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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>A {fun} Intro to R Programming</title>
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---
class: banner
---
name: title-slide
class: primary
#.fancy[A {fun} Intro to R Programming]
###.fancy[The basics,<br>data wrangling,<br>and more!]
<br>
Fabio Votta
[<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:black;overflow:visible;position:relative;"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg> @favstats](http://twitter.com/favstats)<br>
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August 14 2023
.fifty[Link to slides: [favstats.github.io/ds3_r_intro](https://favstats.github.io/ds3_r_intro)]
---
### Your friendly neighborhood R Instructor
.leftcol40[
<img src="https://github.com/favstats/WarwickSpringCamp_QTA/blob/main/docs/slides/day1/images/me.jpg?raw=true" style="width: 90%" />
]
.rightcol60[
+ Ph.D. Candidate in Political Communication at University of Amsterdam
+ Passionate about R and Data Science
+ I love to travel
+ I enjoy and (occasionally) create R memes
<center>
<img src="https://pbs.twimg.com/profile_banners/866598352577867776/1495448334/1500x500" width="60%">
.font60[
[twitter.com/rstatsmemes](https://twitter.com/rstatsmemes)
</center>
]
]
---
class: middle, center
## But enough of me
### Let's learn something about .blue[you]!
<center>
<img src="images/mentimeter_qr_code.png" width="20%">
</center>
Go to `menti.com` and type in the code: 6410 5559
or visit this website: [menti.com/aloxtiea8mx3](https://www.menti.com/aloxtiea8mx3)
---
<div style='position: relative; padding-bottom: 56.25%; padding-top: 35px; height: 0; overflow: hidden;'><iframe sandbox='allow-scripts allow-same-origin allow-presentation' allowfullscreen='true' allowtransparency='true' frameborder='0' height='315' src='https://www.mentimeter.com/app/presentation/al367t83vwruzc9sy2tu65mrpwjfqqtt/embed' style='position: absolute; top: 0; left: 0; width: 100%; height: 100%;' width='420'></iframe></div>
---
### It's not unusual to struggle at first but it gets better!
<img src="images/r_first_then_new.png" width="80%" style="display: block; margin: auto;" />
<!-- {width=50%} -->
.fifty[Illustration adapted from [Allison Horst](https://twitter.com/allison_horst)]
--
+ My experience is that this stuff isn't super easy... but it gets better!
--
+ Awesome inclusive community that is always ready to help
+ Active blogosphere with use cases and examples
---
### A Note on Live-Coding
<img src="https://cdn.myportfolio.com/45214904-6a61-4e23-98d6-b140f8654a40/118ae091-4329-4382-8cb8-012035593dfc_rw_1920.png?h=29e95985575f458232d53ad93d1860cb" width="80%" style="display: block; margin: auto;" />
---
## Overview
+ R Basics
+ Operators
+ Objects (inc. vectors)
+ Functions
+ Exercises
+ Data frames
`\(\text{B R E A K at 2pm (CET) - (5:30 PM IST) - (8:00 PM CST)}\)`
+ Data Manipulation
+ the tidyverse and friends
+ `janitor`
+ `tidyr`
+ `dplyr`
+ Exercises
---
<!-- #### What is <img src="images/Rlogo.svg" width="30px" inline-block/> ? -->
#### What is <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="30px"/>?
R is a .fancy[statistical] programming language developed for data analysis and visualization.
#### What is <img src="images/rstudio.png" style="display: inline-block; margin: 0"; width="80px"/>?
RStudio is an IDE (Integrated Development Environment).
* Write, save and open R Code (.R/.Rmd files)
* Provides syntax-highlighting and auto-completion & much more
--
# But why learn <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="60px"/>?
<!--  -->
---
<!-- #### What is <img src="images/Rlogo.svg" width="30px" inline-block/> ? -->
.leftcol[
#### Why learn <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="30px"/>?
<!--  -->
+ Amazing Community .forty[(but I already said that)]
<!-- + Outstanding repertoire of statistical & computational methods -->
<!-- -- -->
<!-- + Integrates well with other programming languages (like Python) -->
<!-- -- -->
<!-- + Beautiful Data Visualization with `ggplot2` and more -->
]
.rightcol[
.fifty[Artist: [Allison Horst](https://github.com/allisonhorst)]
]
---
<!-- #### What is <img src="images/Rlogo.svg" width="30px" inline-block/> ? -->
.leftcol60[
#### Why learn <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="30px"/>?
<!--  -->
+ Amazing Community .forty[(but I already said that)]
+ Data wrangling is accessible & fun
<!-- + Outstanding repertoire of statistical & computational methods -->
<!-- -- -->
<!-- + Integrates well with other programming languages (like Python) -->
<!-- -- -->
<!-- + Beautiful Data Visualization with `ggplot2` and more -->
]
.rightcol40[
<br>
.fifty[Artist: [Allison Horst](https://github.com/allisonhorst)]
]
---
.leftcol60[
#### Why learn <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="30px"/>?
<!--  -->
+ Amazing Community .forty[(but I already said that)]
+ Data wrangling is accessible & fun
+ Outstanding repertoire of statistical & computational methods
<!-- + Integrates well with other programming languages (like Python) -->
<!-- + Beautiful Data Visualization with `ggplot2` and more -->
]
.rightcol40[
<br>
.fifty[ [easystats](https://github.com/easystats/easystats) packageverse for statistical analysis.]
]
---
.leftcol60[
#### Why learn <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="30px"/>?
<!--  -->
+ Amazing Community .forty[(but I already said that)]
+ Data wrangling is accessible & fun
+ Outstanding repertoire of statistical & computational methods
+ Integrates well with other programming languages
<!-- + Beautiful Data Visualization with `ggplot2` and more -->
]
.rightcol40[
<br>
.fifty[ [reticulate](https://github.com/easystats/easystats) integrates Python into R]
]
---
.leftcol60[
#### Why learn <img src="images/Rlogo.svg" style="display: inline-block; margin: 0"; width="30px"/>?
<!--  -->
+ Amazing Community .forty[(but I already said that)]
+ Data wrangling is accessible & fun
+ Outstanding repertoire of statistical & computational methods
+ Integrates well with other programming languages
+ Beautiful data visualization with `ggplot2`
<br>
<br>
.right[.fifty[Data visualization by [Cédric Scherer](https://www.cedricscherer.com/)]]
]
.rightcol40[
]
---
.leftcol75[
### This workshop is held in .green[Rmarkdown]
]
.rightcol25[
<img src="https://rmarkdown.rstudio.com/docs/reference/figures/logo.png" width="80" height="100" style="display: block; margin: auto 0 auto auto;" />
]
<center>
<img src="https://github.com/allisonhorst/stats-illustrations/blob/main/rstats-artwork/rmarkdown_wizards.png?raw=true" style="width: 76%" />
</center>
.fifty[Artist: [Allison Horst](https://github.com/allisonhorst)]
---
.leftcol75[
## .green[Rmarkdown]
]
.rightcol25[
<img src="https://rmarkdown.rstudio.com/docs/reference/figures/logo.png" width="100" height="120" style="display: block; margin: auto 0 auto auto;" />
]
.leftcol[
<center>
<img src="https://github.com/allisonhorst/stats-illustrations/blob/main/rstats-artwork/rmarkdown_wizards.png?raw=true" style="width: 100%" />
</center>
.fifty[Artist: [Allison Horst](https://github.com/allisonhorst)]
]
.rightcol[
* create *documents* with R
* mix code, text and graphs as you like
* write your thesis, create slides, automated reports, dashboards and interactive web apps all from within [Rmarkdown](https://rmarkdown.rstudio.com/docs/articles/rmarkdown.html)
]
---
## R vs. Rmarkdown
.seventy[
There are two (main) ways you can create scripts in R
]
.pull-left[
.seventy[
R scripts (file ending `.R`):
]
]
.pull-right[
.seventy[
Rmarkdown (`.Rmd`) scripts produce HTML:
]
<img src="images/rmarkown_html.png" style="width: 72%" />
]
---
## R vs. Rmarkdown
.seventy[
There are two (main) ways you can create scripts in R
]
.pull-left[
.seventy[
R scripts (file ending `.R`):
]
]
.pull-right[
.seventy[
Rmarkdown (`.Rmd`) scripts produce PDF:
]
]
---
## R vs. Rmarkdown
.seventy[
There are two (main) ways you can create scripts in R
]
.pull-left[
.seventy[
R scripts (file ending `.R`):
]
]
.pull-right[
.seventy[
Rmarkdown (`.Rmd`) scripts produce so much more:
]
slides (*like the ones you are looking at right now!*), automated reports, dashboards and interactive web apps
]
---
## We'll switch to RStudio in a moment
> The next few slides will have a couple of links that you may want to follow. You can find **all** materials of this workshop, including links, in this GitHub repository: [tinyurl.com/ds3repo](https://github.com/favstats/ds3_r_intro)
.font80[
Hopefully at this point you have already followed the **pre-workshop instructions:**
[tinyurl.com/ds3prep](https://favstats.github.io/ds3_r_intro/prep/instructions.html)
*Once in RStudio, feel free to code along with me, changing a few bits here and there and see how results change.*
]
---
## Alternatives to local RStudio
If you cannot install R or RStudio on your computer for any reason, you have two options to follow along:
+ **Binder**
Simply start a **Binder** instance which will create a session of RStudio in your Browser (may take a little bit):
[tinyurl.com/ds3binder](https://tinyurl.com/ds3binder)
[](https://mybinder.org/v2/gh/favstats/ds3_r_intro/rstudio?urlpath=rstudio)
> Note: If you are using Binder don't forget to download the files before you close out the session because otherwise anything you added will be lost!
---
## Alternatives to local RStudio
+ **Google Colab**
Google Colab instantaneously runs Jupyter Notebooks in your browser with an R Kernel.
+ [Part I (R Basics): tinyurl.com/ds3rintro1](https://colab.research.google.com/drive/1dLsdGbkvgn1JbWgsy9Z-pFmPd_2MG4Xu?usp=sharing)
+ [Part II (Data Manipulation with the `tidyverse`): tinyurl.com/ds3rintro2](https://colab.research.google.com/drive/14CRElnKewnp5MnlxhqVu6OOcIXd-Bkaj?usp=sharing)
---
## Workshop files
Please download the workshop files from here: [https://tinyurl.com/ds3files](https://www.dropbox.com/sh/jievqgwl43nwnbf/AADhoYQW5oMZ-JygK7aNklHra?dl=0).
The link will download a `.zip` file. Extract it to **its own folder**.
Now double-click on **ds3_intro.Rproj**
---
## Within RStudio
<!-- ## RStudio Tour -->
<!-- <center> -->
<!-- <img src="https://bookdown.org/ageraci/STAT160Companion/images/rstudiopanes.png" style="width: 82%" /> -->
<!-- </center> -->
<!-- --- -->
<!-- ## RStudio Tour -->
<!-- * Program pane -->
<!-- * Shows R Files, typically .R or .Rmd -->
<!-- * Environment pane -->
<!-- * All the objects that you created during your session -->
<!-- * Console pane -->
<!-- * For executing short snippets of R code -->
<!-- * Files pane -->
<!-- * Gives access to files, but also help, and plots -->
<!-- --- -->
---
class: inverse, middle, center
# R Basics
--
### Math Operators
---
### Math Operators
At its core R is just a fancy *calculator*
You can do:
`+` addition
`-` subtraction
`*` multiplication
`/` division
`^` exponentiate
---
### Math Operators
At its core R is just a fancy *calculator*
### `+` addition
.details[
```r
15 + 5
```
```
#> [1] 20
```
]
--
### Mixing operators
.details[
```r
(15 + 5) / (2 * 5)
```
```
#> [1] 2
```
]
---
## Short excourse: a new data set appears..
But adding up numbers for no reason is no fun.
--
That's why we will use a data set about .fancy[animals] to learn some R Basics.
.leftcol45[
<img src="images/kisspng-animal-clip-art-portable-network-graphics-illustra-cartoon-animal-transparent-amp-png-clipart-free-5c7ccdbb1c9c98.7009291415516830031172.png" style="width: 100%" />
]
.rightcol55[
[Animal Ageing and Longevity Database](https://www.johnsnowlabs.com/marketplace/the-animal-aging-and-longevity-database/)
Data on over 4200 animals.
Information on age of maturity, gestation or incubation periods but also **longevity (in years)**.
]
---
## Animal Ageing and Longevity Database
Say we want to know how old an animal is in *human years*.
--
We can use the following simple formula to determine that:
<br>
`$$\frac{\text{Maximum lifespan human}}{\text{Maximum lifespan non-human animal}} = \text{animal to human years ratio}$$`
<br>
*Note: This is just a **very rough** way to determine the conversion ratio. It is **much more** complicated in [reality](https://www.akc.org/expert-advice/health/how-to-calculate-dog-years-to-human-years/).*
---
## Animal Ageing and Longevity Database
.leftcol[
| Animal | Maximum Lifespan |
| --- | --- |
| Human | 122.5 |
| Domestic dog | 24.0 |
| Domestic cat | 30.0 |
| American alligator | 77.0 |
| Golden hamster | 3.9 |
| King penguin | 26.0 |
| Lion| 27.0 |
| Greenland shark | 392.0 |
| Galapagos tortoise | 177.0 |
]
.rightcol[
| Animal | Maximum Lifespan |
| --- | --- |
| African bush elephant | 65.0 |
| California sea lion | 35.7 |
| Fruit fly | 0.3 |
| House mouse | 4.0 |
| Giraffe | 39.5 |
| Wild boar | 27.0 |
Source: [Animal Ageing and Longevity Database](https://www.johnsnowlabs.com/marketplace/the-animal-aging-and-longevity-database/)
]
---
### Math Operators
Say we want to know how old a dog is in *human years*.
--
The observed maximum lifespan of a human is 122.5 years. For dogs it is 24.
--
.details[
```r
122.5/24
```
```
#> [1] 5.104167
```
]
So for every year a human ages, a dog "ages" 5.1 human years. How old is a 15 year old dog in human years?
.details[
```r
5.104167*15
```
```
#> [1] 76.56251
```
]
---
## So many numbers..
Now it can be quite tedious to juggle all those numbers around.
Especially if we want to keep reusing numbers we calculated before.
--
Here to simplify that process are:
**Objects**
---
class: inverse, middle, center
# R Basics
### R Objects
---
## R Objects
You can think of R objects as *saving information*, for example simple numbers or just plain text.
Once saved we can recall it whenever we want by just running the name of the object.
--
> Everything that exists in R is *.red[an object]*. .fifty[~John M. Chambers]
--
We create R objects by using the assignment operator:
<center>
.large[**`<-`**]
</center>
.right[
.fifty[You can also assign with the **`=`** sign but we will not be using this here.]
]
---
## R Objects
Here is an example:
```r
human_lifespan <- 122.5
dog_lifespan <- 24
```
If we now run the respective objects we retrieve the saved numbers.
.details[
```r
human_lifespan
```
```
#> [1] 122.5
```
]
.details[
```r
dog_lifespan
```
```
#> [1] 24
```
]
---
## R Objects
Now we can perform the same calculation as before but this time using objects!
```r
dogs_to_human <- human_lifespan / dog_lifespan
```
The object `dogs_to_human` now holds the dog to human years conversion ratio.
--
*Now* we ask again: how old is a 15 year old dog in human years?
.details[
```r
dogs_to_human*15
```
```
#> [1] 76.5625
```
]
---