The whole game 👾

# The whole game <br> 👾

---

layout: true
  
<div class="my-footer">
<span>
<a href="http://bit.ly/bootcamp-nuigalway" target="_blank">bit.ly/bootcamp-nuigalway</a>
</span>
</div>

---

# Welcome!

---

## About me

.pull-left[
<img src="img/mine_circle.png" width="80%" style="display: block; margin: auto;" />
]
.pull-right[
__Mine Çetinkaya-Rundel__
- Senior Lecturer, University of Edinburgh
- Data Scientist & Professional Educator, RStudio
- Associate Professor of the Practice, Duke University

.midi[
🔗  [mine-cr.com](http://mine-cr.com)  
✍️  [citizen-statistician.org](http://citizen-statistician.org)  
🐦  [@minebocek](https://twitter.com/minebocek)  
🔘  she/her  
]
]

---

## About you?

---

## Logistics

- Everything in one place: [bit.ly/bootcamp-nuigalway](http://bit.ly/bootcamp-nuigalway)
- RStudio Cloud: [rstd.io/dsbox-cloud](https://rstd.io/dsbox-cloud)
- Asking for help: Type in chat (but if I don't see it, feel free to interrupt!)

---

# Software

---

---

---

---

# Data science life cycle

---

---

---

---

---

---

---

---

---

---

---

---

# Let's dive in!

---

---

---

---

---

---

---

---

---

---

---

---

---

---

---

---

- Go to [rstd.io/dsbox-cloud](https://rstd.io/dsbox-cloud) and join the workspace.
- On RStudio Cloud, start the assignment called `AE 01a - UN Votes` or `AE 01a - COVID`.
- In the Files pane in the bottom right corner, spot the file called `unvotes.Rmd` (or `covid.Rmd`). Open it, and then click on the "Knit" button.
- Go back to the file and change your name on top (in the `yaml` -- we'll talk about what this means later) and knit again.
- Change the country names to those you're interested in. Your spelling and capitalization should match how the countries appear in the data, so take a peek at the Appendix to confirm spelling. Knit again. Voila, your first data visualization!
]

---

# Data in the wild

---

---

---

---

---

---

## R

- R can be used as a calculator.

```r
8738787213 / 1653
```

```
## [1] 5286623
```

- The most commonly used data type in R is data frames, where each row represents an observation, and each column a variable.

```
##         name      start        end      party
## 1 Eisenhower 1953-01-20 1961-01-20 Republican
## 2    Kennedy 1961-01-20 1963-11-22 Democratic
## 3    Johnson 1963-11-22 1969-01-20 Democratic
## 4      Nixon 1969-01-20 1974-08-09 Republican
## 5       Ford 1974-08-09 1977-01-20 Republican
## 6     Carter 1977-01-20 1981-01-20 Democratic
```

---

## R

- We use the `$` operator to access a variable within a data frame.

```r
presidential$name
```

```
##  [1] "Eisenhower" "Kennedy"    "Johnson"    "Nixon"      "Ford"       "Carter"     "Reagan"    
##  [8] "Bush"       "Clinton"    "Bush"       "Obama"
```

- Functions are (often) verbs, followed by what they will be applied to in parentheses.

```r
do_this(to_this)
do_that(to_this, to_that, with_those)
```

---

## R

- In R, the fundamental unit of shareable code is the package.
--

- As of August 2020, there are over 16,000 packages available on the **C**omprehensive **R** **A**rchive **N**etwork (CRAN), the public clearing house for R packages. Source: [r-pkg.org](https://www.r-pkg.org/).
--

- This huge variety of packages is one reason why R is so successful: the chances are that someone has already solved a problem that you’re working on, and you can benefit from their work by downloading their package.
--

- Using R packages:
  - Install them from CRAN with `install.packages("x")`
  - Use them in R with `library(x)`
  - Get help on them with package `?x` and `help(package = "x")`

---

---

## RStudio

---

---

## R Markdown

---

## How will we use R Markdown?

- Every "your turn" exercise is an R Markdown document
- You'll always have a template R Markdown document to start with
- The amount of scaffolding in the template will decrease over the bootcamp

---

---

## tidyverse

All packages share an underlying design philosophy, grammar, and data structures.
]
.pull-right[
<img src="img/tidyverse-packages.png" width="100%" style="display: block; margin: auto;" />
]

---

---

## Reading help files

.pull-left[
You can get help on any function by typing the function name in the Console with a `?` before it:

```r
?mean
```
]
.pull-right[
<img src="img/r-help.png" width="100%" style="display: block; margin: auto;" />
]

---

## Package help

- **Many** modern packages have user friendly web pages with function descriptions, code examples, and vignettes (problem-oriented long form articles that walk you through features of the package), e.g. [ggplot2.tidyverse.org](https://ggplot2.tidyverse.org/).
--

- **All** packages on CRAN have a dedicated with high-level package documentation such as a description, dependencies, etc. as well as a link to a PDF reference manual, e.g.  [cran.r-project.org/web/packages/ggplot2](https://cran.r-project.org/web/packages/ggplot2/index.html).
--

- **Some** packages also have cheatsheets which can be quite handy! [rstudio.com/resources/cheatsheets](https://rstudio.com/resources/cheatsheets/)
  
.alert[
I recommend using the package websites when available since they display output of code in the examples whereas the help in R and reference manual does not.
]

---

.your-turn[
Take a few minutes in breakout sessions to come up with a list of 1-2 questions you would like clarified before we move on to the next module.
]