The RStudio IDE

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<div class="footer-small"><span>https://github.com/mjfrigaard/csuc-data-journalism</div>

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# The RStudio IDE
#.fancy[using RStudio to manage code, data, and files]

<br>

.large[by Martin Frigaard]

Written: September 30 2021

Updated: November 30 2021

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<br><br><br><br><br>[Created using the "λέξις" theme](https://jhelvy.github.io/lexis/index.html#what-does-%CE%BB%CE%AD%CE%BE%CE%B9%CF%82-mean)
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# The RStudio IDE

### Managing your code, data, and files with RStudio

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## Change RStudio's Default Settings

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#### Click on **Tools** > **Global Options...**

#### - We want to uncheck "*Restore .RData into work space at start up*"

#### - We also want to make sure we change "*Save work space to .Rdata on exit*" to "*Never*"

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# Customize RStudio

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### Code
### Console
### Appearance
### Pane Layout
### R Markdown
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# Code Editing

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## - Auto indent?

## - Continue comment lines?

## - Save R scripts before sourcing?

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# Code Display

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## - Margins?

## - Scrolling?

## - Rainbow parentheses?

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# Code Saving

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## - Cursor position?

## - Line endings?

## - Text encoding?

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# Code Completion

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## - Insert parentheses?

## - Insert spaces?

## - Completion delay setting?

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# Code Diagnostics

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## - Check your R Code?

## - Check other languages?

## - How long?

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# Console

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## - Display?

## - Debugging?

## - Other?

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# Appearance

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#### - RStudio theme?

#### - Zoom?

##### - Also hold `⌘` and press `+` on macOS

##### - Also hold `ctrl` and press `+` on Windows

#### - Font?

#### - Editor theme?

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## Pane layout

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#### - Source?

#### - Console?

#### Combining pane elements?

##### - Plots, Connections, Build, VCS, Presentation

##### - Files, Packages, Help, Tutorial, Viewer

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# Pane layout view

Standard layout options

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# Pane layout: add column

#### Two screens?

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*add a Source column and rearrange the panes*

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# Pane layout: add column view

Now you see **Source**, **Tutorial**, and **Console** panes on a single screen!

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# RStudio Projects

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# Why RStudio Projects?

### Keep track of all your files with RStudio project files (`.Rproj`).

####  Self contained

> Using R projects keeps track or your current working directory!

#### Project orientated

> .Rproj files make bundling and shipping files and folders easier!

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# Why RStudio Projects?

### Keep track of all your files with RStudio project files (`.Rproj`).

#### Avoid removing all the files

**Don't do this!**

```r
rm(list = ls())
```

> `.Rproj` files keep all the files associated with a project together — input data, R scripts, analytic results, figures.

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# Creating RStudio project in existing folder

#### Click on *'Project: (None)'* > *'New Project'*

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# Creating RStudio project in existing folder

#### Click on *'Browse* > *'Create Project'*

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# Creating RStudio projects in new folder

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#### Click on .blue[Project: (None)] > .blue[New Project]

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#### Select project type

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# Creating RStudio projects in new folder

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#### Create new folder name

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#### Choose parent folder

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# Creating RStudio projects in new folder

#### If you have Git installed, select *'Create a git repository'*

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# Creating RStudio projects in new folder

#### Check for new project name & *Git* pane

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# Folder Structure

- separate raw and cleaned data

- keep documents and code separate

- keep figures separate

- name files appropriately (preferably 2 digit prefix)

- structure is reusable and easy to understand

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# Folder structure

#### Adapted from from '[Good enough practices in scientific computing](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005510)'

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# Naming things

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# Naming files

### File names should be:

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#### 1. human readable -> (makes sense)

#### 2. machine readable -> (regex)

#### 3. sort/order well -> (ISO 8601 date)

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##### 2020-10-12-270-301-**central-lab-metrics**.csv

##### 2020-10-12-**270-301**-central-lab-metrics.csv

##### **2020-10-12**-270-301-central-lab-metrics.csv

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# Naming files*

We can perform regular expression searches for files like this:

*Find 270-301 files*

```r
grepl(pattern = "270-301", 
      x = "2020-10-12-270-301-central-lab-metrics.csv")
```

```
  [1] TRUE
```

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> *Adapted from [Jenny Byran's slides](https://speakerdeck.com/jennybc/how-to-name-files)

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# Naming files*

### Also acceptable: Logical order and underscores `_`

```r
files
```

```
  [1] "01.0_import_lab-data.R"  "02.0_wrangle_lab-data.R"
  [3] "03.0_eda_lab-data.R"
```

```r
stringr::str_split_fixed(string = files, pattern = "_", 3)
```

```
       [,1]   [,2]      [,3]        
  [1,] "01.0" "import"  "lab-data.R"
  [2,] "02.0" "wrangle" "lab-data.R"
  [3,] "03.0" "eda"     "lab-data.R"
```

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> *Adapted from [Jenny Byran's slides](https://speakerdeck.com/jennybc/how-to-name-files)

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# File paths

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# Use relative rather than absolute file paths

### **Absolute paths** are specific to a system

`/project-name/data` -> absolute path in macOS

`\\project-name\\data` -> absolute path in Windows

### **Relative paths** are specific to a folder

`project-name/data` -> relative path in macOS

`project-name\\data` -> relative path in Windows

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# Or use the `here` package

### The `here::set_here()` function solves a lot of file path problems (*especially if you're not using R projects*)

```r
library(here)
here::set_here(".")
list.files(all.files = TRUE, pattern = "here")
```

```
  [1] ".here"
```

This creates a `.here` file (similar to `.Rproj` files)

As long as the `.here` file stays in the referenced folder, you can include simply include `here::here()` in the top of your code files.

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# Terminal pane

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#### Learn a handful of command-line tools to make life easier

`cd`, `pwd`, `mkdir`, `rm`, `ls`, etc.

#### RStudio comes with a Terminal pane for quick access to the command-line

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# Getting help

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R comes with a *ton* of accessible help files

```r
?read.csv
```

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## Getting help online

R also help an incredible community! Click on the links below to see some of the common places for Q & A.

### 1) [Dedicated forum on RStudio Community](https://community.rstudio.com/)

### 2) [Questions tagged R on StackOverflow](https://stackoverflow.com/questions/tagged/r)

### 3) [Twitter topics with #rstats hashtag](https://twitter.com/hashtag/rstats)

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## Asking good questions (reproducible examples)

You'll get better results if you ask a question with a reproducible example. The [`reprex` package](https://github.com/tidyverse/reprex) was designed to help you create one!

```r
install.packages("reprex")
library(reprex)
```

### *Use the RStudio Addin to create a reproducible example from code you've copied onto your clipboard!*

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# Reprex Addin 1

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1. Copy code
2. Select .blue[Addin] > .blue[Render selection]

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# Reprex Addin 2

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1. Copy code
2. Select .blue[Addin] > .blue[Render selection] 
3. Wait for console  
4. Paste reprex

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# Reprex + datapasta

### To copy + paste actual data in a reproducible example, try `datapasta`!

https://reprex.tidyverse.org/articles/articles/datapasta-reprex.html

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Learn more about R best practices:

1. [R for Data Science](https://r4ds.had.co.nz/)

2. [Tidyverse](https://www.tidyverse.org/)

3. [RViews Community Blog](https://rviews.rstudio.com/)

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# THANK YOU!

## Feedback

@mjfrigaard on Twitter and Github

mjfrigaard@gmail.com