Lesson5.Rmd

---
params:
  lesson: "Lesson 5"
  title: "Turning code into reproducible documents with `Rmarkdown`"
  functions: "`here`, `summarise`,  `set_here`, `dr_here`"
  packages: "`here`, `dplyr`, `readr`,`rmarkdown`"      
  # end inputs ---------------------------------------------------------------
header-includes: \usepackage{float}
always_allow_html: yes
output:
  html_document:
    code_folding: show
---
  
```{r, setup, echo = FALSE, cache = FALSE, include = FALSE}
options(width=100)
knitr::opts_chunk$set(
  eval = FALSE, # run all code
  echo = TRUE, # show code chunks in output 
  tidy = TRUE, # make output as tidy
  message = FALSE,  # mask all messages
  warning = FALSE, # mask all warnings 
  comment = "",
  tidy.opts=list(width.cutoff=100), # set width of code chunks in output
  size="small" # set code chunk size
  )
```
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<!-- install packages -->
```{r, load packages, eval=T, include=T, cache=F, message=F, warning=F, results='hide',echo=F}
packages <- c("ggplot2","ggthemes","dplyr","tidyverse","zoo","RColorBrewer","viridis","plyr")   
if (require(packages)) {
    install.packages(packages,dependencies = T)
    require(packages)
    # load tvthemes
    devtools::install_github("Ryo-N7/tvthemes")
}
lapply(packages,library,character.only=T)  
```

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# `r paste0(params$lesson,": ",params$title)`    
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Functions for `r params$lesson`  
`r params$functions`    
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Packages for `r params$lesson`          
`r params$packages`        
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# Agenda

Create reproducible HTML, PDF, and Word documents from R using `RMarkdown`.   
* **[Download the `RMarkdown` template (right click > Save As)](https://github.com/darwinanddavis/EmoRyCodingClub/raw/master/Lesson5_rmd.Rmd).** Save this in the same folder as your coding club files. The file should have a *.Rmd* extension, e.g. **Lesson5_rmd.Rmd**.        
* Open `RStudio` and run the following code to install the necessary packages:

```{r, eval=F}
packages <- c("pacman","rmarkdown", "here")  
install.packages(packages,dependencies = T)
lapply(packages,require,character.only=T)  
```
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<!--  end yaml template------------------------------------------------------- -->
  
# Do First      

Recreate the below plot using the larger NYC Airbnb dataset. Here's the code to add the title and labels.  

```{r,eval=F}
url <- "http://data.insideairbnb.com/united-states/ny/new-york-city/2021-04-07/data/listings.csv.gz"
nyc_full <- readr::read_csv(url) # reads in data

ttl <- "NYC Airbnb availability"
subttl <- "for room types across neighbourhoods"
xlab <- "Availability of property in next 30 days"
ylab <- "Count"

# append this to your ggplot function with a `+`
labs(title = ttl,
     subtitle = subttl,
     x = xlab,
     y = ylab) 
```

```{r,echo=F,eval=T,cache=T}
url <- "http://data.insideairbnb.com/united-states/ny/new-york-city/2021-04-07/data/listings.csv.gz"
nyc_full <- readr::read_csv(url) # reads in data
```

```{r, echo=F, eval=T, out.width="100%"}
ttl <- "NYC Airbnb availability"
subttl <- "for room types across neighbourhoods"
xlab <- "Availability of property in next 30 days"
ylab <- "Count"
my_theme <- theme_tufte()

names(nyc_full)

# glimpse(nyc_full)  
nyc_full_ <- nyc_full %>% dplyr::filter(availability_30 > 0)

ggplot() +
  geom_bar(data = nyc_full_, 
           mapping = aes(x = availability_30,
       color=neighbourhood_group_cleansed,
       fill=neighbourhood_group_cleansed), show.legend = F) +
  facet_grid(room_type ~ neighbourhood_group_cleansed) +
  labs(title = ttl,
       subtitle = subttl,
       x = xlab,
       y = ylab) +
  my_theme

```
  
# Setting your working directory  
Using `here` to set your working directory  
```{r}
require(here) # load the here package if not already
set_here() # set current working directory 
dr_here() # print current working directory where .here is located
```

**Example 1**    
1. Create a folder in your local directory called **'lookhere'**.  
2. Open a new file in TextEdit (Mac) or Notepad (Windows), type in something like " _We found the here file!_ ", then save the file as **"heretest.txt"**.       
```{r}
require(readr)  
# example 1
list.files() # print files in your current working dir. the 'heretest.txt' file is not here, but one folder below in the new 'lookhere' folder
here("lookhere","heretest.txt") # using here to forage for the file
here("lookhere","heretest.txt") %>% read_lines # print the contents in R
```
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**Example 2**  
1. Create another folder within the **lookhere** folder called **lookheretoo**    
2. Create another .txt file called **heretesttoo.txt** and save it.    
```{r}
# example 2
# create two folders 
folder1 <- "lookhere"
folder2 <- "lookheretoo"
file <- "heretesttoo.txt"
# navigate to the /lookheretoo folder and open the heretesttoo file using 'here'
here(folder1,folder2,file) %>% read_lines 
read_lines(here(folder1,folder2,file)) # non-tidy version

```
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Why is `here` useful?    
  * You can step through sub folders by defining them individually as function inputs  
  * You can user define these subfolders as variables at the beginning of your `R` script and refer to them throughout your script without pasting, e.g. `paste(folder1,folder2,sep="/")`.      

# Creating an `R` project (`Rproj`) file    

**Option 1:** Create an RProject new directory:  
* _File > New Project_  
* _Create New Project_  
* Choose a name for your RProj folder. Fill out _Directory name:_ (make it machine-friendly, i.e. no spaces)   
* Choose a place for the RProj to live. _Browse_  
* Select _Open in new session_  

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**Option 2:** If you already have a folder *just* for Emory Coding Club:   
* _File > New Project_      
* _Existing directory > Browse_  
* Select _Open in new session_    

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* Open the 'Lesson5_rmd.Rmd' file within this project and save it as 'Lesson5_rmd.Rmd'.        
* Open another _.R_ file within this project and save it.    
* Now repeat the above steps with a second _Rproj_ file. Save this in another directory somewhere on your computer.      
* Now check the working directory within both _Rproj_ files using the `here` package. What do you see?         

# Navigating the `Rmarkdown` interface    

Have a look through each section of the raw `.Rmd` file to see what the code does. You'll be using this template to create your own files, such as creating personal notes for future sessions in this coding club.      

<!-- ----------------------- image --------------------------- -->
<div align="center"; text-align:center>
  <img src="img/rmd.jpg" style=width:100%>
</div>
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# Exercises  

* Knit an HTML document. Use the hotkey `Cmd/Ctrl + Shift + K`    
* Create a 'EmoRy Coding Club notes' document      
* Create your own parameter in the yaml     
* Create a code chunk that shows the code and output, but masks any warnings  
* Create a code chunk with a plot of your own data or from the Airbnb data. Here's the NYC Airbnb data:    
```{r}
# large Airbnb dataset (106 cols)
require(readr,dplyr)

url <- "http://data.insideairbnb.com/united-states/ny/new-york-city/2021-04-07/data/listings.csv.gz"

nyc_full <- read_csv(url) # reads in data
nyc_full %>% glimpse
```
* Change the above figure dimensions in the knitted document     
* Create a table with the title in bold, one of the columns set to right justified text, and one of the rows italicised   
* Write an inline equation and an indented equation     


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