Tidy Data

class: title-slide, center

6

# Tidy Data

## Tidy Data Science with the Tidyverse and Tidymodels

### W. Jake Thompson

#### [https://tidyds-2021.wjakethompson.com](https://tidyds-2021.wjakethompson.com) &#183; [https://bit.ly/tidyds-2021](https://bit.ly/tidyds-2021)

.footer-license[*Tidy Data Science with the Tidyverse and Tidymodels* is licensed under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).]

<div style = "position:fixed; visibility: hidden">
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`$$\require{color}\definecolor{blue}{rgb}{0, 0.623529411764706, 0.717647058823529}$$`
</div>

---
class: your-turn

# Your turn 0

.big[
* Open the R Notebook **materials/exercises/06-tidy.Rmd**
* Run the setup chunk
]

---
background-image: url(images/tidy/applied-ds-tidy.png)
background-position: center 60%
background-size: 85%

# .nobold[(Applied)] Data Science

---
name: tidy-tools
class: center middle

# tidy tools

---
# Tidy tools

Functions are easiest to use when they are:

1\. **Simple**: They do one thing, and they do it well.

2\. **Composable**: They can be combined with other functions for multi-step operations.

3\. **Smart**: They can use R objects as input.

Tidy functions do these things in a specific way.

---
# Tidy tools

Functions are easiest to use when they are:

1\. **Simple**: They do one thing, and they do it well.

2\. **Composable**: They can be combined with other functions for multi-step operations.

.fade[
3\. **Smart**: They can use R objects as input.
]

Tidy functions do these things in a specific way.

---
# Simple

.big[
They do one thing, and they do it well.

**`filter()`** &#8211; extract cases  
**`arrange()`** &#8211; reorder cases  
**`group_by()`** &#8211; group cases  
**`select()`** &#8211; extract variables  
**`mutate()`** &#8211; create new variables  
**`summarize()`** &#8211; summarize variables
]

---
# Composable

.big[
They can be combined with other functions for multi-step operations.

Each `dplyr` function takes a data frame as its first argument and returns a data frame. As a result, you can directly pipe the output of one function into the next.
]

---
name: tidy-data
class: center middle

# tidy data

---
class: center middle

<blockquote>
.huge[Data are not just numbers, they are numbers with a context.]
.right[ <cite> &#8211; [George Cobb and David Moore (1997)](https://doi.org/10.2307/2975286) </cite>]
</blockquote>

---
class: pop-quiz

# Consider

What are the variables in this data set?

---
class: pop-quiz

# Consider

What are the variables in this data set?

---
class: pop-quiz

# Consider

What are the variables in this data set?

---
class: pop-quiz

# Consider

What are the variables in this data set?

---
# This isn't tidy

What are the variables in this data set?

---
class: center middle

<blockquote>
.huge[Data comes in many format, but R prefers just one: tidy data.]
.right[ <cite> &#8211; Garrett Grolemund </cite>]
</blockquote>

---
# Tidy data

.pull-left[
<img src="images/tidy/tidy-data.png" width="100%" style="display: block; margin: auto;" />
]

.pull-right[
A data set is **tidy** if:

1. Each .blue[**variable**] is in its own .blue[**column**].

2. Each .dark-yellow[**case**] is in its own .dark-yellow[**row**].

3. Each .pink[**value**] is in its own .pink[**cell**].
]

---
class: your-turn

# Your turn 1

.big[
Is **`bp_systolic`** tidy? What are the variables?
]

---
class: your-turn

.panelset[
.panel[.panel-name[`bp_systolic`]

```r
bp_systolic
#> # A tibble: 3 x 4
#> subject_id time_1 time_2 time_3
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1 120 118 121
#> 2 2 125 131 NA
#> 3 3 141 NA NA
```
]

.panel[.panel-name[`bp_systolic2`]

```r
bp_systolic2
#> # A tibble: 6 x 3
#> subject_id time systolic
#> <dbl> <dbl> <dbl>
#> 1 1 1 120
#> 2 1 2 118
#> 3 1 3 121
#> 4 2 1 125
#> 5 2 2 131
#> 6 3 1 141
```
]
]

???
Three variables: subject, blood pressure, time point

---
class: your-turn

# Your turn 2

.big[
Using **`bp_systolic2`** with `group_by()` and `summarize()`:

1. Find the average systolic blood pressure for each subject.

2. Find the last time each subject was measured.
]

---
class: your-turn

```r
bp_systolic2 %>%
 group_by(subject_id) %>%
 summarize(avg_sys = mean(systolic),
 last_measurement = max(time))
#> # A tibble: 3 x 3
#> subject_id avg_sys last_measurement
#> <dbl> <dbl> <dbl>
#> 1 1 120. 3
#> 2 2 128 2
#> 3 3 141 1
```

---
class: center middle

<blockquote>
.huge[Tidy datasets are all alike, but every messy dataset is messy in its own way.]
.right[ <cite> &#8211; [Hadley Wickham (2014)](https://doi.org/10.18637/jss.v059.i10) </cite>]
</blockquote>

---
<div class="hex-book">
 <a href="https://tidyr.tidyverse.org">
 <img class="hex" src="images/hex/tidyr.png">
 </a>
 <a href="https://r4ds.had.co.nz/tidy-data.html">
 <img class="book" src="images/books/r4ds-tidy-data.png">
 </a>
</div>

---
# `tidyr` verbs

.left-column[
<img src="images/tidy/pivot-longer.png" height="70px">
]

.right-column.center[
Move column names into values with **`pivot_longer()`**
]

---
# `tidyr` verbs

.left-column[
<img src="images/tidy/pivot-longer.png" height="70px">



<img src="images/tidy/pivot-wider.png" height="70px">
]

.right-column.center[
Move column names into values with **`pivot_longer()`**




Move values into column names with **`pivot_wider()`**
]

---
# `tidyr` verbs

.left-column[
<img src="images/tidy/pivot-longer.png" height="70px">



<img src="images/tidy/pivot-wider.png" height="70px">



<img src="images/tidy/separate.png" height="70px">
]

.right-column.center[
Move column names into values with **`pivot_longer()`**




Move values into column names with **`pivot_wider()`**





Split a column with **`separate()`**
]

---
# `tidyr` verbs

---
name: pivot-longer
class: center middle

# `pivot_longer()`

---
# Toy data for practice

```r
cases
#> # A tibble: 3 x 4
#> country `2011` `2012` `2013`
#> <chr> <dbl> <dbl> <dbl>
#> 1 FR 7000 6900 7000
#> 2 DE 5800 6000 6200
#> 3 US 15000 14000 13000
```

---
class: pop-quiz

# Consider

.big[
Discuss in the chat: What are the variables in the **`cases`** data set?
]

---
class: pop-quiz

# Consider

.big[
What are the variables in the **`cases`** data set?
]

???

Variable 1: Country

---
class: pop-quiz

# Consider

.big[
What are the variables in the **`cases`** data set?
]

???

Variable 2: Year

---
class: pop-quiz

# Consider

.big[
What are the variables in the **`cases`** data set?
]

???

Variable 3: cases

---
class: your-turn

# Your turn 3

.big[
On a sheet of paper, draw how the **`cases`** data set would look if it had the same values grouped into three columns: **`country`**, **`year`**, and **`n`**.
]

---
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---
background-image: url(images/tidy/pivot-longer/pl04.png)
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---
background-image: url(images/tidy/pivot-longer/pl05.png)
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---
background-image: url(images/tidy/pivot-longer/pl06.png)
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---
background-image: url(images/tidy/pivot-longer/pl07.png)
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---
background-image: url(images/tidy/pivot-longer/pl08.png)
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---
background-image: url(images/tidy/pivot-longer/pl09.png)
background-position: center middle
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---
background-image: url(images/tidy/pivot-longer/pl10.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-longer/pl11.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-longer/pl12.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-longer/pl13.png)
background-position: center middle
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---
background-image: url(images/tidy/pivot-longer/pl14.png)
background-position: center middle
background-size: 85%

???

The `names_to` argument specifies the new variable name for what was formerly the column headings.

---
background-image: url(images/tidy/pivot-longer/pl15.png)
background-position: center middle
background-size: 85%

???

The `values_to` argument specific the new variable name for what were formerly the spread out values.

---
# `pivot_longer()`

<code class ='r hljs remark-code'>cases %>% &nbsp;&nbsp;pivot_longer(cols = -country, &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;names_to = "year", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_to = "n")</code>

---
# `pivot_longer()`

<code class ='r hljs remark-code'>cases %>% &nbsp;&nbsp;pivot_longer(cols = -country, &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;names_to = "year", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_to = "n")</code>

???

The data to reshape

---
# `pivot_longer()`

<code class ='r hljs remark-code'>cases %>% &nbsp;&nbsp;pivot_longer(cols = -country, &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;names_to = "year", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_to = "n")</code>

???

`cols` specifies which columns need to be pivoted

---
# `pivot_longer()`

<code class ='r hljs remark-code'>cases %>% &nbsp;&nbsp;pivot_longer(cols = -country, &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;names_to = "year", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_to = "n")</code>

???

Name of the column the column names will go to.

---
# `pivot_longer()`

???

Name of the column the values will go to.

---
class: your-turn

# Your turn 4

.big[
Use **`pivot_longer()`** to reorganize **`table4a`** into three columns: `country`, `year`, and `cases`.
]

```r
table4a
#> # A tibble: 3 x 3
#> country `1999` `2000`
#> * <chr> <int> <int>
#> 1 Afghanistan 745 2666
#> 2 Brazil 37737 80488
#> 3 China 212258 213766
```

---
class: your-turn

.panelset[
.panel[.panel-name[Solution]

```r
table4a %>%
 pivot_longer(cols = -country, names_to = "year", values_to = "n")
#> # A tibble: 6 x 3
#> country year n
#> <chr> <chr> <int>
#> 1 Afghanistan 1999 745
#> 2 Afghanistan 2000 2666
#> 3 Brazil 1999 37737
#> 4 Brazil 2000 80488
#> 5 China 1999 212258
#> 6 China 2000 213766
```
]

.panel[.panel-name[Better]

```r
table4a %>%
 pivot_longer(cols = -country, names_to = "year", values_to = "n",
 names_transform = list(year = as.integer))
#> # A tibble: 6 x 3
#> country year n
#> <chr> <int> <int>
#> 1 Afghanistan 1999 745
#> 2 Afghanistan 2000 2666
#> 3 Brazil 1999 37737
#> 4 Brazil 2000 80488
#> 5 China 1999 212258
#> 6 China 2000 213766
```
]
]

---
name: pivot-wider
class: center middle

# `pivot_wider()`

---
# Toy data for practice

```r
pollution
#> # A tibble: 6 x 3
#> city size amount
#> <chr> <chr> <dbl>
#> 1 New York large 23
#> 2 New York small 14
#> 3 London large 22
#> 4 London small 16
#> 5 Beijing large 121
#> 6 Beijing small 56
```

---
class: pop-quiz

# Consider

.big[
Discuss in the chat: What are the variables in the **`pollution`** data set?
]

---
class: pop-quiz

# Consider

.big[
What are the variables in the **`pollution`** data set?
]

???

Variable 1: City

---
class: pop-quiz

# Consider

.big[
What are the variables in the **`pollution`** data set?
]

???

Variable 2: amount of large particulate

---
class: pop-quiz

# Consider

.big[
What are the variables in the **`pollution`** data set?
]

???

Variable 3: amount of small particulate

---
class: your-turn

# Your turn 5

.big[
On a sheet of paper, draw how the **`pollution`** data set would look if it had the same values grouped into three columns: **`city`**, **`large`**, and **`small`**.
]

---
background-image: url(images/tidy/pivot-wider/pw00.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw01.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw02.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw03.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw04.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw05.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw06.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw07.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw08.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw09.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw10.png)
background-position: center middle
background-size: 85%

---
background-image: url(images/tidy/pivot-wider/pw11.png)
background-position: center middle
background-size: 85%

???

The `names_from` argument specifies the variable the new column names will come from.

---
background-image: url(images/tidy/pivot-wider/pw12.png)
background-position: center middle
background-size: 85%

???

The `values_from` argument specific the variable the new values will come from.

---
# `pivot_wider()`

<code class ='r hljs remark-code'>pollution %>% &nbsp;&nbsp;pivot_wider(names_from = "size", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_from = "amount")</code>

---
# `pivot_wider()`

<code class ='r hljs remark-code'>pollution %>% &nbsp;&nbsp;pivot_wider(names_from = "size", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_from = "amount")</code>

???

The data to reshape

---
# `pivot_wider()`

<code class ='r hljs remark-code'>pollution %>% &nbsp;&nbsp;pivot_wider(names_from = "size", &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;values_from = "amount")</code>

???

Name of the column that will become column names.

---
# `pivot_wider()`

???

Name of the column that will make up the values of the new columns.

---
class: your-turn

# Your turn 6

.big[
Use **`pivot_wider()`** to reorganize **`table2`** into four columns: `country`, `year`, `cases`, and `population`.
]

.smallish[

```r
table2
#> # A tibble: 12 x 4
#> country year type count
#> <chr> <int> <chr> <int>
#> 1 Afghanistan 1999 cases 745
#> 2 Afghanistan 1999 population 19987071
#> 3 Afghanistan 2000 cases 2666
#> 4 Afghanistan 2000 population 20595360
#> 5 Brazil 1999 cases 37737
#> 6 Brazil 1999 population 172006362
#> 7 Brazil 2000 cases 80488
#> 8 Brazil 2000 population 174504898
#> 9 China 1999 cases 212258
#> 10 China 1999 population 1272915272
#> 11 China 2000 cases 213766
#> 12 China 2000 population 1280428583
```
]

---
class: your-turn

```r
table2 %>%
 pivot_wider(names_from = "type", values_from = "count")
#> # A tibble: 6 x 4
#> country year cases population
#> <chr> <int> <int> <int>
#> 1 Afghanistan 1999 745 19987071
#> 2 Afghanistan 2000 2666 20595360
#> 3 Brazil 1999 37737 172006362
#> 4 Brazil 2000 80488 174504898
#> 5 China 1999 212258 1272915272
#> 6 China 2000 213766 1280428583
```

---
name: sep-unite
class: center middle

# `separate()` and `unite()`

---
# Toy data for practice

```r
scores
#> # A tibble: 12 x 3
#> name house score
#> <chr> <chr> <dbl>
#> 1 Ronald Weasley Gryffindor 78
#> 2 Harry Potter Gryffindor 85
#> 3 Hermione Granger Gryffindor 100
#> 4 Justin Finch-Fletchley Hufflepuff 87
#> 5 Hannah Abbot Hufflepuff 92
#> 6 Susan Bones Hufflepuff 93
#> 7 Anthony Goldstein Ravenclaw 84
#> 8 Michael Corner Ravenclaw 93
#> 9 Padma Patil Ravenclaw 97
#> 10 Vincent Crabbe Slytherin 61
#> 11 Gregory Goyle Slytherin 61
#> 12 Draco Malfoy Slytherin 92
```

---
class: pop-quiz

# Consider

.big[
Discuss in the chat: What the variables in the `scores` data set?
]

---
class: pop-quiz

# Consider

.big[
One variable or two? What is "tidy" will depend on your purpose.
]

---
# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ...)</code>

---
# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ...)</code>

???

Data frame to tidy

---
# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ...)</code>

???

Column to separate

---
# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ...)</code>

???

New columns to be created

---
# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ...)</code>

???

What divides the pieces of information

---

```r
scores %>%
 separate(col = name, into = c("first", "last"))
#> Warning: Expected 2 pieces. Additional pieces discarded in 1 rows [4].
#> # A tibble: 12 x 4
#> first last house score
#> <chr> <chr> <chr> <dbl>
#> 1 Ronald Weasley Gryffindor 78
#> 2 Harry Potter Gryffindor 85
#> 3 Hermione Granger Gryffindor 100
#> 4 Justin Finch Hufflepuff 87
#> 5 Hannah Abbot Hufflepuff 92
#> 6 Susan Bones Hufflepuff 93
#> 7 Anthony Goldstein Ravenclaw 84
#> 8 Michael Corner Ravenclaw 93
#> 9 Padma Patil Ravenclaw 97
#> 10 Vincent Crabbe Slytherin 61
#> 11 Gregory Goyle Slytherin 61
#> 12 Draco Malfoy Slytherin 92
```

---

<code class ='r hljs remark-code'>scores %>% &nbsp;&nbsp;separate(col = name, into = c("first", "last")) #> Warning: Expected 2 pieces. Additional pieces discarded in 1 rows [4]. #> # A tibble: 12 x 4 #> &nbsp;&nbsp;&nbsp;first &nbsp;&nbsp;&nbsp;last &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;house &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;score #> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<dbl> #> &nbsp;1 Ronald &nbsp;&nbsp;Weasley &nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;78 #> &nbsp;2 Harry &nbsp;&nbsp;&nbsp;Potter &nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;85 #> &nbsp;3 Hermione Granger &nbsp;&nbsp;Gryffindor &nbsp;&nbsp;100 #> &nbsp;4 Justin &nbsp;&nbsp;Finch &nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;87 #> &nbsp;5 Hannah &nbsp;&nbsp;Abbot &nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;92 #> &nbsp;6 Susan &nbsp;&nbsp;&nbsp;Bones &nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;93 #> &nbsp;7 Anthony &nbsp;Goldstein Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;84 #> &nbsp;8 Michael &nbsp;Corner &nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;93 #> &nbsp;9 Padma &nbsp;&nbsp;&nbsp;Patil &nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;97 #> 10 Vincent &nbsp;Crabbe &nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 11 Gregory &nbsp;Goyle &nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 12 Draco &nbsp;&nbsp;&nbsp;Malfoy &nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;92</code>

---

<code class ='r hljs remark-code'>scores %>% &nbsp;&nbsp;separate(col = name, into = c("first", "last")) #> Warning: Expected 2 pieces. Additional pieces discarded in 1 rows [4]. #> # A tibble: 12 x 4 #> &nbsp;&nbsp;&nbsp;first &nbsp;&nbsp;&nbsp;last &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;house &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;score #> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<dbl> #> &nbsp;1 Ronald &nbsp;&nbsp;Weasley &nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;78 #> &nbsp;2 Harry &nbsp;&nbsp;&nbsp;Potter &nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;85 #> &nbsp;3 Hermione Granger &nbsp;&nbsp;Gryffindor &nbsp;&nbsp;100 #> &nbsp;4 Justin &nbsp;&nbsp;Finch &nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;87 #> &nbsp;5 Hannah &nbsp;&nbsp;Abbot &nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;92 #> &nbsp;6 Susan &nbsp;&nbsp;&nbsp;Bones &nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;93 #> &nbsp;7 Anthony &nbsp;Goldstein Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;84 #> &nbsp;8 Michael &nbsp;Corner &nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;93 #> &nbsp;9 Padma &nbsp;&nbsp;&nbsp;Patil &nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;97 #> 10 Vincent &nbsp;Crabbe &nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 11 Gregory &nbsp;Goyle &nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 12 Draco &nbsp;&nbsp;&nbsp;Malfoy &nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;92</code>

---

<code class ='r hljs remark-code'>scores %>% &nbsp;&nbsp;separate(col = name, into = c("first", "last"), sep = " ") #> # A tibble: 12 x 4 #> &nbsp;&nbsp;&nbsp;first &nbsp;&nbsp;&nbsp;last &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;house &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;score #> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<dbl> #> &nbsp;1 Ronald &nbsp;&nbsp;Weasley &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;78 #> &nbsp;2 Harry &nbsp;&nbsp;&nbsp;Potter &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;85 #> &nbsp;3 Hermione Granger &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;100 #> &nbsp;4 Justin &nbsp;&nbsp;Finch-Fletchley Hufflepuff &nbsp;&nbsp;&nbsp;87 #> &nbsp;5 Hannah &nbsp;&nbsp;Abbot &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;92 #> &nbsp;6 Susan &nbsp;&nbsp;&nbsp;Bones &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;93 #> &nbsp;7 Anthony &nbsp;Goldstein &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;84 #> &nbsp;8 Michael &nbsp;Corner &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;93 #> &nbsp;9 Padma &nbsp;&nbsp;&nbsp;Patil &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;97 #> 10 Vincent &nbsp;Crabbe &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 11 Gregory &nbsp;Goyle &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 12 Draco &nbsp;&nbsp;&nbsp;Malfoy &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;92</code>

---

<code class ='r hljs remark-code'>scores %>% &nbsp;&nbsp;separate(col = name, into = c("first", "last"), sep = " ") #> # A tibble: 12 x 4 #> &nbsp;&nbsp;&nbsp;first &nbsp;&nbsp;&nbsp;last &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;house &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;score #> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<chr> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<dbl> #> &nbsp;1 Ronald &nbsp;&nbsp;Weasley &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;78 #> &nbsp;2 Harry &nbsp;&nbsp;&nbsp;Potter &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;&nbsp;85 #> &nbsp;3 Hermione Granger &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Gryffindor &nbsp;&nbsp;100 #> &nbsp;4 Justin &nbsp;&nbsp;Finch-Fletchley Hufflepuff &nbsp;&nbsp;&nbsp;87 #> &nbsp;5 Hannah &nbsp;&nbsp;Abbot &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;92 #> &nbsp;6 Susan &nbsp;&nbsp;&nbsp;Bones &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Hufflepuff &nbsp;&nbsp;&nbsp;93 #> &nbsp;7 Anthony &nbsp;Goldstein &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;84 #> &nbsp;8 Michael &nbsp;Corner &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;93 #> &nbsp;9 Padma &nbsp;&nbsp;&nbsp;Patil &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Ravenclaw &nbsp;&nbsp;&nbsp;&nbsp;97 #> 10 Vincent &nbsp;Crabbe &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 11 Gregory &nbsp;Goyle &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;61 #> 12 Draco &nbsp;&nbsp;&nbsp;Malfoy &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Slytherin &nbsp;&nbsp;&nbsp;&nbsp;92</code>

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# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ..., &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;extra = "warn", fill = "warn")</code>

- **`warn`**: emit warning, drop extra values

- **`drop`**: drop extra values without warning

- **`merge`**: merge extra values into final column of `into`

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# `separate()`

<code class ='r hljs remark-code'>separate(data, col, into, sep = "[^[:alnum:]]+", ..., &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;extra = "warn", fill = "warn")</code>

- **`warn`**: emit warning, fill with `NA` from right

- **`right`**: fill with `NA` from right without warning

- **`left`**: fill with `NA` from left without warning

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# `unite()`