riinuots

library(tidyverse)
one = tibble(x    = c(2, 4, 3, 2.75, 2.75, 3.25, 3.25),
             y    = c(1, 1, 6, 0,    1,    1,    0),
             group = c(rep("#005a32", 3), rep("#543005", 4)))

two = tribble(~x,   ~y,
              2.7,  2,
              3,    3,
              3.4,  1.6,
              3.5,  2.5,

riinuots

library(tidyverse)
one = tibble(x    = c(2, 4, 3, 2.75, 2.75, 3.25, 3.25),
             y    = c(1, 1, 6, 0,    1,    1,    0),
             group = c(rep("#005a32", 3), rep("#543005", 4)))

two = tribble(~x,   ~y,
              2.7,  2,
              3,    3,
              3.4,  1.6,
              3.5,  2.5,

riinuots

# Part 1/3 of #HealthyR #rstats Season's Greetings
library(tidyverse)
one = tibble(x    = c(2, 4, 3, 2.75, 2.75, 3.25, 3.25),
             y    = c(1, 1, 6, 0,    1,    1,    0),
            group = c(rep("#005a32", 3), rep("#543005", 4)))
              
ggplot(one, aes(x, y, fill = group)) +
  geom_polygon()

riinuots

library(tidyverse)
library(palmerpenguins)

penguins %>% 
  ggplot(aes(species, flipper_length_mm, fill = sex, size = body_mass_g)) +
  geom_jitter(shape = 21, colour = "grey", alpha = 0.8) +
  scale_fill_viridis_d() +
  theme_bw()

riinuots

---
title: "Reticulate example"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
	echo = TRUE,
	message = FALSE,
	warning = FALSE

riinuots

# R script to split up the recruitment PDF that we get from HR
# Riinu Pius 30/07/2020
# Script figures out where each new application starts, extracts the candidates last name
# then creates a separate PDF for each candidate: Lastname.pdf
library(tidyverse)
library(pdftools)


pdf_filename = "Candidate report (n) Job Title vacancy 123456.pdf"
# Change to "\" if on Windows:

riinuots

---
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r message=FALSE, warning=FALSE}
library(tidyverse)

riinuots

---
header-includes:
  - \usepackage{float}
  - \floatplacement{table}{!hb}
  - \floatplacement{figure}{!hb}
---

riinuots

library(tidyverse)
library(rnaturalearth)
library(sf)
theme_set(theme_void())

world_map = ne_countries(scale = "medium", returnclass = "sf") %>% 
  st_transform(crs = "+proj=moll") %>% 
  filter(sovereignt != "Antarctica")

healthyr_iso= c("GB", "EE", "GH")

riinuots

library(shiny)
library(tidyverse)
library(gapminder)

# User Interface
ui <- basicPage(
  
  plotOutput(outputId = "myplot")
  
)