across_microflip_1.Rmd

---
title: "How to Use the _across()_ function"
subtitle: "mutate or summarize across many columns at once"  
author: 
  - "Peter Higgins"
date: '`r Sys.Date()`'
output:
  xaringan::moon_reader:
    lib_dir: libs
    css: xaringan-themer.css
    nature:
      highlightStyle: github
      highlightLines: true
      countIncrementalSlides: false
      ratio: 16:9
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(fig.width = 6, message = FALSE, warning = FALSE, comment = "", cache = FALSE, fig.retina = 3)

library(flipbookr)
library(xaringan)
library(xaringanthemer)
library(tidyverse)
library(medicaldata)
data <- medicaldata::blood_storage %>% as_tibble()
```

```{r xaringan-themer, include=FALSE, warning=FALSE}
library(xaringanthemer)
style_duo_accent(
  primary_color = "#00274C",
  secondary_color = "#FFCB05",
  inverse_header_color = "#FFFFFF"
)
```


### How to Use Across to Mutate many columns at once

#### This is awfully convenient

Format: <br>

mutate(across(logic.test = which variables, _function to apply()_))

Example 1: mutate numeric to factor

Some numeric variables having to do with Tumor volume and Stage should actually be factors.

---

```{r across1, include = FALSE, eval = FALSE}
data %>%
# select the variables needed
  select(Age, starts_with('T')) %>% 
# check out the variable types
  select(-starts_with('Time')) %>% 
# now do mutate across
  mutate(across(starts_with('T'), 
                factor)) 
# see how variable types have changed
# 
# Format:
# mutate(across(logic.test,function))
```

`r chunk_reveal("across1", 
    break_type = "auto", 
    title = "Mutate across (selected) numeric type to convert to factor type")`