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# <div class="line-block">Getting Started in R<br />
an introduction to data analysis and visualisation</div>
## Welcome!
### Réka Solymosi & Sam Langton & Emily Buehler
### 1 July 2019

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# Welcome!

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## About us

@r_solymosi

@sh_langton

@emily_buehler

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## About you

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## About the course

**Schedule**

|         | Slot   | Module                                                | 
|:--------|:-------|:------------------------------------------------------|
| **1**   | Mon pm | Intro                                   | 
| **2.1** | Tue am | Basics                                   | 
| **2.2** | Tue pm | Import data                          | 
| **3.1** | Wed am | Tidy data                           | 
| **3.2** | Wed pm | Transform data                    | 
| **4.1** | Thu am | Visualise data                     |
| **4.2** | Thu pm | Model data                   |
| **5**   | Fri am | Reporting data |

<br>

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## About the course

By the end of the week you will be able to:

- be able to read and write basic R code
- read your data into R Studio
- tidy (prep) your data for analysis
- filter and subset data
- summarise and create new variables
- visualise your data
- model your data
- presenting results in a report

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## Why R?

- growing popularity
 - reproducable
 - learn to code
 - diverse
 - open source
 - community driven

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## Growing popularity

source: http://r4stats.com/articles/popularity/

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## Growing popularity

source: http://r4stats.com/articles/popularity/

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## Growing popularity

<img src="https://i0.wp.com/r4stats.com/wp-content/uploads/2017/02/Fig-1a-IndeedJobs-2017.png?w=650" height="450px" />
  
source: http://r4stats.com/articles/popularity/

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## Reproducible

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## Reproducible

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## Reproducible: the point

- People are very opinionated about it
- Replication and transparency is a key debate in research
- The need for replication is blind to research discipline
- One day we might not have a choice in the matter
- Either way, it will make your life a lot easier!

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## Diverse: Inferential stats

```r
library(stats)
```

```r
mean()
sd()
chisq.test()
t.test()
aov()
glm()
```

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## Diverse: Plots

```r
plot(cars$speed, cars$dist)
```

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## Diverse: Plots

```r
library(ggplot2)
```

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## Diverse: Plots

```r
library(waffle)
```

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## Diverse: Maps

```r
library(ggplot2) ; library(sf)
```

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## Diverse: Stylised Maps

```r
library(ggplot2) ; library(sf) # + open code
```

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## Diverse: Sequence analysis

```r
library(TraMineR)
```

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## Diverse: Spatial autocorrelation

```r
library(spdep)
```

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## Diverse: Aoristic analysis

```r
library(aoristic)
```

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## Diverse: Social network analyis

```r
library(igraph)
```

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## Diverse: Text mining

```r
library(tidytext) ; library(geniusR)
```

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## Diverse: Text analysis

```r
library(tidytext) ; library(geniusR)
```

![](https://i2.wp.com/www.johnmackintosh.com/img/2018-01-28-album-word-correlations-original.png?w=456&ssl=1)

[Source: John MacKintosh on R bloggers](https://www.r-bloggers.com/hardwired-for-tidy-text/)

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## Diverse: Text analysis

```r
library(tidytext) 
```

[Source: Jakub Glinka on R bloggers](https://www.r-bloggers.com/sentiment-analysis-of-the-lord-of-the-rings-with-tidytext/)

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## Diverse: interactive maps

```r
library(tmap)
```

![](img/ME_gif.gif)

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## Diverse: Shiny apps to visualise voting

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## Open tools

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## Open source

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## Open source

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## Community driven

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## Community driven

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## Community driven

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## Community driven

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## Community driven

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## Community driven

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## Community driven

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## Community driven

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## Community driven

Top resources: 
 - Stack Overflow
 - RPubs
 - R4DS
 - Twitter

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## Community driven

<img src="img/twitter_profiles.png" width="700px" />
 
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## Join the community

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## After coffee

- get to know R Studio 
- learn about packages
- open, edit and run an R script
- save the output