session2.Rmd

---
title: "R through the user interface of RStudio - performing basic operations"
subtitle: "Learning the basics of R - Part 1"  
author: 
  - "Ernest Guevarra"
date: '23 October 2024'
output:
  xaringan::moon_reader:
    css: xaringan-themer.css
    nature:
      slideNumberFormat: "%current%"
      highlightStyle: github
      highlightLines: true
      ratio: 16:9
      countIncrementalSlides: true
---

```{r setup, include=FALSE}
options(htmltools.dir.version = FALSE)
knitr::opts_chunk$set(
  fig.width=9, fig.height=3.5, fig.retina=3,
  out.width = "100%",
  cache = FALSE,
  echo = TRUE,
  message = FALSE, 
  warning = FALSE,
  hiline = TRUE
)

if (!require(remotes)) install.packages("remotes")
if (!require(fontawesome)) remotes::install_github("rstudio/fontawesome")
```

```{r xaringan-themer, include=FALSE, warning=FALSE}
library(xaringanthemer)
style_mono_light(
  base_color = "#002147",
  title_slide_background_image = "",
  title_slide_background_size = "cover",
  header_font_google = google_font("Fira Sans"),
  text_font_google   = google_font("Fira Sans Condensed"),
  text_font_size = "1.2em",
  link_color = "#214700",
  header_h1_font_size = "50px",
  header_h2_font_size = "40px",
  header_h3_font_size = "30px",
  code_font_google   = google_font("Fira Mono"),
  text_slide_number_font_size = "0.5em",
  footnote_font_size = "0.5em"
)
```

# Outline

1. Using RStudio to access the R console

2. Some basic operators in R

    * Arithmetic    
    * Relational    
    * Logical    
    * Assignment
    
3. Using RStudio to create scripts

---

# Using RStudio to access the R console

* RStudio has a specific window/pane for the R console which behaves exactly the same as the raw R console

* Issue commands directly on the console to produce a desired outcome or perform a specific action

* Most commands produce an output that is shown on the console

---

class: inverse, center, middle

# Basic operators in R

---

# Arithmetic operators

These operators are used to carry out mathematical operations like addition and multiplication. Here is a list of arithmetic operators available in R.

```{r, echo = FALSE}
operator <- c("+", "-", "*", "/", "^", "%%", "%/%")
description <- c("Addition", "Subtraction", "Multiplication", "Division", "Exponent", "Modulus", "Integer Division")

data.frame(operator, description) |>
  knitr::kable(
    row.names = FALSE,
    col.names = c("Operator", "Description")
  ) |>
  kableExtra::kable_styling(
    bootstrap_options = "striped",
    full_width = FALSE,
    position = "center"
  )
```

---

# Arithmetic operators - application

Let us try R's arithmetic operations to calculate BMI:

$$ \text{BMI} ~ = ~ \frac{kgs}{m  ^ 2} $$

using the following values:

$$ \text{weight} ~ = ~ 80 ~ \text{kgs} $$

$$ \text{height} ~ = ~ 1.6 ~ \text{metres} $$
---

# Arithmetic operators - application

```{r, echo = TRUE}
80 / 1.6 ^ 2
```

---

# Relational operators

Relational operators are used to compare between values. Here is a list of relational operators available in R.

```{r, echo = FALSE}
operator <- c("<", ">", "<=", ">=", "==", "!=")
description <- c("Less than", "Greater than", "Less than or equal to", "Greater than or equal to", "Equal to", "Not equal to")

data.frame(operator, description) |>
  knitr::kable(
    row.names = FALSE,
    col.names = c("Operator", "Description")
  ) |>
  kableExtra::kable_styling(
    bootstrap_options = "striped",
    full_width = FALSE,
    position = "center"
  )
```

---

# Relational operators - application

Let us apply the relational operators using again BMI as an example.

Say we have **Person A** with a weight of *80 kilograms* and a *height of 1.6 metres* and **Person B** with a weight of *120 kilograms* and a height of *210 centimetres*.

In R, try to answer the following questions:

1. Is **Person A** heavier in weight compared to **Person B**?

2. Is **Person A** taller in height compared to **Person B**?

3. Whose BMI is greater, **Person A** or **Person B**?

---

# Relational operators - application

### 1. Is **Person A** heavier in weight compared to **Person B**?

```{r, echo = TRUE}
80 > 120     ## Is Person A's weight greater than Person B's weight

80 < 120     ## Is Person A's weight lesser than Person B's weight

80 == 120    ## Is Person A's weight the same as Person B's weight
```

---

# Relational operators - application

### 2. Is **Person A** taller in height compared to **Person B**?

```{r, echo = TRUE}
1.6 > 210 / 100    ## Is Person A's height greater than Person B's height

1.6 < 210 / 100    ## Is Person A's height lesser than Person B's height

1.6 == 210 / 100   ## Is Person A's height the same as Person B's height
```

---

# Relational operators - application

### 3. Whose BMI is greater, **Person A** or **Person B**?

```{r, echo = TRUE}
80 / 1.6 ^ 2 > 120 / (210 / 100) ^ 2    ## Is Person A's BMI greater than Person B's BMI

80 / 1.6 ^ 2 < 120 / (210 / 100) ^ 2    ## Is Person A's BMI lesser than Person B's BMI

80 / 1.6 ^ 2 == 120 / (210 / 100) ^ 2   ## Is Person A's BMI the same as Person B's BMI
```

---

# Logical operators

Logical operators are used to carry out Boolean operations like AND, OR etc.

```{r, echo = FALSE, eval = FALSE}
operator <- c("!", "&", "&&", "|", "||")
description <- c("Logical NOT", "Element-wise logical AND", "Logical AND", "Element-wise logical OR", "Logical OR")

data.frame(operator, description) |>
  knitr::kable(
    row.names = FALSE,
    col.names = c("Operator", "Description")
  ) |>
  kableExtra::kable_styling(
    bootstrap_options = "striped",
    full_width = FALSE,
    position = "center"
  )
```

Operator         | Description
:---             | :---
!                | Logical NOT
&                | Element-wise logical AND
&&               | Logical AND
&#124;         | Element-wise logical OR
&#124;&#124; | Logical OR 

---

# Logical operators - application

Let us apply the logical operators again using the example of BMI for Person A and Person B in the previous exercise.

In R, answer the following questions using logical operators:

1. Is the weight of **Person A** AND the weight of **Person B** both equal to 80 kilograms?

2. Is the weight of **Person A** OR the weight of **Person B** less than 100 kilograms?

3. Is the weight of **Person A** greater than the weight of **Person B** AND the height of **Person A** greater than the height of **Person B**?

4. Is the weight of **Person A** greater than the weight of **Person B** OR the height of **Person A** greater than the height of **Person B**?

---

# Logical operators - application

### 1. Is the weight of **Person A** AND the weight of **Person B** both equal to 80 kilograms?

```{r, echo = TRUE}
80 == 80 & 120 == 80
```

### 2. Is the weight of **Person A** OR the weight of **Person B** less than 100 kilograms?

```{r, echo = TRUE}
80 < 100 | 120 < 100
```

---

# Logical operators - application

### 3. Is the weight of **Person A** greater than the weight of **Person B** AND the height of **Person A** greater than the height of **Person B**?

```{r, echo = TRUE}
80 > 120 & 1.6 > 2.1
```

### 4. Is the weight of **Person A** greater than the weight of **Person B** OR the height of **Person A** greater than the height of **Person B**?

```{r, echo = TRUE}
80 > 120 | 1.6 > 2.1
```

---

# Assignment operators

These operators are used to assign values to objects.

```{r, echo = FALSE}
operator <- c("<-", "<<-", "=", "->", "->>")
description <- c("Leftwards assignment", "Leftwards assignment", "Leftwards assignment", "Rightwards assignment", "Rightwards assignment")

data.frame(operator, description) |>
  knitr::kable(
    row.names = FALSE,
    col.names = c("Operator", "Description")
  ) |>
  kableExtra::kable_styling(
    bootstrap_options = "striped",
    full_width = FALSE,
    position = "center"
  )
```

---

# Assignment operators - application

Let us again use the BMI example to apply the assignment operators:

1. Assign the weight of person A to an object named `weight_a`

2. Assign the height of person A to an object named `height_a`

3. Calculate BMI for person A using objects `weight_a` and `height_a`. Assign the value of BMI to an object named `bmi_a`.

---

# Assignment operators - application

### 1. Assign the weight of person A to an object named `weight_a`

```{r, echo = TRUE}
weight_a <- 80

weight_a
```

### 2. Assign the height of person A to an object named `height_a`

```{r, echo = TRUE}
height_a <- 1.6

height_a
```

---

# Assignment operators - application

### 3. Calculate BMI for person A using objects `weight_a` and `height_a`. Assign the value of BMI to an object named `bmi_a`.

```{r, echo = TRUE}
bmi_a <- weight_a / height_a ^ 2

bmi_a
```

---

class: inverse, center, middle

# Questions?

---

class: inverse, center, middle

# Practical session

Using what we have learned in the first half of the session, we'll learn about how to write R scripts.

---

# Using RStudio to create scripts

* So far, we have tried issuing commands in R straight into the console to perform single commands at a time

* In real life context, we will rarely use R for a single command. To make meaningful analysis, we will often string together a series of commands to produce an intended result/output

* We will also often have to repeat the same commands with different data or parameters

* As such, direct to console issuing of commands in R will be highly inefficient

---

# Using RStudio to create scripts

.pull-left[
RStudio, being an **integrated development environment (IDE)**, provides functionality and tools for 

* recording multiple lines of commands which can be run/issued onto the console line by line; and,

* saving the recorded multiple lines of code/commands for later use.

This record of multiple lines of code/commands is often called an **R script** and is saved as plain text file with a `.R` extension.
]

.pull-right[
```{r example_script, echo = TRUE, eval = FALSE}
## R script to calculate BMI of 
## person A and person B
weight_a <- 80
height_a <- 1.6
bmi_a <- weight_a / height_a ^ 2

weight_b <- 12
height_b <- 2.1
bmi_b <- weight_b / height_b ^ 2
```
]

---

class: inverse, center, middle

# Questions?

---

class: inverse, center, middle

# Thank you!

Slides can be viewed at https://oxford-ihtm.io/open-reproducible-science/session2.html

PDF version of slides can be downloaded at https://oxford-ihtm.io/open-reproducible-science/pdf/session2-r-basics-part1.pdf

R scripts for slides available [here](https://github.com/OxfordIHTM/open-reproducible-science/blob/main/session2.Rmd)