Tidy data

class: center, middle, inverse, title-slide

# Tidy data
## <br><br> College of the Atlantic
###

---

## Tidy data

>Happy families are all alike; every unhappy family is unhappy in its own way. 
>
>Leo Tolstoy

.pull-left[
**Characteristics of tidy data:**

- Each variable forms a column.
- Each observation forms a row.
- Each type of observational unit forms a table.
]
--
.pull-right[
**Characteristics of untidy data:**

!@#$%^&*()
]

---

.question[
What makes this data not tidy?
]

.footnote[
Source: [Army Air Forces Statistical Digest, WW II](https://www.ibiblio.org/hyperwar/AAF/StatDigest/aafsd-3.html)
]

---

.question[
What makes this data not tidy?
]

<br>

.footnote[
Source: [Gapminder, Estimated HIV prevalence among 15-49 year olds](https://www.gapminder.org/data)
]

---

.question[
What makes this data not tidy?
]

<br>

.footnote[
Source: [US Census Fact Finder, General Economic Characteristics, ACS 2017](https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_17_5YR_DP03&src=pt)
]

---

## Displaying vs. summarising data

.panelset[

.panel[.panel-name[Output]

.pull-left[

```
##                     name height   mass
## 1         Luke Skywalker    172   77.0
## 2                  C-3PO    167   75.0
## 3                  R2-D2     96   32.0
## 4            Darth Vader    202  136.0
## 5            Leia Organa    150   49.0
## 6              Owen Lars    178  120.0
## 7     Beru Whitesun lars    165   75.0
## 8                  R5-D4     97   32.0
## 9      Biggs Darklighter    183   84.0
## 10        Obi-Wan Kenobi    182   77.0
## 11      Anakin Skywalker    188   84.0
## 12        Wilhuff Tarkin    180     NA
## 13             Chewbacca    228  112.0
## 14              Han Solo    180   80.0
## 15                Greedo    173   74.0
## 16 Jabba Desilijic Tiure    175 1358.0
## 17        Wedge Antilles    170   77.0
## 18      Jek Tono Porkins    180  110.0
## 19                  Yoda     66   17.0
## 20             Palpatine    170   75.0
## 21             Boba Fett    183   78.2
## 22                 IG-88    200  140.0
## 23                 Bossk    190  113.0
## 24      Lando Calrissian    177   79.0
## 25                 Lobot    175   79.0
## 26                Ackbar    180   83.0
## 27            Mon Mothma    150     NA
## 28          Arvel Crynyd     NA     NA
## 29 Wicket Systri Warrick     88   20.0
## 30             Nien Nunb    160   68.0
## 31          Qui-Gon Jinn    193   89.0
## 32           Nute Gunray    191   90.0
## 33         Finis Valorum    170     NA
## 34         Jar Jar Binks    196   66.0
## 35          Roos Tarpals    224   82.0
## 36            Rugor Nass    206     NA
## 37              Ric Olié    183     NA
## 38                 Watto    137     NA
## 39               Sebulba    112   40.0
## 40         Quarsh Panaka    183     NA
## 41        Shmi Skywalker    163     NA
## 42            Darth Maul    175   80.0
## 43           Bib Fortuna    180     NA
## 44           Ayla Secura    178   55.0
## 45              Dud Bolt     94   45.0
## 46               Gasgano    122     NA
## 47        Ben Quadinaros    163   65.0
## 48            Mace Windu    188   84.0
## 49          Ki-Adi-Mundi    198   82.0
## 50             Kit Fisto    196   87.0
## 51             Eeth Koth    171     NA
## 52            Adi Gallia    184   50.0
## 53           Saesee Tiin    188     NA
## 54           Yarael Poof    264     NA
## 55              Plo Koon    188   80.0
## 56            Mas Amedda    196     NA
## 57          Gregar Typho    185   85.0
## 58                 Cordé    157     NA
## 59           Cliegg Lars    183     NA
## 60     Poggle the Lesser    183   80.0
## 61       Luminara Unduli    170   56.2
## 62         Barriss Offee    166   50.0
## 63                 Dormé    165     NA
## 64                 Dooku    193   80.0
## 65   Bail Prestor Organa    191     NA
## 66            Jango Fett    183   79.0
## 67            Zam Wesell    168   55.0
## 68       Dexter Jettster    198  102.0
## 69               Lama Su    229   88.0
## 70               Taun We    213     NA
## 71            Jocasta Nu    167     NA
## 72         Ratts Tyerell     79   15.0
## 73                R4-P17     96     NA
## 74            Wat Tambor    193   48.0
## 75              San Hill    191     NA
## 76              Shaak Ti    178   57.0
## 77              Grievous    216  159.0
## 78               Tarfful    234  136.0
## 79       Raymus Antilles    188   79.0
## 80             Sly Moore    178   48.0
## 81            Tion Medon    206   80.0
## 82                  Finn     NA     NA
## 83                   Rey     NA     NA
## 84           Poe Dameron     NA     NA
## 85                   BB8     NA     NA
## 86        Captain Phasma     NA     NA
## 87         Padmé Amidala    165   45.0
```
]
.pull-right[

```
## # A tibble: 3 x 2
##   gender    avg_ht
##   <chr>      <dbl>
## 1 feminine    165.
## 2 masculine   177.
## 3 <NA>        181.
```
]

]

.panel[.panel-name[Code]

.pull-left[

```r
starwars %>%
  select(name, height, mass)
```
]
.pull-right[

```r
starwars %>%
  group_by(gender) %>%
  summarize(
    avg_ht = mean(height, na.rm = TRUE)
    )
```
]

]

---
## Acknowledgements

* This course builds on the materials from [Data Science in a Box](https://datasciencebox.org/) developed by Mine Çetinkaya-Rundel and are adapted under the [Creative Commons Attribution Share Alike 4.0 International](https://github.com/rstudio-education/datascience-box/blob/master/LICENSE.md)