Rmd file containing a function which returns Rmarkdown-friendly output including headers for organization. Useful if you have multiple outcomes/explanatory variables/data sets that you want to report identical analyses on.

headerFunsEx.Rmd

---
title: "Outputting Headers within Functions"
author: "Katherine Hoffman"
date: "3/20/2019"
output:
  html_document:
    toc: true
    toc_float:
      collapsed: false
      smooth_scroll: false
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = F, results="asis", warning=F, message=F)
library(tidyverse)
dat1 <- data.frame(x=rnorm(50),y=rnorm(50))
dat2 <- data.frame(x=rnorm(250),y=rnorm(250))
```

```{r}
# Make many mini functions
xDistFun <- function(dat){
  ggplot(dat, aes(x)) + geom_histogram(fill="blue")}

yDistFun <- function(dat){
  ggplot(dat, aes(y)) + geom_histogram(fill="red")}

xRegFun <- function(dat){
  lm(y ~ x, data=dat) %>% broom::tidy() %>% knitr::kable()}

# Organize functions into a repetitive analysis
runManyFuns <- function(dat){
  title <- deparse(substitute(dat))
  h1 <- "Distributions"
  out1 <- list(xDistFun(dat = dat), yDistFun(dat = dat))
  h2 <- "Regression Model"
  out2 <- xRegFun(dat = dat)
  headers <- c(h1, h2)
  out <- list(out1, out2)
  cat(paste0("\n#Data: ", title, "\n"))
  for (i in 1:length(headers)){
    cat(paste0("\n##", headers[i], "\n"))
    print(out[i])
  }
}
```

```{r}
# Run analysis on different data sets, outcomes, etc.
runManyFuns(dat1)
runManyFuns(dat2)
```