Introduction to R the Tidy Way

# Introduction to R the Tidy Way
## R and RStudio Basics
### Mine Dogucu
### 2020-03-05

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<div class="my-header"></div>

<div class="my-footer"> 
 CC BY-SA <a href="https://mdogucu.ics.uci.edu">Mine Dogucu</a></div>

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## License

More information can be found [here](https://creativecommons.org/licenses/by-sa/2.5/)

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## RStudio Cloud

- Log into RStudio Cloud using the link on the whiteboard

- From Spaces on the left navigation bar intro-r-tidy should be selected.

- In this workspace, make a copy of the pre-lunch project.

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## No Temporary Project

Your project should NOT be temporary. If it says so then save a permanent copy. If you already made a copy you should be good.

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## .Rmd

- On the lower right pane in the `Files` tab open the `sample-rmarkdown.Rmd` file.

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## Knitting

- Click the Knit button to knit this document and then we will talk about R Markdown documents.

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## Our very own .Rmd

- Open `1_basics.Rmd`
- I will do a live demo

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## Demo - Adding Chunks

## Demo - Run Code

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## Demo - Defining Objects

```r
birth_year <- 1950 # note the change in the environment

age <- 2020 - birth_year

age 
```

```
## [1] 70
```

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## Demo - Defining Objects

R is case sensitive.

```r
Age
```

```
## Error in eval(expr, envir, enclos): object 'Age' not found
```

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## Demo - Defining Objects

```r
name_p <- c("Molly", "Zainab", "Mohsen") #c is a combine function 
# strings come in quotes

kid_p <- c(2, 3, 2) 
```

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## Demo - Defining Objects

```r
data.frame(name = name_p,
           kid = kid_p)
```

```
##     name kid
## 1  Molly   2
## 2 Zainab   3
## 3 Mohsen   2
```

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## Vocabulary

do(something)

do is a function something is an argument

do(something colorful)

do is a function something is an argument colorful is an argument

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## Looking at Data

Get to know the `candy_ranking` data.

- Clicking on the data frame in the Environment.
- Clicking on the blue button. 
- Using `glimpse()`

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## Looking at Data - `glimpse()`

`glimpse()` shows variables and some data values but it is not in the usual row-column format but rather flipped version of this with additional information about the variables and the data frame.

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## Looking at Data - `glimpse()`

```r
glimpse(candy_rankings)
```

```
## Observations: 85
## Variables: 13
## $ competitorname   <chr> "100 Grand", "3 Musketeers", "One dime", "One...
## $ chocolate        <lgl> TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, ...
## $ fruity           <lgl> FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALS...
## $ caramel          <lgl> TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE...
## $ peanutyalmondy   <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE...
## $ nougat           <lgl> FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE...
## $ crispedricewafer <lgl> TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALS...
## $ hard             <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FAL...
## $ bar              <lgl> TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, ...
## $ pluribus         <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FAL...
## $ sugarpercent     <dbl> 0.732, 0.604, 0.011, 0.011, 0.906, 0.465, 0.6...
## $ pricepercent     <dbl> 0.860, 0.511, 0.116, 0.511, 0.511, 0.767, 0.7...
## $ winpercent       <dbl> 66.97173, 67.60294, 32.26109, 46.11650, 52.34...
```

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class: center, middle

## More on Candy Rankings

[The Ultimate Halloween Candy Power Ranking](https://fivethirtyeight.com/features/the-ultimate-halloween-candy-power-ranking/)

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## Schedule for the Day

__08:45 - 09:00 Introduction__  
__09:00 - 09:15 Getting to Know the Basics__  
09:15 - 10:15 Data Visualization  
10:15 - 10:30 Break  
10:30 - 12:00 Data Wrangling  
12:00 - 01:00 Lunch  
01:00 - 01:30 Working Locally With R  
01:30 - 02:00 Dealing with Datasets  
02:00 - 02:30 Case Study  
02:30 - 02:45 Break  
02:45 - 03:30 Modeling  
03:30 - 04:00 Everything I did not have time to cover