Lecture 0

Author

Lifeng Ren

Published

October 7, 2023

1 Set Up

Let us firstly set up our R programming environment and have an overview of Rstudio.

1.1 Install R and Rstudio

Please follow the instruction of this link to download and install R and Rstudio.

1.2 What is R and Rstudio

R is a language and environment for statistical computing and graphics.
RStudio is an integrated development environment for R.

1.3 Go over the Interface of Rstudio

There are four main windows in Rstudio.

The Console window

The Source window: Here is place we normally write our code.

The Environment / History / Connections / Tutorial window: Right now it is empty, because we have not loaded any data yet. Here is the place, we can see some data frames, functions, and vectors.

The Files / Plots / Packages / Help / Viewer window: You can see your file path, plots, etc. in this window.

2 Code in R

We will talk more about coding in R in the next few days, and there are lot of things to be care of for any programming language, such us:

Workflows set up
Version Control
Inline Comments
…

Each single topic worth a ton of time to study. However, I will only talk about some basics of each part. And I really wish you can code like a pro.

So, let us get familiar with the R Script and R Markdown first, and go over some coding conventions.

2.1 R script

You always need yourself and your collaborator know what is your script about. So, please define some basic information for your R script. The following is an example I use.

Code

#____________________________
#  Script Information----
#____________________________
##
## Script Title: Introduction to R Statistical Software
##
## Task: Lecture 0
##
## Author: Lifeng Ren
##
## Date Last Modified: 2023-08-14
##
## Date Created: 2023-08-14
##
## Copyright (c) Lifeng Ren, 2023
## Email: ren00154@umn.edu
##
## ___________________________
##
## Version: V1.0 (2023-08-14)
##   
## Version Notes: Initial Efforts
## ___________________________

You can create RStudio headers (that can be tracked by Rstudio) using the

Windows: Ctrl + Shift + R
Mac OS: Command + Shift + R

If you test and try a little bit you would find that R can track and of the following format: #+ space + your section name + ---- (four dashes).

Code

# This is a default R section -------------------------------

#____________________________________________   This is `underscore`
#  Single has tag will not bold the words----   This is `dash`
#____________________________________________   This is `underscore`

#__________________________________________
##  Double hash tag will bold the words----   
#__________________________________________

2.2 R Markdown

Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. .Rmd is the abbreviation for R Markdown file and for more a complete R markdown reference, I personally recommend you this user guide, and official documentation on http://rmarkdown.rstudio.com to know the full picture of R markdown.

Short note: For the students taking APEC8211 - APEC8212, you need to hand in the Homework in a typed format. So, learning code in Rmd would be good to save you time.

In this class we are going to go over some very basic knowledge of R Markdown.

First, you have the opportunity to edit your page style and header, which is called a YAML header, the following is an example of my own YAML header for this class.

Code

---
title: "Lecture 1: R-Review-2023"
author: "Lifeng Ren"
date: "`r Sys.Date()`"
output: 
  html_document:
    theme: united
    toc: true
    toc_float: true
    toc_depth: 2
    highlight: tango
    df_print: paged
    mathjax: local
    self_contained: false
    number_sections: true
    fig_width: 7
    fig_height: 6
    fig_caption: true
    code_folding: hide
---

In the Rmd documentation, we have two main things:

Markdown Document
- Math: use the $ sign, and the mathematical equations coding style should be the same for LaTex.
  - For example: The probability density function of a normal distribution could be typed as: $f(x)=\frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$ , and Rmd will show the and inline output: $f(x)=\frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$. Using $$ instead of the single $, will have the following output.
    \[ f(x)=\frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2} \]
- Hyperlink: [This is the TEXT](This is the LINK). Please use the source code of this document to see the example.
- For other Markdown coding documentation, please refer to: R Markdown Cookbook
Code Chunk (mainly should be R, but can also be customized)

The code chunk normally starts with r, and follows by the chunk name you defined, and then put the chunk environment after it. For example:

Code

  ```{r, chunkexample, eval=FALSE}
    summary(cars)
  ``` #Example

According to the online documentation of R Markdown:

Using include = FALSE hides both the code and its output in the final document. However, R Markdown still executes the code in the chunk, making the results accessible to subsequent chunks.
Setting echo = FALSE ensures only the code is hidden, while its output remains visible in the final document. It’s particularly handy for displaying visuals without the accompanying code.
If you want to hide messages produced by the code, use message = FALSE.
To suppress warnings from being displayed in the final output, employ warning = FALSE.
Add a caption to images or plots using fig.cap = “…”.
To skip the execution of a particular code chunk altogether, use eval = FALSE.
You can also use knitr::opts_chunk$set(ANY OPTIONS ABOVE) like below to set a global environment for all code chunks like this:
Code
```
knitr::opts_chunk$set(echo = TRUE)
```

More coding details in Rmd should be reviewed using the source code I provided.

2.3 Coding Style

We are not professional programmer, but coding habitat is super important. Here are some most important parts I think you should be careful of.

2.3.1 Naming

Please name your variables in either the following way, and being consistent:
- MyVariable
- my_variable
- my.variable
Do not start a name with numbers like: 2023badname
Do not include illegal characters like: 2023/%badname

2.3.2 Comments

Remind yourself and other collaborators with comments in addition to headers.
For example:

Code

    #__________________________________________
    ##  Comments Your Code is Important----   
    #__________________________________________
    
    mean(x) # You might not need to generate comments for a simple function
    
    
    # A function to generate the Fibonacci sequence
    fibonacci <- function(n) { # but for a complex function you need more comments
      if (n <= 0) {
        return(integer(0))  # return an empty integer vector for non-positive n
      } else if (n == 1) {
        return(0)
      } else if (n == 2) {
        return(c(0, 1))
      } else {
        fib_sequence <- c(0, 1)
        for (i in 3:n) {
          next_element <- sum(tail(fib_sequence, 2))
          fib_sequence <- c(fib_sequence, next_element)
      }
      return(fib_sequence)
      }
    }

    # Print the first 10 numbers of the Fibonacci sequence
    print(fibonacci(10))

2.3.3 Most used Built-in Symbols and Command

Symbol	Definition	Example
`=`	Assigns within functions/datasets.	`fun(arg = value)`
`<-`	Assigns values to objects/datasets.	`obj <- 2` (shortcut: Mac: `cmd`+ `-`; Win: `ctrl`+`-`)
`==`	Checks equality.	`obj == 2` checks if `obj` equals 2.
`!=`	Checks inequality.	`obj != 2` checks if `obj` isn’t 2.
`>`	Greater than.	`obj > 2` checks if `obj` is more than 2.
`<`	Less than.	`obj < 2` checks if `obj` is less than 2.
`>=`	Greater than or equal to.	`obj >= 2`
`<=`	Less than or equal to.	`obj <= 2`
`!`	NOT (logical negation).	`!TRUE` returns `FALSE`.
`&`	AND (element-wise).	`c(TRUE, FALSE) & c(TRUE, TRUE)` returns `TRUE, FALSE`.
`\\|`	OR (element-wise).	`c(TRUE, FALSE) \\| c(FALSE, FALSE)` returns `TRUE, FALSE`.
`&&`	AND (first element).	`TRUE && FALSE` returns `FALSE`.
`\\|\\|`	OR (first element).	`TRUE \\|\\| FALSE` returns `TRUE`.
`%in%`	Tests if in a set.	`2 %in% c(1, 2, 3)` returns `TRUE`.

We will see them more often in the next couple sessions.

2.4 In-class exercise

Now, let us go to Rstudio and play with what we have learned.

Download the files

Create a folder in your local computer for the this class, preferably named as: R_Review_2023
Download the lec1 folder/zip file under R_Review_2023 from Canvas or GitHub Repository
Open lec1_stu.R: Change the Script Information with your own names, date, …

print: “Hello World”

In the source window, type the following code and select the sentence and click on Run
Code
```
  print("Hello World!")
```
```
[1] "Hello World!"
```
Type the same thing in the Console window, and hit enter.
Get Help with any functions like print: ?print()
Code
```
  ?print()
```

Assign a char value to hello using the following code and see the change in the envrionemt window. Then, print out hello.

Code

  hello <- "Hello World!"
  print(hello)

[1] "Hello World!"

3 Summary

In this section, we briefly go through Rstudio with some coding rules/conventions and get a better sense of the Rstudio Interface. After this section, make sure you are comfortable with the following points:

Interface about Rstudio
- How to generate a new Rscript and RMarkdown file.
Coding Rules in R
- How to generate the header, comments in Rscript
- Basic RMarkdown syntax
- Variables Naming Rules
- Frequently used symbols

4 Reference

An Introduction to R
R for Graduate Student
R Markdown Cookbook
Introduction to Econometrics with R
R for Economics
Data Visualization with R
Dr. Qingxiao Li’s notes for R-Review 2020
Rodrigo Franco’s notes for R-Review 2021