Manipuler des bases de données avec dplyr

# Manipuler des<br>bases de données<br>avec `dplyr`

.class-info[
<figure>
  <img src="img/04/dplyr.png" alt="dplyr" title="dplyr" width="15%">
</figure>
]

---

``` r
gapminder
```

```
## # A tibble: 1,704 × 6
##    country     continent  year lifeExp      pop gdpPercap
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
##  1 Afghanistan Asia       1952    28.8  8425333      779.
##  2 Afghanistan Asia       1957    30.3  9240934      821.
##  3 Afghanistan Asia       1962    32.0 10267083      853.
##  4 Afghanistan Asia       1967    34.0 11537966      836.
##  5 Afghanistan Asia       1972    36.1 13079460      740.
##  6 Afghanistan Asia       1977    38.4 14880372      786.
##  7 Afghanistan Asia       1982    39.9 12881816      978.
##  8 Afghanistan Asia       1987    40.8 13867957      852.
##  9 Afghanistan Asia       1992    41.7 16317921      649.
## 10 Afghanistan Asia       1997    41.8 22227415      635.
## # ℹ 1,694 more rows
```
]

---

# tidyverse

???

From "Master the Tidyverse" by RStudio

---

# tidyverse

.center[
<figure>
  <img src="img/02/tidyverse.png" alt="The tidyverse" title="The tidyverse" width="50%">
</figure>
]

---

# `dplyr`: verbes pour manipuler des données

<table>
  <tr>
    <td>Extraire des lignes avec <code>filter()</code></td>
    <td><img src="img/04/filter.png" alt="filter" title="filter" height="80px"></td>
  </tr>
  <tr>
    <td>Extraire des colonnes avec <code>select()</code></td>
    <td><img src="img/04/select.png" alt="select" title="select" height="80px"></td>
  </tr>
  <tr>
    <td>Arranger/trier les lignes avec <code>arrange()</code></td>
    <td><img src="img/04/arrange.png" alt="arrange" title="arrange" height="80px"></td>
  </tr>
  <tr>
    <td>Créer/modifier des colonnes avec <code>mutate()</code></td>
    <td><img src="img/04/mutate.png" alt="mutate" title="mutate" height="80px"></td>
  </tr>
  <tr>
    <td>Résumer des sous-ensembles avec<br><code>group_by() |> summarize()</code></td>
    <td><img src="img/04/summarize.png" alt="summarize" title="summarize" height="80px"></td>
  </tr>
</table>

---

# `filter()`

---

# `filter()`

]

.pull-right[
- <b><span style="background: #FFDFD1">`DATA`</span></b> = tableau de données à transformer
- <b><span style="background: #FFD0CF">`...`</span></b> = Un ou plusieurs tests<br>.small[`filter()` retourne chaque ligne pour lequel le test retourne `TRUE`]
]

---

.pull-left[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:left;"> year </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1952 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1957 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1962 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1967 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1972 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>
]

.pull-right[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:right;"> year </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1952 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1957 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1962 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1967 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1972 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Denmark </td>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 1977 </td>
  </tr>
</tbody>
</table>
]

---

# `filter()`

]

---

# Tests logiques

<table>
  <tr>
    <th class="cell-center">Test</th>
    <th class="cell-left">Signification</th>
    <th class="cell-center">Test</th>
    <th class="cell-left">Signification</th>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x < y</code></td>
    <td class="cell-left">plus petit que</td>
    <td class="cell-center"><code class="remark-inline-code">x %in% y</code></td>
    <td class="cell-left">dans (élément d'un vecteur)</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x > y</code></td>
    <td class="cell-left">plus grand que</td>
    <td class="cell-center"><code class="remark-inline-code">is.na(x)</code></td>
    <td class="cell-left">valeur manquante?</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">==</code></td>
    <td class="cell-left">égale</td>
    <td class="cell-center"><code class="remark-inline-code">!is.na(x)</code></td>
    <td class="cell-left">valeurs non manquantes</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x <= y</code></td>
    <td class="cell-left">plus petit ou égal à</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x >= y</code></td>
    <td class="cell-left">plus grand ou égal à</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">x != y</code></td>
    <td class="cell-left">différent de</td>
  </tr>
</table>

---

# À votre tour #1: filtrer

1. Les données du Canada
2. Toutes les données de pays situés en Océanie (Oceania)
3. Lignes où l'espérance de vie est supérieure à 82 ans

<countdown-timer class="countdown" id="timer_13625c40" minutes="3" seconds="0" update-every="1" tabindex="0" style="right:0;bottom:0;"></countdown-timer>

---

``` r
filter(gapminder, country == "Canada")
```
]

``` r
filter(gapminder, continent == "Oceania")
```
]

``` r
filter(gapminder, lifeExp > 82)
```
]

---

# Erreur fréquente

]

]

---

# `filter()` avec des conditions multiples

---

# Opérateurs logiques

<table>
  <tr>
    <th class="cell-center">Opérateur</th>
    <th class="cell-center">Signification</th>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">a & b</code></td>
    <td class="cell-center">et</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">a | b</code></td>
    <td class="cell-center">ou</td>
  </tr>
  <tr>
    <td class="cell-center"><code class="remark-inline-code">!a</code></td>
    <td class="cell-center">pas</td>
  </tr>
</table>

---

# Par défaut, union ("et")

---

# À votre tour #2: filtrer

1. Les données du Canada avant 1970
2. Les pays où l'espérance de vie en 2007 est inférieure à 50
3. Les pays hors d'Afrique où l'espérance de vie en 2007 est inférieur à 50

<countdown-timer class="countdown" id="timer_6650ddfb" minutes="4" seconds="0" update-every="1" tabindex="0" style="right:0;bottom:0;"></countdown-timer>

---

``` r
filter(gapminder, country == "Canada", year < 1970)
```

``` r
filter(gapminder, year == 2007, lifeExp < 50)
```

``` r
filter(gapminder, year == 2007, lifeExp < 50, 
       continent != "Africa")
```

---

# Erreurs fréquentes

]

]
]

]

]
]

---

# Syntaxe commune

]

.pull-right[
- <b><span style="background: #EFB3FF">`VERB`</span></b> = fonction `dplyr`/verbe
- <b><span style="background: #FFDFD1">`DATA`</span></b> = base de données à transformer
- <b><span style="background: #FFD0CF">`...`</span></b> = commandes pour le verbe
]

---

# `mutate()`

]

.pull-right[
- <b><span style="background: #FFDFD1">`DATA`</span></b> = base de données à transformer
- <b><span style="background: #FFD0CF">`...`</span></b> = colonnes à modifier/créer
]

---

.pull-left.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> year </th>
   <th style="text-align:left;"> gdpPercap </th>
   <th style="text-align:left;"> pop </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1952 </td>
   <td style="text-align:left;"> 779.4453145 </td>
   <td style="text-align:left;"> 8425333 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1957 </td>
   <td style="text-align:left;"> 820.8530296 </td>
   <td style="text-align:left;"> 9240934 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1962 </td>
   <td style="text-align:left;"> 853.10071 </td>
   <td style="text-align:left;"> 10267083 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1967 </td>
   <td style="text-align:left;"> 836.1971382 </td>
   <td style="text-align:left;"> 11537966 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> 1972 </td>
   <td style="text-align:left;"> 739.9811058 </td>
   <td style="text-align:left;"> 13079460 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>
]

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:right;"> year </th>
   <th style="text-align:left;"> … </th>
   <th style="text-align:right;"> gdp </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1952 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 6567086330 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1957 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 7585448670 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1962 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 8758855797 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1967 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9648014150 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1972 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9678553274 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1977 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 11697659231 </td>
  </tr>
</tbody>
</table>
]

---

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:right;"> year </th>
   <th style="text-align:left;"> … </th>
   <th style="text-align:right;"> gdp </th>
   <th style="text-align:right;"> pop_mil </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1952 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 6567086330 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1957 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 7585448670 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1962 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 8758855797 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1967 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9648014150 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1972 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 9678553274 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:right;"> 1977 </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:right;"> 11697659231 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
</tbody>
</table>
]

---

# `ifelse()`

]

.pull-right[
- <b><span style="background: #FFC0DC">`TEST`</span></b> = un test logique
- <b><span style="background: #FFDFD1">`VALEUR_SI_VRAI`</span></b> = valeur si vrai
- <b><span style="background: #CBB5FF">`VALEUR_SI_FAUX`</span></b> = valeur si faux
]

---

```
## # A tibble: 1,704 × 7
##    country     continent  year lifeExp      pop gdpPercap after_1960
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl> <lgl>     
##  1 Afghanistan Asia       1952    28.8  8425333      779. FALSE     
##  2 Afghanistan Asia       1957    30.3  9240934      821. FALSE     
##  3 Afghanistan Asia       1962    32.0 10267083      853. TRUE      
##  4 Afghanistan Asia       1967    34.0 11537966      836. TRUE      
##  5 Afghanistan Asia       1972    36.1 13079460      740. TRUE      
##  6 Afghanistan Asia       1977    38.4 14880372      786. TRUE      
##  7 Afghanistan Asia       1982    39.9 12881816      978. TRUE      
##  8 Afghanistan Asia       1987    40.8 13867957      852. TRUE      
##  9 Afghanistan Asia       1992    41.7 16317921      649. TRUE      
## 10 Afghanistan Asia       1997    41.8 22227415      635. TRUE      
## # ℹ 1,694 more rows
```

---
class: title title-1

# `case_when()`

``` r
case_when(CAS1_EST_VRAI ~ VALEUR1, 
          CAS2_EST_VRAI ~ VALEUR2,
          TRUE ~ VALEUR_AUTRE)
```

---

``` r
mutate(gapminder, 
       decennie = case_when(
         year < 1960 ~ "années 50",
         # year >= 1960 & year < 1970 ~ "années 60",
         year < 1970 ~ "années 60",
         year < 1980 ~ "années 70",
         year < 1990 ~ "années 80",
         year < 2000 ~ "années 90",
         TRUE ~ "millénaire")
)
```

---

```
## # A tibble: 1,704 × 7
##    country     continent  year lifeExp      pop gdpPercap decennie 
##    <fct>       <fct>     <int>   <dbl>    <int>     <dbl> <chr>    
##  1 Afghanistan Asia       1952    28.8  8425333      779. années 50
##  2 Afghanistan Asia       1957    30.3  9240934      821. années 50
##  3 Afghanistan Asia       1962    32.0 10267083      853. années 60
##  4 Afghanistan Asia       1967    34.0 11537966      836. années 60
##  5 Afghanistan Asia       1972    36.1 13079460      740. années 70
##  6 Afghanistan Asia       1977    38.4 14880372      786. années 70
##  7 Afghanistan Asia       1982    39.9 12881816      978. années 80
##  8 Afghanistan Asia       1987    40.8 13867957      852. années 80
##  9 Afghanistan Asia       1992    41.7 16317921      649. années 90
## 10 Afghanistan Asia       1997    41.8 22227415      635. années 90
## # ℹ 1,694 more rows
```

---

# À votre tour #3: transformer

1. `africa`, qui est vrai (`TRUE`) si le pays est situé sur le continent africain
2. `log_gdpPercap` pour le log PIB par capita (indice: utiliser `log()`)
3. `africa_asia` avec comme valeur `"Afrique ou Asie"` si le pays est dans un des deux continents, sinon `"Autre continent"`

<countdown-timer class="countdown" id="timer_d8fd26d3" minutes="5" seconds="0" update-every="1" tabindex="0" style="right:0;bottom:0;"></countdown-timer>

---

``` r
mutate(gapminder, 
       africa = continent == "Africa")
```

``` r
mutate(gapminder, 
       log_gdpPercap = log(gdpPercap))
```

``` r
mutate(gapminder, 
       africa_asia = ifelse(continent %in% c("Africa", "Asia"),
                            "Afrique ou Asie",
                            "Autre continent"))
```

---

# Comment procéder avec plusieurs verbes?

.box-inv-1.sp-after[Créer un jeu de données pour 2002 *et* calculer le log PIB par capita]

---

# Comment procéder avec plusieurs verbes?

.box-inv-1.sp-after[Créer un jeu de données pour 2002 *et* calculer le log PIB par capita]

---

#  Comment procéder avec plusieurs verbes?

.box-inv-1.sp-after[Créer un jeu de données pour 2002 *et* calculer le log PIB par capita]

.box-inv-1[L'opérateur tuyau, `|>`, prend un objet à gauche<br>et l'assigne au premier argument de la fonction de droite]

---

# Comment procéder avec plusieurs verbes?

---

# Comment procéder avec plusieurs verbes?

.box-inv-1.sp-after[Créer un jeu de données pour 2002 *et* calculer le log PIB par capita]

---

# Améliorer la lisibilité du code avec `|>`

---

# `summarize()`

.pull-left.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:left;"> year </th>
   <th style="text-align:left;"> lifeExp </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1952 </td>
   <td style="text-align:left;"> 28.801 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1957 </td>
   <td style="text-align:left;"> 30.332 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1962 </td>
   <td style="text-align:left;"> 31.997 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1967 </td>
   <td style="text-align:left;"> 34.02 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>
]

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> mean_life </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 59.47444 </td>
  </tr>
</tbody>
</table>
]

---

# `summarize()`

.pull-left.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:left;"> year </th>
   <th style="text-align:left;"> lifeExp </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1952 </td>
   <td style="text-align:left;"> 28.801 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1957 </td>
   <td style="text-align:left;"> 30.332 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1962 </td>
   <td style="text-align:left;"> 31.997 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1967 </td>
   <td style="text-align:left;"> 34.02 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Afghanistan </td>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:left;"> 1972 </td>
   <td style="text-align:left;"> 36.088 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>
]

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> mean_life </th>
   <th style="text-align:right;"> min_life </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 59.47444 </td>
   <td style="text-align:right;"> 23.599 </td>
  </tr>
</tbody>
</table>
]

---

# À votre tour #4: résumer

1. La première année des mesures (minimum)
2. La dernière année des mesures (maximum) 
3. Le nombre de lignes dans la base de données (utilisez l'aide mémoire)
4. Le nombre de pays distincts dans la base de données (utilisez l'aide mémoire)

<countdown-timer class="countdown" id="timer_ef070430" minutes="4" seconds="0" update-every="1" tabindex="0" style="right:0;bottom:0;"></countdown-timer>

---

``` r
gapminder |> 
  summarize(first = min(year),
            last = max(year),
            num_rows = n(),
            num_unique = n_distinct(country))
```

.small[
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> first </th>
   <th style="text-align:right;"> last </th>
   <th style="text-align:right;"> num_rows </th>
   <th style="text-align:right;"> num_unique </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 1952 </td>
   <td style="text-align:right;"> 2007 </td>
   <td style="text-align:right;"> 1704 </td>
   <td style="text-align:right;"> 142 </td>
  </tr>
</tbody>
</table>
]

---

# À votre tour #5: résumer

1. le nombre de pays
2. l'espérance de vie médiane

pour le continent africain en 2007.

<countdown-timer class="countdown" id="timer_ac2b3bfa" minutes="4" seconds="0" update-every="1" tabindex="0" style="right:0;bottom:0;"></countdown-timer>

---

``` r
gapminder |>
  filter(continent == "Africa", year == 2007) |>
  summarise(n_countries = n_distinct(country), 
            med_le = median(lifeExp))
```

.small[
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> n_countries </th>
   <th style="text-align:right;"> med_le </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 52 </td>
   <td style="text-align:right;"> 52.9265 </td>
  </tr>
</tbody>
</table>
]

---

# `group_by()`

&nbsp;

---

``` r
gapminder |> 
  group_by(continent) |> 
  summarize(n_countries = n_distinct(country)) 
```

.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:right;"> n_countries </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Africa </td>
   <td style="text-align:right;"> 52 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Americas </td>
   <td style="text-align:right;"> 25 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Asia </td>
   <td style="text-align:right;"> 33 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Europe </td>
   <td style="text-align:right;"> 30 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Oceania </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
</tbody>
</table>
]

---

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:right;"> mean </th>
   <th style="text-align:right;"> sum </th>
   <th style="text-align:right;"> n </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:right;"> 42 </td>
   <td style="text-align:right;"> 252 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
</tbody>
</table>
]

---

.pull-left.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> city </th>
   <th style="text-align:left;"> particle_size </th>
   <th style="text-align:right;"> amount </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;background-color: rgba(178, 177, 249, 1) !important;"> New York </td>
   <td style="text-align:left;background-color: rgba(178, 177, 249, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(178, 177, 249, 1) !important;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(178, 177, 249, 1) !important;"> New York </td>
   <td style="text-align:left;background-color: rgba(178, 177, 249, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(178, 177, 249, 1) !important;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(239, 179, 255, 1) !important;"> London </td>
   <td style="text-align:left;background-color: rgba(239, 179, 255, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(239, 179, 255, 1) !important;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(239, 179, 255, 1) !important;"> London </td>
   <td style="text-align:left;background-color: rgba(239, 179, 255, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(239, 179, 255, 1) !important;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 208, 207, 1) !important;"> Beijing </td>
   <td style="text-align:left;background-color: rgba(255, 208, 207, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(255, 208, 207, 1) !important;"> 121 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 208, 207, 1) !important;"> Beijing </td>
   <td style="text-align:left;background-color: rgba(255, 208, 207, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(255, 208, 207, 1) !important;"> 56 </td>
  </tr>
</tbody>
</table>
]

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> city </th>
   <th style="text-align:right;"> mean </th>
   <th style="text-align:right;"> sum </th>
   <th style="text-align:right;"> n </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 208, 207, 1) !important;"> Beijing </td>
   <td style="text-align:right;background-color: rgba(255, 208, 207, 1) !important;"> 88.5 </td>
   <td style="text-align:right;background-color: rgba(255, 208, 207, 1) !important;"> 177 </td>
   <td style="text-align:right;background-color: rgba(255, 208, 207, 1) !important;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(239, 179, 255, 1) !important;"> London </td>
   <td style="text-align:right;background-color: rgba(239, 179, 255, 1) !important;"> 19.0 </td>
   <td style="text-align:right;background-color: rgba(239, 179, 255, 1) !important;"> 38 </td>
   <td style="text-align:right;background-color: rgba(239, 179, 255, 1) !important;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(178, 177, 249, 1) !important;"> New York </td>
   <td style="text-align:right;background-color: rgba(178, 177, 249, 1) !important;"> 18.5 </td>
   <td style="text-align:right;background-color: rgba(178, 177, 249, 1) !important;"> 37 </td>
   <td style="text-align:right;background-color: rgba(178, 177, 249, 1) !important;"> 2 </td>
  </tr>
</tbody>
</table>
]

---

.pull-left.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> city </th>
   <th style="text-align:left;"> particle_size </th>
   <th style="text-align:right;"> amount </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> New York </td>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(255, 223, 209, 1) !important;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> New York </td>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(255, 240, 212, 1) !important;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> London </td>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(255, 223, 209, 1) !important;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> London </td>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(255, 240, 212, 1) !important;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> Beijing </td>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(255, 223, 209, 1) !important;"> 121 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> Beijing </td>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(255, 240, 212, 1) !important;"> 56 </td>
  </tr>
</tbody>
</table>
]

.pull-right.small[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> particle_size </th>
   <th style="text-align:right;"> mean </th>
   <th style="text-align:right;"> sum </th>
   <th style="text-align:right;"> n </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 223, 209, 1) !important;"> Large </td>
   <td style="text-align:right;background-color: rgba(255, 223, 209, 1) !important;"> 55.33333 </td>
   <td style="text-align:right;background-color: rgba(255, 223, 209, 1) !important;"> 166 </td>
   <td style="text-align:right;background-color: rgba(255, 223, 209, 1) !important;"> 3 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: rgba(255, 240, 212, 1) !important;"> Small </td>
   <td style="text-align:right;background-color: rgba(255, 240, 212, 1) !important;"> 28.66667 </td>
   <td style="text-align:right;background-color: rgba(255, 240, 212, 1) !important;"> 86 </td>
   <td style="text-align:right;background-color: rgba(255, 240, 212, 1) !important;"> 3 </td>
  </tr>
</tbody>
</table>
]

---

# À votre tour #6: grouper et résumer

.box-1[Trouvez l'espérance de vie <br>minimum, maximum et médiane<br>par continent pour 2007 uniquement]

<countdown-timer class="countdown" id="timer_4b174e77" minutes="5" seconds="0" update-every="1" tabindex="0" style="right:0;bottom:0;"></countdown-timer>

---

``` r
gapminder |> 
  group_by(continent) |> 
  summarize(min_le = min(lifeExp),
            max_le = max(lifeExp),
            med_le = median(lifeExp))
```

``` r
gapminder |> 
  filter(year == 2007) |> 
  group_by(continent) |> 
  summarize(min_le = min(lifeExp),
            max_le = max(lifeExp),
            med_le = median(lifeExp))
```

---

# `dplyr`: verbes pour manipuler des données