--- title: "1.1 Getting Started with R and RStudio" --- ```{r} #| label: setup #| include: false knitr::opts_chunk$set( echo = TRUE, message = FALSE, warning = FALSE, fig.width = 6, fig.height = 3.6, fig.align = "center", dpi = 120, error = TRUE, fig.path = "_figs/getting-started/" ) library(tidyverse) ``` Install R and RStudio, run a script, and open a project so R can find your files. ## 1. Install R, then RStudio R is the language. RStudio (Posit) is an editor that makes R easier to use. Install them in this order: 1. [R](https://www.r-project.org/) for Windows, macOS, or Linux. 2. [RStudio Desktop](https://posit.co/download/rstudio-desktop/). RStudio will not work properly if R is not installed first. We will work in RStudio, not in the older R application that installs with R. R was designed for statistics. It is free, it is built around packages, and it is a good language for analysis you can rerun. Python is also widely used in data science. This course uses R. --- ## 2. The RStudio Layout When you open RStudio, you will typically see several panes: - the **console**, where R evaluates code immediately - a **source** editor, where you write scripts and documents you want to keep - an **environment / history** pane, which lists objects in the current session - a **files / plots / packages / help** pane The source pane stays closed until you open or create a file. A few habits that save time: - The **Files** tab is a limited file manager. You can open, copy, and delete files, and you can set the console working directory from **More**. - The **Environment** tab shows objects you have created in this session. - The **Help** tab shows documentation. You can also type `help(mean)` or `?mean` in the console. --- ## 3. Configure RStudio Once Open **Tools → Global Options… → General**. Under **Workspace**: - uncheck **Restore .RData into workspace at startup** - set **Save workspace to .RData on exit** to **Never** If RStudio restores yesterday's objects, you can accidentally use results you no longer have code for. That looks convenient and is bad for reproducibility. Other useful options: - **Code → Editing**: turn on soft wrapping - **Appearance**: choose a font size you can read --- ## 4. The Console The console is the pane with the `>` prompt. Type: ```{r} #| label: chunk-1 1 + 1 ``` and press Enter. R prints: ```{r} #| label: chunk-2 #| eval: false # [1] 2 ``` The `[1]` is not part of the answer. It is the index of the first element R is showing you. The up and down arrow keys cycle through recent console commands. That is useful when you mistype a line. R is a calculator: ```{r} #| label: chunk-3 3 * 7 9 / 3 (3 + 5) * 6 3 ^ 2 ``` `%%` is remainder after integer division: ```{r} #| label: chunk-4 1 %% 2 # 1 4 %% 2 # 0 ``` The console is useful for short experiments. It is a poor place to keep your work. When you close RStudio, console history is not a script. If a command is incomplete, R shows a `+` prompt and waits. Press **Esc** to get back to `>`. --- ## 5. Scripts A **script** is a text file of R code, usually with a `.R` extension. Create one with **File → New File → R Script**. Type this into the script: ```{r} #| label: chunk-5 x <- 10 x * 2 ``` Place the cursor on a line and run it with **Ctrl+Enter** (Windows/Linux) or **Cmd+Enter** (macOS). You can also click **Run**. The code is sent to the console, and the console shows the result. A useful habit is: > Type in a script. Run from the script. Treat the console as a scratch pad. Save the script. You can reopen it in a later session. Lab 1 is mostly a script (`lab01.R`). Section G is a short Quarto file; see note **1.5**. --- ## 6. Comments R ignores anything after `#` on a line: ```{r} #| label: chunk-6 # This line is only for humans. x <- 10 # store 10 in x ``` Comments are how you explain *why* you wrote something, not how you hide code you might need later. --- ## 7. Assignment We store a value with `<-`: ```{r} #| label: chunk-7 greeting <- "Hello" greeting ``` In this course: - `<-` stores a value in an object - `=` names an argument inside a function call, for example `mean(x, na.rm = TRUE)` R is **case sensitive**. `x` and `X` are different objects. `TRUE` is not `true`. `sum()` is not `Sum()`. --- ## 8. Getting Help Almost every function has a help page: ```{r} #| label: chunk-8 help(mean) ?mean help("%%") ``` `??topic` searches help pages. Adding `"in R"` to a web search is often faster than memorizing function names. --- ## 9. Organize Your Files Do not keep every course file on the Desktop with names like `file 1`. You will not be able to tell R where the data is, and other people will not be able to rerun your work. Create one folder for the course, for example `data_612`, and keep lecture work and assignments in separate subfolders. Use **snake_case** names. Avoid spaces and special characters. data_612/ students.csv lab01.R data/ students.csv extra/ R/ output/ assignments/ lab_01/ Inside a project, a common pattern is: - `R/` for `.R` scripts - `data/` for files you import - `output/` for files you write You do not need every folder every week. You do need a place that is not a pile. Back up that folder to Google Drive or another cloud service. A crashed laptop is a common way to lose a course. --- ## 10. Where Are Your Files? R does not search your whole computer for a file. It looks in one folder, called the **working directory**, unless you tell it a path. ```{r} #| label: chunk-9 getwd() ``` That path is "where R is standing." In RStudio you can also read it just under the Console tab. A better habit for the course is **File → New Project**. An RStudio project pins the working directory to that folder. Do not nest one project inside another. Note **1.3** is the full treatment: relative vs absolute paths, `.` and `..`, choosing an import function, and saving results. --- ## 11. Errors Are Information If R cannot run a line, it prints an error. Read it from the top. Common first-week mistakes include: - a missing quotation mark - a missing parenthesis - running `install.packages(ggplot2)` without quotes - calling a function from a package you have not loaded - looking for a file that is not in the working directory You do not need to memorize every error. You do need to read it. --- ## 12. What to Do Next Once R and RStudio are installed and you can run a line from a script, continue with: - **1.2** R Packages and the Tidyverse - **1.3** Working with Files and Paths - **1.4** Introduction to R Concepts - **1.5** R Markdown and Quarto - **Lab 1**, which asks you to predict what R will do *before* you run the code. Work in a `.R` script.