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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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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),

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##----------------------------------------------------------------------------------------------------------##
##  Cedric Scherer ([email protected])                                                         ##
##  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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#### 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: