://www.yan-holtz.com/img/team/YH_pic_square.png")

# retrieve lightness
c <- magick::image_channel(img)
img_df <- tibble::as_tibble(as.data.frame.table(drop(as.integer(c[[1]]))))
img_df <- dplyr::mutate(img_df, across(c(Var1, Var2), as.numeric))

z3tt

library(ggplot2)

value <- 7.3

ggplot() +
  # Add gap to bottom
  coord_radial(
    start = 4/3 * pi,  # 240°
    end = 2/3 * pi,    # 120°
    expand = FALSE

z3tt

library(tidyverse)

df_students <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-05-07/student_teacher_ratio.csv")

df_world_tile <- readr::read_csv("https://gist.githubusercontent.com/maartenzam/787498bbc07ae06b637447dbd430ea0a/raw/9a9dafafb44d8990f85243a9c7ca349acd3a0d07/worldtilegrid.csv") %>% 
  mutate(
    ## Namibias two-digit country code is handled as `NA` - let us fix that
    alpha.2 = if_else(name == "Namibia", "NA", alpha.2),
    ## We are going to split "Americas" into "North America" and "Sout America"
    region = if_else(region == "Americas", sub.region, region),

z3tt

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)

z3tt

## packages
library(ggplot2)
library(dplyr)
library(tidyr)
library(ggbraid)
library(colorspace)
library(owidR)
# plus ggtext via namespace

z3tt

library(tidyverse)
library(sf)
library(terra)
library(stars)
library(ggspatial)
library(systemfonts)
library(patchwork)

register_variant(
  name = "Input Mono Light",