chapter1.Rmd

---
title_meta: Chapter 1
title: Intro to basics
description: >-
  Take your first steps with R. In this chapter, you will learn how to use the
  console as a calculator and how to assign variables. You will also get to know
  the basic data types in R. Let's get started.
free_preview: true
---

## How it works

```yaml
type: NormalExercise
key: 15d729634a
xp: 100
skills:
  - 1
```

In the editor, you should type R code to solve the exercises. When you submit your code, every line of code is interpreted and executed by R and you get a message whether or not your code was correct. The output of your R code is shown in the console.

R makes use of the `#` sign to add comments, so that you and others can understand what the R code is about. Just like Twitter! Comments are not run as R code, so they will not influence your result. For example, _Calculate 3 + 4_ in the editor is a comment.

You can also execute R commands straight in the console. This is a good way to experiment with R code, as your submission is not checked for correctness.

`@instructions`
- In the editor there is already some sample code. Can you see which lines are actual R code and which are comments?
- Add a line of code that calculates the sum of 6 and 12, and submit your code.

`@hint`
Just add a line of R code that calculates the sum of 6 and 12, just like the example in the sample code!

`@pre_exercise_code`
```{r}
# no pec

```

`@sample_code`
```{r}
# Calculate 3 + 4
3 + 4

# Calculate 6 + 12

```

`@solution`
```{r}
# Calculate 3 + 4
3 + 4

# Calculate 6 + 12
6 + 12
```

`@sct`
```{r}
ex() %>% check_output_expr("18", missing_msg = "Make sure to add `6 + 12` on a new line. Do not start the line with a `#`, otherwise your R code is not executed!")

success_msg("Awesome! See how the console shows the result of the R code you submitted? Now that you're familiar with the interface, let's get down to R business!")
```

---

## Arithmetic with R

```yaml
type: NormalExercise
key: 720745eda5
xp: 100
skills:
  - 1
```

In its most basic form, R can be used as a simple calculator. Consider the following arithmetic operators:

- Addition: `+`
- Subtraction: `-`
- Multiplication: `*`
- Division: `/`
- Exponentiation: `^`
- Modulo: `%%`

The last two might need some explaining:

- The `^` operator raises the number to its left to the power of the number to its right: for example `3^2` is 9.
- The modulo returns the remainder of the division of the number to the left by the number on its right, for example 5 modulo 3 or `5 %% 3` is 2.

With this knowledge, follow the instructions to complete the exercise.

`@instructions`
- Type `2^5` in the editor to calculate 2 to the power 5.
- Type `28 %% 6` to calculate 28 modulo 6.
- Submit the answer and have a look at the R output in the console.
- Note how the `#` symbol is used to add comments on the R code.

`@hint`
Another example of the modulo operator: `9 %% 2` equals `1`.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# An addition
5 + 5 

# A subtraction
5 - 5 

# A multiplication
3 * 5

 # A division
(5 + 5) / 2 

# Exponentiation


# Modulo

```

`@solution`
```{r}
# An addition
5 + 5

# A subtraction
5 - 5 

# A multiplication
3 * 5

 # A division
(5 + 5) / 2 

# Exponentiation
2 ^ 5

# Modulo
28 %% 6
```

`@sct`
```{r}
msg = "Do not remove the other arithmetic examples!"
ex() %>% check_output_expr("2^5", missing_msg = "The exponentiation example is not correct. Write `2 ^ 5` on a new line.")

ex() %>% check_output_expr("28 %% 6", missing_msg = "There seems to be an issue with the modulo example. Write `28 %% 6` on a new line.")
success_msg("Great! Head over to the next exercise.")
```

---

## Variable assignment

```yaml
type: NormalExercise
key: 5f200ffd43
xp: 100
skills:
  - 1
```

A basic concept in (statistical) programming is called a **variable**. 

A variable allows you to store a value (e.g. 4) or an object (e.g. a function description) in R. You can then later use this variable's name to easily access the value or the object that is stored within this variable. 

You can assign a value 4 to a variable `my_var` with the command

```
my_var <- 4
```

`@instructions`
Over to you: complete the code in the editor such that it assigns the value 42 to the variable `x` in the editor. Submit the answer. Notice that when you ask R to print `x`, the value 42 appears.

`@hint`
Look at how the value 4 was assigned to `my_variable` in the exercise's assignment. Do the exact same thing in the editor, but now assign 42 to the variable `x`.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# Assign the value 42 to x
x <- 

# Print out the value of the variable x
x
```

`@solution`
```{r}
# Assign the value 42 to x
x <- 42

# Print out the value of the variable x
x
```

`@sct`
```{r}
ex() %>% check_object("x", undefined_msg = "Make sure to define a variable `x`.")  %>% check_equal(incorrect_msg = "Make sure that you assign the correct value to `x`.")

success_msg("Good job! Have you noticed that R does not print the value of a variable to the console when you did the assignment? `x <- 42` did not generate any output, because R assumes that you will be needing this variable in the future. Otherwise you wouldn't have stored the value in a variable in the first place, right? Proceed to the next exercise!")
```

---

## Variable assignment (2)

```yaml
type: NormalExercise
key: c5944b90eb
xp: 100
skills:
  - 1
```

Suppose you have a fruit basket with five apples. As a data analyst in training, you want to store the number of apples in a variable with the name `my_apples`.

`@instructions`
- Type the following code in the editor: `my_apples <- 5`. This will assign the value 5 to `my_apples`.
- Type: `my_apples` below the second comment. This will print out the value of `my_apples`.
- Submit your answer, and look at the output: you see that the number 5 is printed. So R now links the variable `my_apples` to the value 5.

`@hint`
Remember that if you want to assign a number or an object to a variable in R, you can make use of the assignment operator `<-`. Alternatively, you can use `=`, but `<-` is widely preferred in the R community.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# Assign the value 5 to the variable my_apples


# Print out the value of the variable my_apples

```

`@solution`
```{r}
# Assign the value 5 to the variable my_apples
my_apples <- 5

# Print out the value of the variable my_apples
my_apples
```

`@sct`
```{r}
ex() %>% check_object("my_apples", undefined_msg = "Please make sure to define a variable `my_apples`.") %>% check_equal(incorrect_msg = "Make sure that you assign the correct value to `my_apples`.")

ex() %>% check_output_expr("my_apples", missing_msg = "Have you explicitly told R to print out the `my_apples` variable to the console?")

success_msg("Great! Continue to the next exercise!")
```

---

## Variable assignment (3)

```yaml
type: NormalExercise
key: 1c1bd25045
xp: 100
skills:
  - 1
```

Every tasty fruit basket needs oranges, so you decide to add six oranges. As a data analyst, your reflex is to immediately create the variable `my_oranges` and assign the value 6 to it. Next, you want to calculate how many pieces of fruit you have in total. Since you have given meaningful names to these values, you can now code this in a clear way: 

```
my_apples + my_oranges
```

`@instructions`
- Assign to `my_oranges` the value 6.
- Add the variables `my_apples` and `my_oranges` and have R simply print the result.
- Assign the result of adding `my_apples` and `my_oranges` to a new variable `my_fruit`.

`@hint`
`my_fruit` is just the sum of `my_apples` and `my_oranges`. You can use the `+` operator to sum the two and `<-` to assign that value to the variable `my_fruit`.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# Assign a value to the variables my_apples and my_oranges
my_apples <- 5


# Add these two variables together


# Create the variable my_fruit

```

`@solution`
```{r}
# Assign a value to the variables my_apples and my_oranges
my_apples  <- 5
my_oranges <- 6

# Add these two variables together
my_apples + my_oranges

# Create the variable my_fruit
my_fruit <- my_apples + my_oranges
```

`@sct`
```{r}

msg <- "Have you used `my_fruit <- my_apples + my_oranges` to create the `my_fruit` variable?"
ex() %>% check_object("my_apples") %>% check_equal(incorrect_msg = "Keep the line that assigns 5 to `my_apples`.")

ex() %>% check_object("my_oranges") %>% check_equal(incorrect_msg = "Keep the line that assigns 6 to `my_oranges`.")

ex() %>% check_output_expr("my_apples + my_oranges",missing_msg = "Make sure to print out the result of adding `my_apples` and `my_oranges`. The code example in the description already gives away the answer to this instruction!")

ex() %>% check_object("my_fruit", undefined_msg = msg)  %>% check_equal(incorrect_msg = msg)
success_msg("Nice one! The great advantage of doing calculations with variables is reusability. If you just change `my_apples` to equal 12 instead of 5 and rerun the script, `my_fruit` will automatically update as well. Continue to the next exercise.")
```

---

## Apples and oranges

```yaml
type: NormalExercise
key: 915fcc7c99
xp: 100
skills:
  - 1
```

Common knowledge tells you not to add apples and oranges. But hey, that is what you just did, no :-)? The `my_apples` and `my_oranges` variables both contained a number in the previous exercise. The `+` operator works with numeric variables in R. If you really tried to add "apples" and "oranges", and assigned a text value to the variable `my_oranges` (see the editor), you would be trying to assign the addition of a numeric and a character variable to the variable `my_fruit`. This is not possible.

`@instructions`
- Submit the answer and read the error message. Make sure to understand why this did not work.
- Adjust the code so that R knows you have 6 oranges and thus a fruit basket with 11 pieces of fruit.

`@hint`
You have to assign the numeric value `6` to the `my_oranges` variable instead of the character value `"six"`. Note how the quotation marks are used to indicate that `"six"` is a character.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# Assign a value to the variable my_apples
my_apples <- 5 

# Fix the assignment of my_oranges
my_oranges <- "six" 

# Create the variable my_fruit and print it out
my_fruit <- my_apples + my_oranges 
my_fruit
```

`@solution`
```{r}
# Assign a value to the variable my_apples
my_apples <- 5  

# Fix the assignment of my_oranges
my_oranges <- 6

# Create the variable my_fruit and print it out
my_fruit <- my_apples + my_oranges 
my_fruit
```

`@sct`
```{r}
ex() %>% check_error(incorrect_msg = "You can do this by setting the `my_oranges` variable to a numeric value, not a string!")

ex() %>% check_object("my_apples") %>% check_equal(incorrect_msg = "Make sure that `my_apples` still contains `5`.")

ex() %>% check_object("my_oranges") %>% check_equal(incorrect_msg = "Make sure that `my_oranges` is equal to `6`.")

ex() %>% check_object("my_fruit") %>% check_equal(incorrect_msg = "The value of `my_fruit` is not correct. It should be 11, the sum of `my_apples` and `my_oranges`.")

ex() %>% check_object("my_fruit")%>% check_or(
  check_code(.,"my_fruit\\s*<-\\s*my_apples\\s*\\+\\s*my_oranges", missing_msg = "Did you create `my_fruit` as the sum of variables `my_apples` and `my_oranges`?", append=F),
  check_code(.,"my_fruit\\s*<-\\s*my_oranges\\s*\\+\\s*my_apples", missing_msg = "Did you create `my_fruit` as the sum of variables `my_apples` and `my_oranges`?", append=F)
 )
ex() %>% check_output_expr("my_fruit", missing_msg = "Don't remove the line that prints out `my_fruit`.")



success_msg("Awesome, keep up the good work! Continue to the next exercise.")
```

---

## Basic data types in R

```yaml
type: NormalExercise
key: 0f23107394
xp: 100
skills:
  - 1
```

R works with numerous data types. Some of the most basic types to get started are:

- Decimal values like `4.5` are called **numerics**.
- Whole numbers like `4` are called **integers**. Integers are also numerics.
- Boolean values (`TRUE` or `FALSE`) are called **logical**.
- Text (or string) values are called **characters**.

Note how the quotation marks in the editor indicate that `"some text"` is a string.

`@instructions`
Change the value of the:

- `my_numeric` variable to `42`.
- `my_character` variable to `"universe"`. Note that the quotation marks indicate that `"universe"` is a character.
- `my_logical` variable to `FALSE`.

Note that R is case sensitive!

`@hint`
Replace the values in the editor with the values that are provided in the exercise. For example: 
`my_numeric <- 42` assigns the value 42 to the variable `my_numeric`.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# Change my_numeric to be 42
my_numeric <- 42.5

# Change my_character to be "universe"
my_character <- "some text"

# Change my_logical to be FALSE
my_logical <- TRUE
```

`@solution`
```{r}
# Change my_numeric to be 42
my_numeric <- 42

# Change my_character to be "universe"
my_character <- "universe"

# Change my_logical to be FALSE
my_logical <- FALSE
```

`@sct`
```{r}
ex() %>% check_object("my_numeric") %>% check_equal(incorrect_msg = "Have you correctly changed the declaration of `my_numeric` so it contains the value 42?")

ex() %>% check_object("my_character") %>% check_equal(incorrect_msg = "Have you correctly changed `my_character` to `\"universe\"`? Don't forget the quotes!")

ex() %>% check_object("my_logical") %>% check_equal(incorrect_msg = "Have you correctly changed `my_logical` to `FALSE`? All letters of `FALSE` should be capitalized!")

success_msg("Great work! Continue to the next exercise.")
```

---

## What's that data type?

```yaml
type: NormalExercise
key: 99b549229d
xp: 100
skills:
  - 1
```

Do you remember that when you added `5 + "six"`, you got an error due to a mismatch in data types? You can avoid such embarrassing situations by checking the data type of a variable beforehand. You can do this with the `class()` function, as the code in the editor shows.

`@instructions`
Complete the code in the editor and also print out the classes of `my_character` and `my_logical`.

`@hint`
The code that prints the data type of `my_numeric` is already included; do a similar things for `my_character` and `my_logical`.

`@pre_exercise_code`
```{r}
# no pec
```

`@sample_code`
```{r}
# Declare variables of different types
my_numeric <- 42
my_character <- "universe"
my_logical <- FALSE 

# Check class of my_numeric
class(my_numeric)

# Check class of my_character


# Check class of my_logical

```

`@solution`
```{r}
# Declare variables of different types:
my_numeric <- 42
my_character <- "universe"
my_logical <- FALSE

# Check class of my_numeric
class(my_numeric)

# Check class of my_character
class(my_character)

# Check class of my_logical
class(my_logical)
```

`@sct`
```{r}
msg <- "Do not change the declaration of the variables!"
ex()  %>% check_object("my_numeric", undefined_msg = msg)  %>%  check_equal(incorrect_msg = msg)

ex()  %>% check_object("my_character", undefined_msg = msg)  %>%  check_equal(incorrect_msg = msg)

ex()  %>% check_object("my_logical", undefined_msg = msg)  %>%  check_equal(incorrect_msg = msg)

patt <- "Have you included `class(%1$s)` to print out the data type of `%1$s`?"
ex() %>% check_output_expr("class(my_numeric)",missing_msg = "Do not remove the code that prints out the type of `my_numeric`.")

ex() %>% check_output_expr("class(my_character)",missing_msg = sprintf(patt, "my_character"))

ex() %>% check_output_expr("class(my_logical)",missing_msg = sprintf(patt, "my_logical"))
success_msg("Congratulations! This was the last exercise for this chapter. Head over to the next chapter to get immersed in the world of vectors!")
```