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### Welcome! | Вітаємо!

## Table of Contents | Зміст

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**Vectors** are strings of numbers, characters or logical data (one-dimension array). In other words, a vector is a simple tool to store your grouped data.

### Numeric, Character and Logical Vectors | Числові, Символьні і Логічні Вектори

Let's say we have four movie release dates (1985, 1999, 2015, 1964) and we want to assign them to a single variable, `release_year`. This means we'll need to create a vector using **`c()`**.

release_year <- c(1985, 1999, 2015, 1964)

release_year

What if we use quotation marks? Then this becomes a **character vector**.

# Create genre vector and assign values to it

There are also **logical vectors**, which consist of TRUE's and FALSE's. They're particular important when you want to check its contents

titles == "Akira" # which item in `titles` is equal to "Akira"?

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### Adding more elements to a vector

You can add more elements to a vector with the same **`c()`** function you use the create vectors:

release_year <- c(1985, 1999, 2015, 1964)

release_year <- c(release_year, 2016:2018)

### Length of a vector | Довжина вектора

How do we check how many items there are in a vector? We can use the **length()** function:

release_year

### Head and Tail of a vector | "Голова" та "Хвіст" вектора

We can also retrieve just the **first few items** using the **head()** function:

head(release_year) #first six items

head(release_year, n = 2) #first n items

head(release_year, 2)

We can also retrieve just the **last few items** using the **tail()** function:

tail(release_year) #last six items

tail(release_year, 2) #last two items

### Sorting a vector | Сортування вектора

We can also sort a vector:

sort(release_year)

We can also **sort in decreasing order**:

sort(release_year, decreasing = TRUE)

But if you just want the minimum and maximum values of a vector, you can use the **`min()`** and **`max()`** functions

min(release_year)

### Average of Numbers | Середнє арифметичне

If you want to check the average cost of movies produced in 2014, what would you do? Of course, one way is to add all the numbers together, then divide by the number of movies:

cost_2014 <- c(8.6, 8.5, 8.1)

You also can use the <b>mean</b> function to find the average of the numeric values in a vector:

mean_cost_2014 <- mean(cost_2014)

### Giving Names to Values in a Vector | Як присвоїти назви значенням вектора?

Suppose you want to remember which year corresponds to which movie.

#Creating a year vector

Now, you can retrieve the values based on the names:

release_year[c("American Beauty", "Chicago")]

Note that the values of the vector are still the years. We can see this in action by adding a number to the first item:

release_year[1] + 100 #adding 100 to the first item changes the year

And you can retrieve the names of the vector using **`names()`**

names(release_year)[1:3]

### Summarizing Vectors | Підсумовування Векторів

You can also use the **"summary"** function for simple descriptive statistics: minimum, first quartile, mean, third quartile, maximum:

summary(cost_2014)

### Using Logical Operations on Vectors | Логічні Операції з Векторами

A vector can also be comprised of **`TRUE`** and **`FALSE`**, which are special **logical values** in R. These boolean values are used used to indicate whether a condition is true or false.

movie_year <- 1997

You can also make a logical comparison across multiple items in a vector. Which movie release years here are "greater" than 2014?

movies_years <- c(1998, 2010, 2016)

We can also check for **equivalence**, using **`==`**. Let's check which movie year is equal to 2015.

movies_years == 2015 # is equal to 2015?

If you want to check which ones are **not equal** to 2015, you can use **`!=`**

movies_years != 2015

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What if you wanted to retrieve the second year from the following **vector of movie years**?

movie_years <- c(1985, 1999, 2002, 2010, 2012)

To retrieve the **second year**, you can use square brackets **`[]`**:

movie_years[2] #second item

To retrieve the **third year**, you can use:

movie_years[3]

And if you want to retrieve **multiple items**, you can pass in a vector:

movie_years[c(1,3)] #first and third items

**Retrieving a vector without some of its items** | **Вивід вектора без деяких його елементів**

titles <- c("Black Swan", "Jumanji", "City of God", "Toy Story", "Casino")

You can save the new vector using a variable:

new_titles <- titles[-1] #removes "Black Swan", the first item

** Missing Values (NA)** | ** Відсутні значення (NA) **

age_restric <- c(14, 12, 10, NA, 18, NA)

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### Subsetting vectors based on a logical condition | Поділ векторів на основі логічної умови

What if we want to know which movies were created after year 2000? We can simply apply a logical comparison across all the items in a vector:

release_year > 2000

To retrieve the actual movie years after year 2000, you can simply subset the vector using the logical vector within **square brackets "[]"**:

release_year[movie_years > 2000] #returns a vector for elements that returned TRUE for the condition

As you may notice, subsetting vectors in R works by retrieving items that were TRUE for the provided condition. For example, `year[year > 2000]` can be verbally explained as: _"From the vector `year`, return only values where the values are TRUE for `year > 2000`"_.

release_year

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Factors are variables in R which take on a limited number of different values; such variables are often refered to as  **categorical variables**. The difference between a categorical variable and a continuous variable is that a categorical variable can belong to a limited number of categories. A continuous variable, on the other hand, can correspond to an infinite number of values. For example, the height of a tree is a continuous variable, but the titles of books would be a categorical variable.

Let's start with a _**vector**_ of genres:

genre_vector <- c("Comedy", "Animation", "Crime", "Comedy", "Animation")

As you may have noticed, you can theoretically group the items above into three categories of genres: _Animation_, _Comedy_ and _Crime_. In R-terms, we call these categories **"factor levels"**.

genre_factor <- factor(genre_vector)

levels(genre_factor) # factor levels

### Summarizing Factors | Підсумовування Факторів

When you have a large vector, it becomes difficult to identify which levels are most common (e.g., "How many 'Comedy' movies are there?").

summary(genre_factor)

And recall that you can sort the values of the table using **sort()**.

sort(summary(genre_factor)) #sorts values by ascending order

### Ordered factors | Впорядковані фактори

There are two types of categorical variables: a **nominal categorical variable** and an **ordinal categorical variable**.

movie_length <- c("Very Short", "Short", "Medium","Short", "Long",

__`movie_length`__ should be converted to an ordinal factor since its categories have a natural ordering. By default, the function <b>factor()</b> transforms `movie_length` into an unordered factor.

movie_length_ordered <- factor(movie_length, ordered = TRUE ,

Now, lets look at the summary of the ordered factor, <b>factor_mvlength_vector</b>:

summary(movie_length_ordered)

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VECTORS AND FACTORS | ВЕКТОРИ І ФАКТОРИ¶

Welcome! | Вітаємо!¶

Table of Contents | Зміст¶

About the Dataset | Про датасет¶

Vectors | Вектори¶

Numeric, Character and Logical Vectors | Числові, Символьні і Логічні Вектори¶

[Tip] TRUE and FALSE in R ¶

[Tip] TRUE і FALSE в мові R ¶

Vector Operations | Векторні операції¶

Adding more elements to a vector¶

Length of a vector | Довжина вектора¶

Head and Tail of a vector | "Голова" та "Хвіст" вектора¶

Sorting a vector | Сортування вектора¶

Average of Numbers | Середнє арифметичне¶

Giving Names to Values in a Vector | Як присвоїти назви значенням вектора?¶

Summarizing Vectors | Підсумовування Векторів¶

Using Logical Operations on Vectors | Логічні Операції з Векторами¶

[Tip] Logical Operators in R ¶

[Лайф-хак] Логічні оператори в R ¶

Subsetting Vectors | Поділ векторів¶

[Tip] Checking NA in R ¶

[Tip] Перевірка на наявність NA в мові R ¶

Subsetting vectors based on a logical condition | Поділ векторів на основі логічної умови¶

Factors | Фактори¶

Summarizing Factors | Підсумовування Факторів¶

Ordered factors | Впорядковані фактори¶

About the Author: | Про автора:¶

About the Translator: | Про перекладача¶