1_R_basics.Rmd

---
title: "1. Small introduction to R and RStudio"
author: "[G. Moroz](mailto:agricolamz@gmail.com) <br> Presentation link: goo.gl/HdS466"
editor_options: 
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---

```{r setup, include=FALSE}
knitr::opts_chunk$set(message = FALSE, warning = FALSE, comment=NA)
```

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## 0. Prerequisites:

* install [R](https://cran.r-project.org/)
* install [RStudio Desktop](http://www.rstudio.com/download) (it is not necessary, but RStudio makes a lot of things easier)

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## 1. R
To download R, go to [CRAN](https://cran.r-project.org/). Don’t try to pick a mirror that’s close to you, instead it is better to use the cloud mirror, https://cloud.r-project.org.

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## 2. RStudio
RStudio is an integrated development environment, or IDE, for R programming. There are two possibilities:

* you type R code in the R console pane, and press enter to run it
* you type R code in the Code editor pane, and press control/command + enter to run selected part

![](https://raw.githubusercontent.com/agricolamz/2018_lingtypology_course_Paris/master/rstudio.png)

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## 3. Some R basics
### 3.1 Base elements
```{r}
7
-5.7
"bonjour"
"bon mot"
TRUE
FALSE
```
### 3.2 Variables
```{r}
my_var <- 7
my_var
my_var+7
my_var
my_var <- my_var + 7
```

### 3.2 Vectors
```{r}
5:9
11:4
numbers <- c(7, 9.9, 24)
multiple_strings <- c("the", "quick", "brown", "fox", "jumps", "over", "the", "lazy", "dog")
one_string <- c("the quick brown fox jumps over the lazy dog")
true_false <- c(TRUE, FALSE, FALSE, TRUE)
length(numbers)
length(multiple_strings)
length(one_string)
```

### 3.3 Dataframe
```{r}
my_df <- data.frame(latin = c("a", "b", "c"),
                    cyrillic = c("а", "б", "в"),
                    greek = c("α", "β", "γ"),
                    numbers = c(1:3),
                    is.vowel = c(TRUE, FALSE, FALSE),
                    stringsAsFactors = FALSE)
my_df
nrow(my_df)
ncol(my_df)
```

### 3.4 Indexing
```{r}
numbers[3]
multiple_strings[9]
my_df[2, 3]
my_df[2,]
my_df[,3]
my_df$is.vowel
my_df$is.vowel[2]
```

### 3.5 Reading files to R
We can read to R a dataset about Numeral Classifiers from [AUTOTYP database](https://github.com/autotyp/autotyp-data).
```{r}
new_df <- read.csv("https://raw.githubusercontent.com/autotyp/autotyp-data/master/data/Numeral_classifiers.csv")
new_df
```

It could be also a file on your computer, just provide a whole path to the file. Windows users need to change backslashes `\` to slashes `/`.

```{r, eval = FALSE}
new_df_2 <- read.csv("/home/agricolamz/my_file.csv")
```

### 3.6 Writing files from R
```{r, eval = FALSE}
write.csv(new_df_2, "/home/agricolamz/my_new_file.csv",
          row.names = FALSE)
```

### 3.7 Missing data
In R, missing values are represented by the symbol `NA` (not available).

```{r}
is.na(new_df$NumClass.Presence)
sum(is.na(new_df$NumClass.Presence))
sum(is.na(new_df))
```

### 3.8 How to get help in R
```{r, eval = FALSE}
?nchar
```

## 3.9 Installing packages
There are a lot of R packages for solving a lot of different problems. There are two way for install them (you need an internet connection):

* packages on CRAN are checked in multiple ways and should be stable

```{r, eval=FALSE}
install.packages("lingtypology")
```

* packages on GitHub are NOT checked and could contain anything, but it is the place where all package developers keep the last vertion of they work.

```{r, eval=FALSE}
install.packages("devtools")
devtools::install_github("ropensci/lingtypology")
```

* or package file
```{r, eval=FALSE}
install.packages("lingtypology",
                 destdir = "/path/to/your/package")
```

After the package is installed you need to load the package using the following command:
```{r, eval=FALSE}
library("lingtypology")
```

There is a nice picture from [Phillips N. D. (2017) YaRrr! The Pirate’s Guide to R](https://bookdown.org/ndphillips/YaRrr/):

![](package.png)


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## 4. Tasks
### 4.1
Install `lingtypology` package and find, how many rows in the `circassian` dataset.

<form name="FormOne" onsubmit="return validateFormOne()" method="post">
<input type="text" name="answerOne">
<input type="submit" value="check">
</form>

### 4.2
In the `circassian` dataset find out the name of the 86. village.

<form name="FormTwo" onsubmit="return validateFormTwo()" method="post">
<input type="text" name="answerTwo">
<input type="submit" value="check">
</form>

### 4.3
Write the `circassian` dataset to your computer and use `file.info()` function to figure out how many bites in the result file.

<form name="FormThree" onsubmit="return validateFormThree()" method="post">
<input type="text" name="answerThree">
<input type="submit" value="check">
</form>

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## 5. Further reading

There are a lot of books, articles, tutorials and online courses about R. Here is some of them:

* [book _"R for Data Science"_ by G. Grolemund and H. Wickham](http://r4ds.had.co.nz/)
* [on-line course _"Introduction à R"_ by V. Guyader](https://www.datacamp.com/community/open-courses/introduction-a-r)
* [book _"How to do Linguistics with R"_  by N. Levshina](https://benjamins.com/#catalog/books/z.195/main)
* [book _"Statistics for Linguistics with R"_ by S. Gries](https://www.amazon.com/dp/3110307286)

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