Introduction to the Tidyverse

# <br>Introduction to the Tidyverse
## How to take care of your data
### Antoine Bichat <br><br><br><br> State of the R - AgroParisTech <br> May 2, 2018

---

<br>
# {magrittr}

---
# Make Tom eat an apple

* Everyday language

> Tom eats an apple

<br>

Subject - Verb - Complement

<br>

***

<br>

* Programming language

> `eat(Tom, apple)`

<br>

Verb - Subject - Complement

]

---
# Pipe  `%>%`

```r
library(magrittr)
```

* `x %>% f()` is equivalent to `f(x)`

* `x %>% f(y)` is equivalent to `f(x, y)`

```r
2^mean(log(seq_len(10), base = 2), na.rm = TRUE)
```

```
## [1] 4.528729
```

```r
10 %>% 
  seq_len() %>% 
  log(base = 2) %>% 
  mean(na.rm = TRUE) %>% 
  {2^.}
```

```
## [1] 4.528729
```

When you read code, `%>%` is pronounced "then"

The keybord shortcut for `%>%` is Ctrl/⌘ + ⇧ + M

---
# Reassignment pipe  `%<>%`

* `x %<>% f()` is equivalent to `x <- f(x)`

```r
library(ape)

Tree <- 
  "((A,B),(C,D));" %>% 
  read.tree(text = .)

is.rooted(Tree)
```

```
## [1] TRUE
```

```r
Tree %<>% unroot()

is.rooted(Tree)
```

```
## [1] FALSE
```

---
# T-Pipe  `%T>%`

* `x %T>% f() %>% g()` is equivalent to `f(x); g(x)` when f is a side-effect function

```r
iris %>% 
  lm(data = ., Sepal.Length ~ Petal.Length) %T>% 
  plot(1) %>% 
  coefficients()
```

```
##  (Intercept) Petal.Length 
##    4.3066034    0.4089223
```

---

<br>
# {dplyr}

---
# {dplyr}

```r
library(dplyr)
```

{dplyr} is a package which allows you to solve the vast majority of your data-manipulation challenge:

* create variables

* pick variables

* reorder observations

* pick observations

* create summaries

* ...

Functions in this package are verbs and work similarly.

---
# mtcars dataset

```r
DT::datatable(mtcars, class = "compact cell-border", 
              options = list(pageLength = 8))
```

<div id="htmlwidget-fc8d413bcd8eca4d65ce" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-fc8d413bcd8eca4d65ce">{"x":{"filter":"none","data":[["Mazda RX4","Mazda RX4 Wag","Datsun 710","Hornet 4 Drive","Hornet Sportabout","Valiant","Duster 360","Merc 240D","Merc 230","Merc 280","Merc 280C","Merc 450SE","Merc 450SL","Merc 450SLC","Cadillac Fleetwood","Lincoln Continental","Chrysler Imperial","Fiat 128","Honda Civic","Toyota Corolla","Toyota Corona","Dodge Challenger","AMC Javelin","Camaro Z28","Pontiac Firebird","Fiat X1-9","Porsche 914-2","Lotus Europa","Ford Pantera L","Ferrari Dino","Maserati Bora","Volvo 142E"],[21,21,22.8,21.4,18.7,18.1,14.3,24.4,22.8,19.2,17.8,16.4,17.3,15.2,10.4,10.4,14.7,32.4,30.4,33.9,21.5,15.5,15.2,13.3,19.2,27.3,26,30.4,15.8,19.7,15,21.4],[6,6,4,6,8,6,8,4,4,6,6,8,8,8,8,8,8,4,4,4,4,8,8,8,8,4,4,4,8,6,8,4],[160,160,108,258,360,225,360,146.7,140.8,167.6,167.6,275.8,275.8,275.8,472,460,440,78.7,75.7,71.1,120.1,318,304,350,400,79,120.3,95.1,351,145,301,121],[110,110,93,110,175,105,245,62,95,123,123,180,180,180,205,215,230,66,52,65,97,150,150,245,175,66,91,113,264,175,335,109],[3.9,3.9,3.85,3.08,3.15,2.76,3.21,3.69,3.92,3.92,3.92,3.07,3.07,3.07,2.93,3,3.23,4.08,4.93,4.22,3.7,2.76,3.15,3.73,3.08,4.08,4.43,3.77,4.22,3.62,3.54,4.11],[2.62,2.875,2.32,3.215,3.44,3.46,3.57,3.19,3.15,3.44,3.44,4.07,3.73,3.78,5.25,5.424,5.345,2.2,1.615,1.835,2.465,3.52,3.435,3.84,3.845,1.935,2.14,1.513,3.17,2.77,3.57,2.78],[16.46,17.02,18.61,19.44,17.02,20.22,15.84,20,22.9,18.3,18.9,17.4,17.6,18,17.98,17.82,17.42,19.47,18.52,19.9,20.01,16.87,17.3,15.41,17.05,18.9,16.7,16.9,14.5,15.5,14.6,18.6],[0,0,1,1,0,1,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,0,1,0,0,0,1],[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1],[4,4,4,3,3,3,3,4,4,4,4,3,3,3,3,3,3,4,4,4,3,3,3,3,3,4,5,5,5,5,5,4],[4,4,1,1,2,1,4,2,2,4,4,3,3,3,4,4,4,1,2,1,1,2,2,4,2,1,2,2,4,6,8,2]],"container":"<table class=\"compact cell-border\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>mpg<\/th>\n      <th>cyl<\/th>\n      <th>disp<\/th>\n      <th>hp<\/th>\n      <th>drat<\/th>\n      <th>wt<\/th>\n      <th>qsec<\/th>\n      <th>vs<\/th>\n      <th>am<\/th>\n      <th>gear<\/th>\n      <th>carb<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"pageLength":8,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[8,10,25,50,100]}},"evals":[],"jsHooks":[]}</script>

---
# `filter()`

```r
mtcars %>% 
  filter(cyl == 4) 
```
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> mpg </th>
   <th style="text-align:right;"> cyl </th>
   <th style="text-align:right;"> disp </th>
   <th style="text-align:right;"> hp </th>
   <th style="text-align:right;"> drat </th>
   <th style="text-align:right;"> wt </th>
   <th style="text-align:right;"> qsec </th>
   <th style="text-align:right;"> vs </th>
   <th style="text-align:right;"> am </th>
   <th style="text-align:right;"> gear </th>
   <th style="text-align:right;"> carb </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 22.8 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 108.0 </td>
   <td style="text-align:right;"> 93 </td>
   <td style="text-align:right;"> 3.85 </td>
   <td style="text-align:right;"> 2.320 </td>
   <td style="text-align:right;"> 18.61 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 24.4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 146.7 </td>
   <td style="text-align:right;"> 62 </td>
   <td style="text-align:right;"> 3.69 </td>
   <td style="text-align:right;"> 3.190 </td>
   <td style="text-align:right;"> 20.00 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 22.8 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 140.8 </td>
   <td style="text-align:right;"> 95 </td>
   <td style="text-align:right;"> 3.92 </td>
   <td style="text-align:right;"> 3.150 </td>
   <td style="text-align:right;"> 22.90 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 32.4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 78.7 </td>
   <td style="text-align:right;"> 66 </td>
   <td style="text-align:right;"> 4.08 </td>
   <td style="text-align:right;"> 2.200 </td>
   <td style="text-align:right;"> 19.47 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 30.4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 75.7 </td>
   <td style="text-align:right;"> 52 </td>
   <td style="text-align:right;"> 4.93 </td>
   <td style="text-align:right;"> 1.615 </td>
   <td style="text-align:right;"> 18.52 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 33.9 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 71.1 </td>
   <td style="text-align:right;"> 65 </td>
   <td style="text-align:right;"> 4.22 </td>
   <td style="text-align:right;"> 1.835 </td>
   <td style="text-align:right;"> 19.90 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 21.5 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 120.1 </td>
   <td style="text-align:right;"> 97 </td>
   <td style="text-align:right;"> 3.70 </td>
   <td style="text-align:right;"> 2.465 </td>
   <td style="text-align:right;"> 20.01 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 27.3 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 79.0 </td>
   <td style="text-align:right;"> 66 </td>
   <td style="text-align:right;"> 4.08 </td>
   <td style="text-align:right;"> 1.935 </td>
   <td style="text-align:right;"> 18.90 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 26.0 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 120.3 </td>
   <td style="text-align:right;"> 91 </td>
   <td style="text-align:right;"> 4.43 </td>
   <td style="text-align:right;"> 2.140 </td>
   <td style="text-align:right;"> 16.70 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 30.4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 95.1 </td>
   <td style="text-align:right;"> 113 </td>
   <td style="text-align:right;"> 3.77 </td>
   <td style="text-align:right;"> 1.513 </td>
   <td style="text-align:right;"> 16.90 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 21.4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 121.0 </td>
   <td style="text-align:right;"> 109 </td>
   <td style="text-align:right;"> 4.11 </td>
   <td style="text-align:right;"> 2.780 </td>
   <td style="text-align:right;"> 18.60 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
</tbody>
</table>

---
# `select()`

```r
mtcars %>% 
  select(mpg, wt, cyl)
```
<table>
 <thead>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:right;"> mpg </th>
   <th style="text-align:right;"> wt </th>
   <th style="text-align:right;"> cyl </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Mazda RX4 </td>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:right;"> 2.620 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mazda RX4 Wag </td>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:right;"> 2.875 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Datsun 710 </td>
   <td style="text-align:right;"> 22.8 </td>
   <td style="text-align:right;"> 2.320 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hornet 4 Drive </td>
   <td style="text-align:right;"> 21.4 </td>
   <td style="text-align:right;"> 3.215 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hornet Sportabout </td>
   <td style="text-align:right;"> 18.7 </td>
   <td style="text-align:right;"> 3.440 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Valiant </td>
   <td style="text-align:right;"> 18.1 </td>
   <td style="text-align:right;"> 3.460 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Duster 360 </td>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;"> 3.570 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Merc 240D </td>
   <td style="text-align:right;"> 24.4 </td>
   <td style="text-align:right;"> 3.190 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Merc 230 </td>
   <td style="text-align:right;"> 22.8 </td>
   <td style="text-align:right;"> 3.150 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
</tbody>
</table>

See also `mutate_if()`

---
# `arrange()`

```r
mtcars %>% 
  arrange(desc(carb), mpg)
```
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> mpg </th>
   <th style="text-align:right;"> cyl </th>
   <th style="text-align:right;"> disp </th>
   <th style="text-align:right;"> hp </th>
   <th style="text-align:right;"> drat </th>
   <th style="text-align:right;"> wt </th>
   <th style="text-align:right;"> qsec </th>
   <th style="text-align:right;"> vs </th>
   <th style="text-align:right;"> am </th>
   <th style="text-align:right;"> gear </th>
   <th style="text-align:right;"> carb </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 15.0 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 301.0 </td>
   <td style="text-align:right;"> 335 </td>
   <td style="text-align:right;"> 3.54 </td>
   <td style="text-align:right;"> 3.570 </td>
   <td style="text-align:right;"> 14.60 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 19.7 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 145.0 </td>
   <td style="text-align:right;"> 175 </td>
   <td style="text-align:right;"> 3.62 </td>
   <td style="text-align:right;"> 2.770 </td>
   <td style="text-align:right;"> 15.50 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 10.4 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 472.0 </td>
   <td style="text-align:right;"> 205 </td>
   <td style="text-align:right;"> 2.93 </td>
   <td style="text-align:right;"> 5.250 </td>
   <td style="text-align:right;"> 17.98 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 10.4 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 460.0 </td>
   <td style="text-align:right;"> 215 </td>
   <td style="text-align:right;"> 3.00 </td>
   <td style="text-align:right;"> 5.424 </td>
   <td style="text-align:right;"> 17.82 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 13.3 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 350.0 </td>
   <td style="text-align:right;"> 245 </td>
   <td style="text-align:right;"> 3.73 </td>
   <td style="text-align:right;"> 3.840 </td>
   <td style="text-align:right;"> 15.41 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 360.0 </td>
   <td style="text-align:right;"> 245 </td>
   <td style="text-align:right;"> 3.21 </td>
   <td style="text-align:right;"> 3.570 </td>
   <td style="text-align:right;"> 15.84 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 14.7 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 440.0 </td>
   <td style="text-align:right;"> 230 </td>
   <td style="text-align:right;"> 3.23 </td>
   <td style="text-align:right;"> 5.345 </td>
   <td style="text-align:right;"> 17.42 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 15.8 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 351.0 </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> 4.22 </td>
   <td style="text-align:right;"> 3.170 </td>
   <td style="text-align:right;"> 14.50 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 17.8 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 167.6 </td>
   <td style="text-align:right;"> 123 </td>
   <td style="text-align:right;"> 3.92 </td>
   <td style="text-align:right;"> 3.440 </td>
   <td style="text-align:right;"> 18.90 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 19.2 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 167.6 </td>
   <td style="text-align:right;"> 123 </td>
   <td style="text-align:right;"> 3.92 </td>
   <td style="text-align:right;"> 3.440 </td>
   <td style="text-align:right;"> 18.30 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 160.0 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.90 </td>
   <td style="text-align:right;"> 2.620 </td>
   <td style="text-align:right;"> 16.46 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
</tbody>
</table>

---
# `pull()`

```r
mtcars %>% 
  pull(qsec)
```

```
##  [1] 16.46 17.02 18.61 19.44 17.02 20.22 15.84 20.00 22.90 18.30 18.90
## [12] 17.40 17.60 18.00 17.98 17.82 17.42 19.47 18.52 19.90 20.01 16.87
## [23] 17.30 15.41 17.05 18.90 16.70 16.90 14.50 15.50 14.60 18.60
```

---
# `summarise()`

```r
mtcars %>% 
  summarise(Mean_mpg = mean(mpg), 
            Var_disp = var(disp))
```
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> Mean_mpg </th>
   <th style="text-align:right;"> Var_disp </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 20.09062 </td>
   <td style="text-align:right;"> 15360.8 </td>
  </tr>
</tbody>
</table>

---
# `group_by()`

```r
mtcars %>% 
  group_by(cyl, carb) %>% 
  summarise(Count = n(), 
            Mean_mpg = mean(mpg), 
            Var_disp = var(disp))
```
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> cyl </th>
   <th style="text-align:right;"> carb </th>
   <th style="text-align:right;"> Count </th>
   <th style="text-align:right;"> Mean_mpg </th>
   <th style="text-align:right;"> Var_disp </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 27.58 </td>
   <td style="text-align:right;"> 456.59700 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 2 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 25.90 </td>
   <td style="text-align:right;"> 731.95200 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 2 </td>
   <td style="text-align:right;"> 19.75 </td>
   <td style="text-align:right;"> 544.50000 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 19.75 </td>
   <td style="text-align:right;"> 19.25333 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 19.70 </td>
   <td style="text-align:right;"> NA </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 2 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 17.15 </td>
   <td style="text-align:right;"> 1886.33333 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 16.30 </td>
   <td style="text-align:right;"> 0.00000 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 13.15 </td>
   <td style="text-align:right;"> 3340.70000 </td>
  </tr>
  <tr>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 15.00 </td>
   <td style="text-align:right;"> NA </td>
  </tr>
</tbody>
</table>

---
# Programming with dplyr?

```r
iris %>% 
  group_by(Species) %>% 
  summarise(m = median(Sepal.Length))
```

```
## # A tibble: 3 x 2
##   Species        m
##   <fct>      <dbl>
## 1 setosa      5.00
## 2 versicolor  5.90
## 3 virginica   6.50
```

```r
median_by_group <- function(group, var){
  iris %>%
    group_by(group) %>%
    summarise(m = median(var))
}

median_by_group(Species, Sepal.Length)
```

```
## Error in grouped_df_impl(data, unname(vars), drop): Column `group` is unknown
```

---
# `enquo()` and `!!`

Keywords: Tidyeval & Non Standard Evaluation

```r
median_by_group <- function(group, var){
  
  group <- enquo(group)
  var <- enquo(var)
  
  iris %>%
    group_by(!!group) %>%
    summarise(m = median(!!var))
}

median_by_group(Species, Sepal.Length)
```

```
## # A tibble: 3 x 2
##   Species        m
##   <fct>      <dbl>
## 1 setosa      5.00
## 2 versicolor  5.90
## 3 virginica   6.50
```

---
# And with strings?

```r
median_by_group <- function(group, var){
  
  group <- as.name(group)
  var <- as.name(var)
  
  iris %>%
    group_by(!!group) %>%
    summarise(m = median(!!var))
}

median_by_group("Species", "Sepal.Length")
```

```
## # A tibble: 3 x 2
##   Species        m
##   <fct>      <dbl>
## 1 setosa      5.00
## 2 versicolor  5.90
## 3 virginica   6.50
```

---
class: center, middle, inverse

<br>
#{tidyr}
<img src="http://hexb.in/vector/tidyr.svg", width=270>

---
# {tidyr}

```r
library(tidyr)
```

{tidyr} is a package which helps you to transform messy datasets into tidy datasets.

There are three interrelated rules which make your dataset tidy:

1. Each variable must have its own column
    
2. Each observation must have its own row
    
3. Each value must have its own cell

]
]

---
# grades dataset

```r
grades <- tibble(
  Name = c("Tommy", "Mary", "Gary", "Cathy"),
  Sexage = c("m.15", "f.15", "m.16", "f.14"),
  Test1 = c(10, 15, 16, 14),
  Test2 = c(11, 13, 10, 12),
  Test3 = c(12, 13, 17, 10)
  )
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> Name </th>
   <th style="text-align:left;"> Sexage </th>
   <th style="text-align:right;"> Test1 </th>
   <th style="text-align:right;"> Test2 </th>
   <th style="text-align:right;"> Test3 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Tommy </td>
   <td style="text-align:left;"> m.15 </td>
   <td style="text-align:right;"> 10 </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mary </td>
   <td style="text-align:left;"> f.15 </td>
   <td style="text-align:right;"> 15 </td>
   <td style="text-align:right;"> 13 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gary </td>
   <td style="text-align:left;"> m.16 </td>
   <td style="text-align:right;"> 16 </td>
   <td style="text-align:right;"> 10 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cathy </td>
   <td style="text-align:left;"> f.14 </td>
   <td style="text-align:right;"> 14 </td>
   <td style="text-align:right;"> 12 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
</tbody>
</table>

---
# `separate()`

```r
grades <- 
  grades %>%
  separate(Sexage, into = c("Sex", "Age"))
```
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> Name </th>
   <th style="text-align:left;"> Sex </th>
   <th style="text-align:left;"> Age </th>
   <th style="text-align:right;"> Test1 </th>
   <th style="text-align:right;"> Test2 </th>
   <th style="text-align:right;"> Test3 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Tommy </td>
   <td style="text-align:left;"> m </td>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:right;"> 10 </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mary </td>
   <td style="text-align:left;"> f </td>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:right;"> 15 </td>
   <td style="text-align:right;"> 13 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gary </td>
   <td style="text-align:left;"> m </td>
   <td style="text-align:left;"> 16 </td>
   <td style="text-align:right;"> 16 </td>
   <td style="text-align:right;"> 10 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cathy </td>
   <td style="text-align:left;"> f </td>
   <td style="text-align:left;"> 14 </td>
   <td style="text-align:right;"> 14 </td>
   <td style="text-align:right;"> 12 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
</tbody>
</table>

The inverse of `separate()` is `unite()`

---
# `gather()`

```r
grades <- 
  grades %>%
  gather(Test1, Test2, Test3, key = Test, value = Grade)
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> Name </th>
   <th style="text-align:left;"> Sex </th>
   <th style="text-align:left;"> Age </th>
   <th style="text-align:left;"> Test </th>
   <th style="text-align:right;"> Grade </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Tommy </td>
   <td style="text-align:left;"> m </td>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:left;"> Test1 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mary </td>
   <td style="text-align:left;"> f </td>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:left;"> Test1 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gary </td>
   <td style="text-align:left;"> m </td>
   <td style="text-align:left;"> 16 </td>
   <td style="text-align:left;"> Test1 </td>
   <td style="text-align:right;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cathy </td>
   <td style="text-align:left;"> f </td>
   <td style="text-align:left;"> 14 </td>
   <td style="text-align:left;"> Test1 </td>
   <td style="text-align:right;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Tommy </td>
   <td style="text-align:left;"> m </td>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:left;"> Test2 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mary </td>
   <td style="text-align:left;"> f </td>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:left;"> Test2 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gary </td>
   <td style="text-align:left;"> m </td>
   <td style="text-align:left;"> 16 </td>
   <td style="text-align:left;"> Test2 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Cathy </td>
   <td style="text-align:left;"> f </td>
   <td style="text-align:left;"> 14 </td>
   <td style="text-align:left;"> Test2 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
</tbody>
</table>

The inverse of `gather()` is `spread()`

---
# More efficient code: summarising

```r
grades %>% group_by(Name) %>% summarise(Mean = mean(Grade))
```

```
## # A tibble: 4 x 2
##   Name   Mean
##   <chr> <dbl>
## 1 Cathy  12.0
## 2 Gary   14.3
## 3 Mary   13.7
## 4 Tommy  11.0
```

```r
grades %>% group_by(Test) %>% summarise(Mean = mean(Grade))
```

```
## # A tibble: 3 x 2
##   Test   Mean
##   <chr> <dbl>
## 1 Test1  13.8
## 2 Test2  11.5
## 3 Test3  13.0
```

---
# More efficient code: plotting

```r
library(ggplot2)
grades %>%
  ggplot(aes(Test, Grade, color = Name)) +
  geom_point() +
  geom_line(aes(group = Name)) +
  theme_bw()
```

---
class: center, middle, inverse

<br>
# {tibble}

---
# Classical data.frame

```r
swiss
```

```
##              Fertility Agriculture Examination Education Catholic
## Courtelary        80.2        17.0          15        12     9.96
## Delemont          83.1        45.1           6         9    84.84
## Franches-Mnt      92.5        39.7           5         5    93.40
## Moutier           85.8        36.5          12         7    33.77
## Neuveville        76.9        43.5          17        15     5.16
## Porrentruy        76.1        35.3           9         7    90.57
## Broye             83.8        70.2          16         7    92.85
## Glane             92.4        67.8          14         8    97.16
## Gruyere           82.4        53.3          12         7    97.67
## Sarine            82.9        45.2          16        13    91.38
## Veveyse           87.1        64.5          14         6    98.61
## Aigle             64.1        62.0          21        12     8.52
## Aubonne           66.9        67.5          14         7     2.27
## Avenches          68.9        60.7          19        12     4.43
## Cossonay          61.7        69.3          22         5     2.82
## Echallens         68.3        72.6          18         2    24.20
## Grandson          71.7        34.0          17         8     3.30
## Lausanne          55.7        19.4          26        28    12.11
## La Vallee         54.3        15.2          31        20     2.15
## Lavaux            65.1        73.0          19         9     2.84
## Morges            65.5        59.8          22        10     5.23
## Moudon            65.0        55.1          14         3     4.52
## Nyone             56.6        50.9          22        12    15.14
## Orbe              57.4        54.1          20         6     4.20
## Oron              72.5        71.2          12         1     2.40
## Payerne           74.2        58.1          14         8     5.23
## Paysd'enhaut      72.0        63.5           6         3     2.56
## Rolle             60.5        60.8          16        10     7.72
## Vevey             58.3        26.8          25        19    18.46
## Yverdon           65.4        49.5          15         8     6.10
## Conthey           75.5        85.9           3         2    99.71
## Entremont         69.3        84.9           7         6    99.68
## Herens            77.3        89.7           5         2   100.00
## Martigwy          70.5        78.2          12         6    98.96
## Monthey           79.4        64.9           7         3    98.22
## St Maurice        65.0        75.9           9         9    99.06
## Sierre            92.2        84.6           3         3    99.46
## Sion              79.3        63.1          13        13    96.83
## Boudry            70.4        38.4          26        12     5.62
## La Chauxdfnd      65.7         7.7          29        11    13.79
## Le Locle          72.7        16.7          22        13    11.22
## Neuchatel         64.4        17.6          35        32    16.92
## Val de Ruz        77.6        37.6          15         7     4.97
## ValdeTravers      67.6        18.7          25         7     8.65
## V. De Geneve      35.0         1.2          37        53    42.34
## Rive Droite       44.7        46.6          16        29    50.43
## Rive Gauche       42.8        27.7          22        29    58.33
##              Infant.Mortality
## Courtelary               22.2
## Delemont                 22.2
## Franches-Mnt             20.2
## Moutier                  20.3
## Neuveville               20.6
## Porrentruy               26.6
## Broye                    23.6
## Glane                    24.9
## Gruyere                  21.0
## Sarine                   24.4
## Veveyse                  24.5
## Aigle                    16.5
## Aubonne                  19.1
## Avenches                 22.7
## Cossonay                 18.7
## Echallens                21.2
## Grandson                 20.0
## Lausanne                 20.2
## La Vallee                10.8
## Lavaux                   20.0
## Morges                   18.0
## Moudon                   22.4
## Nyone                    16.7
## Orbe                     15.3
## Oron                     21.0
## Payerne                  23.8
## Paysd'enhaut             18.0
## Rolle                    16.3
## Vevey                    20.9
## Yverdon                  22.5
## Conthey                  15.1
## Entremont                19.8
## Herens                   18.3
## Martigwy                 19.4
## Monthey                  20.2
## St Maurice               17.8
## Sierre                   16.3
## Sion                     18.1
## Boudry                   20.3
## La Chauxdfnd             20.5
## Le Locle                 18.9
## Neuchatel                23.0
## Val de Ruz               20.0
## ValdeTravers             19.5
## V. De Geneve             18.0
## Rive Droite              18.2
## Rive Gauche              19.3
```

---
# Tibble

```r
library(tibble)
swiss %>% as_tibble(rownames = "Province")
```

```
## # A tibble: 47 x 7
##    Province     Fertility Agriculture Examination Education Catholic
##    <chr>            <dbl>       <dbl>       <int>     <int>    <dbl>
##  1 Courtelary        80.2        17.0          15        12     9.96
##  2 Delemont          83.1        45.1           6         9    84.8 
##  3 Franches-Mnt      92.5        39.7           5         5    93.4 
##  4 Moutier           85.8        36.5          12         7    33.8 
##  5 Neuveville        76.9        43.5          17        15     5.16
##  6 Porrentruy        76.1        35.3           9         7    90.6 
##  7 Broye             83.8        70.2          16         7    92.8 
##  8 Glane             92.4        67.8          14         8    97.2 
##  9 Gruyere           82.4        53.3          12         7    97.7 
## 10 Sarine            82.9        45.2          16        13    91.4 
## # ... with 37 more rows, and 1 more variable: Infant.Mortality <dbl>
```

.full-width[.content-box-sotr[Row names are variables so they must have their own column. `rownames_to_column()` can help you.]]

---
# Column names

```r
tibble(
  x = 1:5, 
  `2x` = 2 * (1:5), 
  `Some letters` = letters[1:5],
  `;-)` = c(TRUE, FALSE, FALSE, TRUE, TRUE)
)
```

```
## # A tibble: 5 x 4
##       x  `2x` `Some letters` `;-)`
##   <int> <dbl> <chr>          <lgl>
## 1     1    2. a              TRUE 
## 2     2    4. b              FALSE
## 3     3    6. c              FALSE
## 4     4    8. d              TRUE 
## 5     5   10. e              TRUE
```

---
# Consistency in subsetting

```r
df <- data.frame(x = 1:9, y = LETTERS[1:9])
tbl <- tibble(x = 1:9, y = LETTERS[1:9])
```

```r
class(df[, 1:2])
```

```
## [1] "data.frame"
```

```r
class(tbl[, 1:2])
```

```
## [1] "tbl_df"     "tbl"        "data.frame"
```

```r
class(df[, 1])
```

```
## [1] "integer"
```

```r
class(tbl[, 1])
```

```
## [1] "tbl_df"     "tbl"        "data.frame"
```

---
# List-column

```r
starwars %>% select(name, height, mass, hair_color, films, vehicles)
```

```
## # A tibble: 87 x 6
##    name               height  mass hair_color    films     vehicles 
##    <chr>               <int> <dbl> <chr>         <list>    <list>   
##  1 Luke Skywalker        172   77. blond         <chr [5]> <chr [2]>
##  2 C-3PO                 167   75. <NA>          <chr [6]> <chr [0]>
##  3 R2-D2                  96   32. <NA>          <chr [7]> <chr [0]>
##  4 Darth Vader           202  136. none          <chr [4]> <chr [0]>
##  5 Leia Organa           150   49. brown         <chr [5]> <chr [1]>
##  6 Owen Lars             178  120. brown, grey   <chr [3]> <chr [0]>
##  7 Beru Whitesun lars    165   75. brown         <chr [3]> <chr [0]>
##  8 R5-D4                  97   32. <NA>          <chr [1]> <chr [0]>
##  9 Biggs Darklighter     183   84. black         <chr [1]> <chr [0]>
## 10 Obi-Wan Kenobi        182   77. auburn, white <chr [6]> <chr [1]>
## # ... with 77 more rows
```

---
# List-column: put a vector in each case

```r
starwars %>% pull(films) %>% head(4)
```

```
## [[1]]
## [1] "Revenge of the Sith"     "Return of the Jedi"     
## [3] "The Empire Strikes Back" "A New Hope"             
## [5] "The Force Awakens"      
## 
## [[2]]
## [1] "Attack of the Clones"    "The Phantom Menace"     
## [3] "Revenge of the Sith"     "Return of the Jedi"     
## [5] "The Empire Strikes Back" "A New Hope"             
## 
## [[3]]
## [1] "Attack of the Clones"    "The Phantom Menace"     
## [3] "Revenge of the Sith"     "Return of the Jedi"     
## [5] "The Empire Strikes Back" "A New Hope"             
## [7] "The Force Awakens"      
## 
## [[4]]
## [1] "Revenge of the Sith"     "Return of the Jedi"     
## [3] "The Empire Strikes Back" "A New Hope"
```

---
# List-column: put what you want in each case

```r
iris %>% 
  group_by(Species) %>% 
  nest(.key = Data) %>% 
  mutate(Model = purrr::map(Data,
                            ~ lm(data = ., 
                                 Sepal.Length ~ Petal.Length))) %>% 
  mutate(Summary = purrr::map(Model, summary)) %>% 
  mutate(`R squared` = purrr::map_dbl(Summary, ~ .$r.squared))
```

```
## # A tibble: 3 x 5
##   Species    Data              Model    Summary          `R squared`
##   <fct>      <list>            <list>   <list>                 <dbl>
## 1 setosa     <tibble [50 × 4]> <S3: lm> <S3: summary.lm>      0.0714
## 2 versicolor <tibble [50 × 4]> <S3: lm> <S3: summary.lm>      0.569 
## 3 virginica  <tibble [50 × 4]> <S3: lm> <S3: summary.lm>      0.747
```

---
class: center, middle, inverse

<br>
# {tidyverse}

---

```r
library(tidyverse)
```

```
## ── Attaching packages ────────────────────────────────────────────────── tidyverse 1.2.1 ──
```

```
## ✔ ggplot2 2.2.1     ✔ purrr   0.2.4
## ✔ tibble  1.4.2     ✔ dplyr   0.7.4
## ✔ tidyr   0.8.0     ✔ stringr 1.3.0
## ✔ readr   1.1.1     ✔ forcats 0.3.0
```

```
## ── Conflicts ───────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ tidyr::extract()   masks magrittr::extract()
## ✖ dplyr::filter()    masks stats::filter()
## ✖ dplyr::lag()       masks stats::lag()
## ✖ purrr::set_names() masks magrittr::set_names()
```

--
* {ggplot2}: build graph

* {readr}: read rectangular data

* {purrr}: functionnal programming

* {stringr}: manipulate strings

* {forcats}: manipulate factors

Imports `%>%` from {magrittr}

---
class: center, middle, inverse
# Syracuse conjecture

## Application example

---

# Definition

`\begin{equation}
\left\{
  \begin{aligned}
    u_0 & = N \in \mathbb{N}, \\
    u_{n+1} & = \left\{
                  \begin{aligned}
                    \frac{u_n}{2} & \quad \text{ if } u_n\in 2\mathbb{N}, \\
                    3u_n+1 & \quad \text{ else.}
                  \end{aligned}
                \right. 
  \end{aligned}
\right.
\end{equation}`

```r
syracuse <- function(x) {
 c(x, if(x > 1) Recall(if (x %% 2) x * 3 + 1 else x / 2))
}
```

```r
syracuse(6)
```

```
## [1]  6  3 10  5 16  8  4  2  1
```

```r
map(7:8, syracuse)
```

```
## [[1]]
##  [1]  7 22 11 34 17 52 26 13 40 20 10  5 16  8  4  2  1
## 
## [[2]]
## [1] 8 4 2 1
```

---
# Creation of data

```r
data_syracuse <- 
  100 %>% 
  seq_len() %>% 
  tibble(N = .) %>% 
  mutate(Sequence = map(N, syracuse))
```

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class=\"compact cell-border\">\n  <thead>\n    <tr>\n      <th>N<\/th>\n      <th>Sequence<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"pageLength":7,"columnDefs":[{"className":"dt-right","targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[7,10,25,50,100]}},"evals":[],"jsHooks":[]}</script>

---

```r
data_syracuse <-
  data_syracuse %>% 
  mutate(Length = map_int(Sequence, length),
         Max = map_dbl(Sequence, max))
```
--
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class=\"compact cell-border\">\n  <thead>\n    <tr>\n      <th>N<\/th>\n      <th>Sequence<\/th>\n      <th>Length<\/th>\n      <th>Max<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"pageLength":10,"columnDefs":[{"className":"dt-right","targets":[0,2,3]}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>

---
# Shortest length?

```r
data_syracuse %>% 
  select(-Max) %>% 
  filter(Length != log2(N) + 1) %>%
  arrange(Length, desc(N))
```

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---
# Plots

```r
theme_set(theme_bw())

plot_syrac <- function(data, var){
  
  var <- enquo(var)
  
  ggplot(data) +
    aes(x = N, y = !!var) +
    geom_line()
}
```

Unfortunately, this syntax is not supported by {ggplot2} yet. It is still in developpement.

But one can use the old syntax, which will be depreciated:

```r
plot_syrac <- function(data, var){
    ggplot(data) +
    aes_(x = ~N, y = substitute(var)) +
    geom_line()
}
```

---

```r
p1 <- plot_syrac(data_syracuse, Length)
p2 <- plot_syrac(data_syracuse, log10(Max)) + ylab("log(Max)")

cowplot::plot_grid(p1, p2)
```

---
class: middle, center, inverse

<br>
# References

---

### General

* <a href="http://r4ds.had.co.nz" target="_blank"><i>R for Data Science</i></a>, Garrett Grolemund & Hadley Wickham

* <a href="https://www.tidyverse.org" target="_blank"><i>www.tidyverse.org</i></a>

### Non-standard evaluation

* <a href="https://thinkr.fr/tidyeval/" target="_blank"><i>Tidyeval</i></a>, ThinkR (in French)

### For all your questions

* <a href="https://stackoverflow.com/" target="_blank"><i>Stack Overflow</i></a>

---
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# Thanks for your attention!

#### <i class="fa  fa-github "></i> <a href="https://github.com/abichat" target="_blank">@abichat</a>
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#### <i class="fa  fa-twitter "></i> <a href="https://twitter.com/_abichat" target="_blank">@_abichat</a>
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#### <i class="fa  fa-linkedin-square "></i> <a href="https://www.linkedin.com/in/antoinebichat" target="_blank">antoinebichat</a>
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#### <i class="fa  fa-link "></i> <a href="https://abichat.github.io" target="_blank">abichat.github.io</a>
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####<i class="fa  fa-envelope "></i> <a href="mailto:antoine.bichat@mines-nancy.org?subject=Science%20Communication%20with%20R">antoine.bichat@mines-nancy.org</a>

.footnote[Slides created via the R package <b><a href="https://github.com/yihui/xaringan" target="_blank">xaringan</a></b>.]