Introduction

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# Introduction
### Claus O. Wilke
### last updated: 2022-01-17

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## Why Data Visualization?

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<img src = "introduction_files/Data_science_venn.svg", width = 60%></img>
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## Why Data Visualization?

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<img src = "introduction_files/Data_visualization_venn.svg", width = 60%></img>
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## Why R?

???

The R logo [is distributed](https://www.r-project.org/logo/) under the terms of the Creative Commons Attribution-ShareAlike 4.0 International license ([CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)).

RStudio hex stickers [are distributed](https://github.com/rstudio/hex-stickers) under [CC0.](https://github.com/rstudio/hex-stickers/blob/master/LICENSE.md)

<img src = "introduction_files/package-hexlogos.svg", width = 35%, style = "position:absolute; top: 5%; left: 55%;"></img>
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## Why me?

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https://clauswilke.com/dataviz
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## Why me?

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<img src = "introduction_files/ggplot2-website-title.png", width = 60%></img>
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## The first core concept: Markdown

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## The first core concept: Markdown

**Input:**

.small-font[
```
This is a sentence in Markdown, containing `code`, **bold text**,
and *italics*.
```
]

**Output:**

.small-font[
This is a sentence in Markdown, containing `code`, **bold text**, and *italics*.
]

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## The first core concept: Markdown

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**Input:**

.small-font[
```
## 1 Introduction

Data visualization is part art 
and part science. The challenge 
is to get the art right without
getting the science wrong and 
vice versa.
```
]]

.pull-right[
**Output:**

## 1 Introduction

Data visualization is part art 
and part science. The challenge 
is to get the art right without
getting the science wrong and 
vice versa.

]

.absolute-bottom-right[
Text taken from: C. O. Wilke, [Fundamentals of Data Visualization](https://clauswilke.com/dataviz/introduction.html)
]

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## R Markdown combines Markdown and R code

**Input:**

.small-font[

````
The function `rnorm()` creates normal variates.
```{R}
rnorm(5) # create 5 normal variates
```
````
]

**Output:**

.small-font[

The function `rnorm()` creates normal variates.

```r
rnorm(5) # create 5 normal variates
```

```
[1] -0.7007392 -0.5225379  0.2926112 -0.4582357  0.7565365
```
]

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## Using R Markdown in RStudio

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## Knitting an R Markdown file

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<img src = "introduction_files/RStudio-markdown.png", width = 80%, style = "position:relative; top:-52px;"></img>
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## Knitting an R Markdown file

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<img src = "introduction_files/RStudio-markdown-edited.png", width = 80%, style = "position:relative; top:-52px;"></img>
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## Knitting an R Markdown file

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<img src = "introduction_files/markdown-knitted.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

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## Further reading

- [R Markdown tutorial](https://rmarkdown.rstudio.com/lesson-2.html)
- [R Markdown cheatsheet](https://github.com/rstudio/cheatsheets/raw/main/rmarkdown.pdf)
- [R Markdown book](https://bookdown.org/yihui/rmarkdown/)