charliejhadley

library(tidyverse)

fn_with_tidyeval_glue <- function(.data, target_column){
  
  chr_target_column <- quo_name(enquo(target_column))
  
  pvw_glue <- paste0("{", chr_target_column, "}_{.value}")
  
  .data %>%
    pivot_wider(

charliejhadley

---
title: "Untitled"
format: revealjs
---

First without heading

# First 1 heading

content

charliejhadley

/*-- scss:defaults --*/

$inverse-background-color: #272822;
$presentation-font-size-root: 28px;
$presentation-heading-color: #e10020;
$heading2Size: 55px;
$heading3Size: 45px;
$heading4Size: 35px;
$link-color: #e10020;

charliejhadley

# from tibble::as_tibble() focs 
tibble::as_tibble_col(
  list(c = "three", d = list(4:5)),
  column_name = "data"
)
#> # A tibble: 2 × 1
#>   data        
#>   <named list>
#> 1 <chr [1]>   
#> 2 <list [1]>

charliejhadley

library(tidyverse)

some_data <- tibble(
  messy_col = c('{"id":"1234567","bio":"John Smith, first-year undergraduate in Physics","username":"JSAstronaut"}',
                '{"id":"00303","bio":"Jo Smith, first-year undergraduate in Physics","username":"JSAstronaut"}')
)

some_data$messy_col %>% fromJSON()

# Target each column at once:

charliejhadley

library(tidyverse)
library(rnaturalearthdata)
library(sf)

country_sf <- countries110 %>% 
  st_as_sf()

ggplot() +
  geom_sf(data = country_sf,
          aes(fill = lastcensus,

charliejhadley

---
title: "{quarto}"
format: html
---

````{verbatim}
---
output: html_document
---
  

charliejhadley

---
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_hooks$set(force_not_eval = function(value) {
  value$eval <- FALSE
  value
}
)

charliejhadley

---
title: "Report"
output:
  word_document:
    reference_docx: template.docx
    html_document:
    toc: TRUE
    toc_depth: 2
    toc_float: TRUE
---

charliejhadley

---
title: "Untitled"
output:
  html_document:
    toc: TRUE
    toc_depth: 2
    toc_float: TRUE
---