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dat <- structure(list(Move = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 

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##----------------------------------------------------------------------------------------------------------##
##  Cedric Scherer (cedricphilippscherer@gmail.com)                                                         ##
##  Function for a custom ggplot theme                                                                      ##
##  2017-05-27                                                                                              ##
##----------------------------------------------------------------------------------------------------------##

library(ggplot2)

if ("extrafont" %in% rownames(installed.packages()))
{

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## from Hugo Toscano: https://github.com/toscano84/TidyTuesday/blob/master/Week23/TT_week23_fastfood.R

"%||%" <- function(a, b) {
  if (!is.null(a))
    a
  else
    b
}

geom_flat_violin <-

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``` r
library(tidyverse)
library(raster)
library(sf)
#> Linking to GEOS 3.6.1, GDAL 2.2.3, PROJ 4.9.3

oceans <- 
  rnaturalearth::ne_download(scale = 10, 
                             category = "physical", 
                             type = "ocean",

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library(tidyverse)
library(lubridate)

locations <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-06-23/locations.csv')

movement <- locations %>% 
  filter(study_site != "Hart Ranges") %>% 
  mutate(
    season = fct_rev(season), # reverse seasons
    longitude = round(longitude, 2), # round long, lat to reduce number of points

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library(tidyverse)
library(patchwork)

df <- tibble(x = 1, y = 1)

g <- ggplot(df, aes(x, y)) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  coord_cartesian(clip = "off") +
  theme_void() +

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library(shiny)
library(tmap)

data(World)
world_vars <- setdiff(names(World), c("iso_a3", "name", "sovereignt", "geometry"))


ui <- fluidPage(
  tmapOutput("map"),
  selectInput("var", "Variable", world_vars)

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library(shiny)
library(tmap)
library(tidyverse)
library(fullPage)

data(World)
world_vars <- setdiff(names(World), c("iso_a3", "name", "sovereignt", "geometry"))

ui <- pagePiling(
    sections.color = c('#ebebeb', '#f1f1f1'),

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library(tidyverse)
library(gganimate)
library(systemfonts)

df_mac_raw <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-12-22/big-mac.csv')

df_mac <- 
  df_mac_raw %>% 
  mutate(year = lubridate::year(date)) %>% 
  dplyr::select(date, year, iso_a3, currency_code, name, local_price, 

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library(tidyverse)
library(igraph)
library(ggraph)

df <- readRDS("data.Rds")

graph <- graph_from_data_frame(df)

sorting <- c(25, 24, 1, 2, 3, 4, 5, 6, 7, 8, 26, 27, c(9:23))