Intro to R

class: center, middle, inverse, title-slide

# Intro to R
### The R Bootcamp <a href='https://therbootcamp.github.io'>www.therbootcamp.com</a> <a href='https://twitter.com/therbootcamp'>@therbootcamp</a>
### July 2018

---

layout: true

<div class="my-footer">
<a href="https://therbootcamp.github.io/">Basel, July 2018</a>
&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;
&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;
&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;
&emsp;&emsp;&emsp;&emsp;&emsp;
<a href="https://therbootcamp.github.io/">www.therbootcamp.com</a>
</div>

---

# R

From [Wikipedia](https://en.wikipedia.org/wiki/Statistical_model) (emphasis added):

> R is an **open source programming language** and software environment for **statistical computing and graphics** that is supported by the **R Foundation for Statistical Computing**. The R language is **widely used among statisticians and data miners** for developing statistical software and data analysis. Polls, surveys of data miners, and studies of scholarly literature databases show that **R's popularity has increased substantially in recent years**.

> R is a GNU package. The source code for the R software environment is written primarily in **C, Fortran, and R**. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems. While R has a command line interface, there are several **graphical front-ends available**.

---

# Programming language

From [Wikipedia](https://en.wikipedia.org/wiki/Statistical_model) (emphasis added):

> A programming language is a **formal language** that specifies a set of instructions that can be used to produce various kinds of output. Programming languages generally consist of **instructions for a computer**. Programming languages can be used to create programs that **implement specific algorithms**.

.pull-left4[
### Algorithm
1. Load data
2. Extract variables
3. Run analysis
4. Print result
]

.pull-right6[
### Implementation in R

```r
data <- read.table(link)
variables <- data[,c('group','variable')]
analysis <- lm(variable ~ group, data = variables)
summary(analysis)
```
]

---

# Why R?

.pull-left3[
R steadily **grows in popularity**.

Today, R is one of the **most popular languages for data science** and overall.

In terms of the number of data science jobs, **R beats SAS and Matlab**, and is on par with Python.

Image source: https://i0.wp.com/r4stats.com/

]

.pull-right6[

 <img src="https://i0.wp.com/r4stats.com/wp-content/uploads/2017/02/Fig-1a-IndeedJobs-2017.png" height="450">

]

---

# R is so popular because

There are many good reasons to prefer R over superficially more user friendly software such as **Excel** or **SPSS** or more complex programming languages like **C++** or **Python**.

.pull-left45[
### Pro
1. **It's free**
2. Relatively **easy**
3. **Extensibility** ([CRAN](https://cran.r-project.org/), packages)
4. **User base** (e.g., [stackoverflow](https://stackoverflow.com/))
5. [**Tidyverse**](https://www.tidyverse.org/) (`dplyr`, `ggplot`, etc.)
6. [**RStudio**](https://www.rstudio.com/)
7. **Productivity** options: [Latex](https://www.latex-project.org/), [Markdown](https://daringfireball.net/projects/markdown/), [GitHub](https://github.com/)
]

.pull-right45[
### Con
Sometimes slow and awkward, but...

[Tidyverse](https://www.tidyverse.org/)
[Rcpp](http://www.rcpp.org/), [BH](https://cran.r-project.org/web/packages/BH/index.html): Links R to C++ and high-performance C++ libraries 
[rPython](http://rpython.r-forge.r-project.org/): Links R to Python 
[RHadoop](https://github.com/RevolutionAnalytics/RHadoop/wiki): Links R to Hadoop for big data applications. 
]

---

# The almighty `tidyverse`

Among its many packages, R newly contains a collection of high-performance, user-friendly packages (libraries) known as the [tidyverse](https://www.tidyverse.org/). The tidyverse includes:
1. `ggplot2` -- creating graphics.
2. `dplyr` -- data manipulation.
3. `tidyr` -- tidying data.
4. `readr` -- read wild data.
5. `purrr` -- functional programming.
6. `tibble` -- modern data frame.

---

# Packages

.pull-left35[

R features a vast and cutting-edge collection of **packages** provided on [**CRAN**](https://cran.r-project.org/) and [**Git/GitHub**](https://github.com/hadley) by R's large and highly active user base and the work of .

```r
# To install a package
install.packages('package_name')

# load a package
library(package_name)
require(package_name)

#Note: 
# Don't forget that packages 
# must also be loaded.
```

]

.pull-right55[

<a href="https://www.rdocumentation.org/trends">
 www.rdocumentation.org/trends
 </a>

]

---

# Packages

.pull-left35[

```r
# To install a package
install.packages('package_name')

# load a package
library(package_name)
require(package_name)

#Note: 
# Don't forget that packages 
# must also be loaded.
```

]

.pull-right45[

]

---

# RStudio: R's favorite environment

Next to many useful packages, R users greatly benefit from R's integrated development environment [**RStudio**](https://www.rstudio.com/). Rstudio is a **graphical user interface** that allows you to (a) edit code, (b) run code, (c) access files and history, and (d) create plots. RStudio also helps you with **project management**, **version control** via [Github](https://github.com/), writing **reports** using [markdown](http://rmarkdown.rstudio.com/authoring_basics.html) and [knitr](https://yihui.name/knitr/), and many other aspects of working with R.

---
<div class="center_text">
 
 The 24 Lessons of the R Bootcamp
 
</div>

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Name objects using `_`
4. Objects have classes
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. <high>Everything is an object</high>
2. <high>Use `<-` to create/change objects</high>
3. <high>Name objects using `_`</high>
4. Objects have classes
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# an object called some_name
some_name <- c(1, 2, 3)

# add 2 to the object's numbers
some_name + 2
```

```
## [1] 3 4 5
```

```r
# print object
some_name
```

```
## [1] 1 2 3
```

```r
# make change permanent
some_name <- some_name + 2

# print object
some_name
```

```
## [1] 3 4 5
```
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Name objects using `_`
4. <high>Objects have classes</high>
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# an object called some_name
class(some_name)
```

```
## [1] "numeric"
```

```r
typeof(some_name)
```

```
## [1] "double"
```

```r
# an object called some_name
class(list())
```

```
## [1] "list"
```

```r
# an object called some_name
class(tibble())
```

```
## [1] "tbl_df"     "tbl"        "data.frame"
```
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Name objects using `_`
4. Objects have classes
5. <high>Everything happens through functions</high>
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# function c()
some_name <- c(1, 2, 3)

# function `+`()
some_name + 2
```

```
## [1] 3 4 5
```

```r
# function print()
some_name
```

```
## [1] 1 2 3
```

```r
# function class()
class(some_name)
```

```
## [1] "numeric"
```
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. <high>Functions have (default) arguments</high>
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# no argument
mean()
```

```
## Error in mean.default(): argument "x" is missing, with no default
```

```r
# required argument
mean(c(1, 2, 3))
```

```
## [1] 2
```

```r
# introducing NA
mean(c(1, 2, 3, NA))
```

```
## [1] NA
```

```r
# changing default to handle NA
mean(c(1, 2, 3, NA), na.rm = TRUE)
```

```
## [1] 2
```
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. <high>Functions expect certain object classes</high>
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# mean works also for logical
mean(c(TRUE, FALSE, TRUE))
```

```
## [1] 0.6667
```

```r
# but not for character
mean(c("a", "b", "c"))
```

```
## [1] NA
```

```r
# classes relevant for all arg's
mean(c(1, 2, 3), na.rm = "test")
```

```
## Error in if (na.rm) x <- x[!is.na(x)]: argument is not interpretable as logical
```
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. <high>View help files using `?`</high>
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
?mean
```
<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/help.png" width="500">
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-right5[

```r
?cor
```
<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/help_cor.png" width="500">
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. <high>Study errors and warnings</high> 
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# message - attend
basel <- type_convert(baselers)
```

```
## Parsed with column specification:
## cols(
##   sex = col_character()
## )
```

```r
# warning - attend closely
result <- mean('NA')
```

```
## Warning in mean.default("NA"): argument is not numeric or logical: returning NA
```

```r
# error - fix
lenth(1)
```

```
## Error in lenth(1): could not find function "lenth"
```

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. <high>Study errors and warnings</high> 
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
lenth(1)
```

```
## Error in lenth(1): could not find function "lenth"
```

| Error | Description|
|:------|:--------------------------------------------|
|     `'could not find function'`| Typo or package not loaded|
|     `'error in eval'`| An object is used in function that does not exist.|
| `'cannot open()'`| Typo or missing path.|
| `'no applicable method'`| Function inapplicable for type |
| package errors | Unable to install, compile, or load package. |

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. <high>Data is stored in data frames</high>
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
print(baselers)
```

```
## # A tibble: 10,000 x 20
## id sex age height weight income
## <int> <chr> <int> <dbl> <dbl> <dbl>
## 1 1 male 44 174. 113. 6300.
## 2 2 male 65 180. 75.2 10900.
## 3 3 female 31 168. 55.5 5100.
## 4 4 male 27 209. 93.8 4200.
## 5 5 male 24 177. NA 4000.
## 6 6 male 63 187. 67.4 11400.
## 7 7 male 71 152. 83.3 12000.
## 8 8 female 41 156. 67.8 7600.
## 9 9 male 43 176. 69.3 8500.
## 10 10 female 31 166. 66.3 6100.
## # ... with 9,990 more rows, and 14 more
## # variables
```
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. <high>Select variables (vectors) using `$`</high>
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# select sex veriable using $
baselers$sex
```

```
## [1] "male"   "male"   "female" "male"   "male"  
## [6] "male"   "male"   "female"
##  [ reached getOption("max.print") -- omitted 9992 entries ]
```

```r
# Wherever possible, AVOID...
baselers[['sex']]
```

```
## [1] "male"   "male"   "female" "male"   "male"  
## [6] "male"   "male"   "female"
##  [ reached getOption("max.print") -- omitted 9992 entries ]
```

```r
baselers[[2]]
```

```
## [1] "male"   "male"   "female" "male"   "male"  
## [6] "male"   "male"   "female"
##  [ reached getOption("max.print") -- omitted 9992 entries ]
```

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. <high>Use RStudio and projects</high>
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[
### Projects help...
save workspace and history &#9679; set project specific options &#9679; access files &#9679; version control &#9679; etc.
<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/projects_1.png" width="360">
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. <high>Use RStudio and projects</high>
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[
### Folder structure
Complement projects by a <high>folder structure</high> appropriate for your project.
 

 <img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/folder_structure.png">

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. <high>Use editor and shortcuts</high>
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/editor_edit.png"></img>
 
Shortcut to <high>send to console</high>: <br2>&#8984;/ctrl + &#9166; <br2><br2>
Shortcut to <high>rerun chunk</high>: <br2> &#8984;/ctrl + &#8679; + p
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. <high>First load packages and data</high>
15. Use auto-complete
16. Comment and format for readability
]

.pull-right5[

```r
# import packages
library(tidyverse)
library(yarrr)
library(lme4)

# import data
baselers <- read_delim("baselers.txt",
 delim = '\t')
```
 
### The goal is...
... to create self-contained scripts that run uninterrupted from beginning to start.
]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. <high>Use auto-complete</high>
16. Comment and format for readability
]

.pull-right55[

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. <high>Use auto-complete</high>
16. Comment and format for readability
]

.pull-right55[

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. <high>Use auto-complete</high>
16. Comment and format for readability
]

.pull-right55[

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. <high>Comment and format for readability</high>
]

.pull-right5[
## Bad

```r
mean(subset((tibble(c('a','b'),runif(1000,
0,1))),c..a....b..=='a')[,'runif.1000..0..1.'])
```

## Good

```r
# create my data.frame
my_data <- tibble('group' = c('a','b'), 
 'value' = runif(1000,0,1))

# subset data to group a
# and compute average value
my_data %>% 
  filter(group == 'a') %>%
  summarize(mean(value))
```

]

---

# Essentials: The 24 Lessons of the R Bootcamp

.pull-left4[
1. Everything is an object
2. Use `<-` to create/change objects
3. Objects have classes
4. Name objects using `_`
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. <high>Comment and format for readability</high>
]

.pull-right5[
### Short style guide

```r
# Choose appropriate names
analyze_baselers.R
trial_id

# Leave spaces around operators
var_rt <- var(rt, na.rm = TRUE)

# indent code
if (var_rt < 2){
 print('small variance')
} else {
 print('large variance')
}

# Crete sections using
# Data wrangling section ---------
```
See also <a href="http://style.tidyverse.org/">style.tidyverse.org/</a>
]

---

# Essentials: Lesson 17

.pull-left4[
<high>Struggle, ask for help, struggle, ...</high>
]
.pull-right5[

<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/struggle.png" width="420">

]

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# Downloads

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# Interactive session

<high>Open up Rstudio...</high>