R & Tidyverse ggplot2

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# R & Tidyverse<br> <code>ggplot2</code>
## Una introduccion a la visualizacion de datos
### Paul Efren Santos Andrade<br><span class="citation">@PaulEfrenSantos</span>
### 19 August, 2019

---

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---
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![](https://user-images.githubusercontent.com/6571451/51793018-06c26380-216f-11e9-997a-7a08066ae4e2.gif)

---
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![](images/hex-ggplot2.png)

---
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# Los paquetes

---

**Simple**: instalar [tidyverse](http://tidyverse.org)

```r
install.packages('tidyverse')
```

**Medio**: instalar unicamente `ggplot2`

```r
install.pacakages('ggplot2')
```

**Avanzado**: instalar desde GitHub

```r
devtools::install_github('tidyverse/ggplot2')
```

---
layout: false

## Tidyverse

```r
library(tidyverse)
```

```
## -- Attaching packages -------------------------------------------- tidyverse 1.2.1 --
```

```
## v ggplot2 3.2.1     v purrr   0.3.2
## v tibble  2.1.3     v dplyr   0.8.3
## v tidyr   0.8.3     v stringr 1.4.0
## v readr   1.3.1     v forcats 0.4.0
```

```
## -- Conflicts ----------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
```

---
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class: center
# Grammar of Graphics
![](images/ggraphic.jpg)
---
layout: true
# *ggplot2*
---

.left-column[
![](images/hadley.jpg)
__Hadley Wickham__
]

.right-column[
- Crear representaciones gráficas de  nuestros datos es un paso clave para poder comunicar información y hallazgos a otros.

- ggplot2 es un sistema para crear gráficos, basado en [The Grammar of Graphics](https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448/ref=as_li_ss_tl?ie=UTF8&qid=1477928463&sr=8-1&keywords=the+grammar+of+graphics&linkCode=sl1&tag=ggplot2-20&linkId=f0130e557161b83fbe97ba0e9175c431).

- Usted proporciona los datos, le dice a ggplot2 cómo asignar variables, qué caracteristicas mostrar y esta se ocupa de los detalles.
]

---
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class: center
# ggplot2
![](images/ggplot2_book.jpg)

---

## Algunas razones

- Visualizacion  de forma .hl[esquematica]

1. Datos organizados
    2. Expresar los datos como elementos visuales
    3. scales, guides, axis, labels, theme

- Secuencia .hl[comprensible] de la creacion de graficos

- Sencilla de .hl[replicar]

- Secuencia .hl[concistente]

---
layout: false

# Con que estamos tratando?

<br>
`ggplot2` es un gran paquete: .hl[filosofia] + .hl[funciones]
<br>...muy bien organizadas

<br><br>
Muchos ejemplos de visualizacion impresionantes
<br>...no estan en estas diapositivas

<br><br>
Quiza toquemos muchas ideas muy rapido
<br>...pero conoceras **donde** buscar ayuda

.img-right[![](images/ggplot2_exploratory.png)]
.footnote[<https://github.com/allisonhorst/stats-illustrations>]
]

---
layout: false
class: inverse center middle text-white

.font200[<br>Grammar of Graphics]

---

# Gramatica de visualizacion?

.left-code[
"Una idea clara de lo que deseas mostrar, encamina la construccion de un grafico."

.footnote[<http://vita.had.co.nz/papers/layered-grammar.pdf>]
]

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-0-1.png" width="100%" />
]

---
layout: true
# Que datos estan detras?

.left-code[
### MPG

- Manufacturer
- Car Type (Class)
- City MPG
- Highway MPG
]

---

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-2-1.png" width="100%" />
]

---

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-3-1.png" width="100%" />
]

---

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-1-1.png" width="100%" />
]

---

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-4-1.png" width="100%" />
]

---

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-5-1.png" width="100%" />
]

---

.right-plot[
<img src="index_files/figure-html/guess-data-from-plot-6-1.png" width="100%" />
]

---

.right-plot[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> manufacturer </th>
   <th style="text-align:left;"> class </th>
   <th style="text-align:right;"> cty </th>
   <th style="text-align:right;"> hwy </th>
   <th style="text-align:left;"> model </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> audi </td>
   <td style="text-align:left;"> compact </td>
   <td style="text-align:right;"> 18 </td>
   <td style="text-align:right;"> 27 </td>
   <td style="text-align:left;"> a4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> audi </td>
   <td style="text-align:left;"> compact </td>
   <td style="text-align:right;"> 15 </td>
   <td style="text-align:right;"> 25 </td>
   <td style="text-align:left;"> a4 quattro </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ford </td>
   <td style="text-align:left;"> suv </td>
   <td style="text-align:right;"> 12 </td>
   <td style="text-align:right;"> 18 </td>
   <td style="text-align:left;"> expedition 2wd </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ford </td>
   <td style="text-align:left;"> suv </td>
   <td style="text-align:right;"> 13 </td>
   <td style="text-align:right;"> 19 </td>
   <td style="text-align:left;"> explorer 4wd </td>
  </tr>
  <tr>
   <td style="text-align:left;"> toyota </td>
   <td style="text-align:left;"> suv </td>
   <td style="text-align:right;"> 16 </td>
   <td style="text-align:right;"> 20 </td>
   <td style="text-align:left;"> 4runner 4wd </td>
  </tr>
  <tr>
   <td style="text-align:left;"> toyota </td>
   <td style="text-align:left;"> compact </td>
   <td style="text-align:right;"> 21 </td>
   <td style="text-align:right;"> 31 </td>
   <td style="text-align:left;"> camry solara </td>
  </tr>
  <tr>
   <td style="text-align:left;"> toyota </td>
   <td style="text-align:left;"> compact </td>
   <td style="text-align:right;"> 28 </td>
   <td style="text-align:right;"> 37 </td>
   <td style="text-align:left;"> corolla </td>
  </tr>
  <tr>
   <td style="text-align:left;"> toyota </td>
   <td style="text-align:left;"> suv </td>
   <td style="text-align:right;"> 13 </td>
   <td style="text-align:right;"> 18 </td>
   <td style="text-align:left;"> land cruiser wagon 4wd </td>
  </tr>
</tbody>
</table>
]

---
layout: false
# Argumentos

.font120[
- **Data** datos a ser graficados
]

--
.font120[
- **.hlb[Geom]etric ** las formas que se mostraran
]

--
.font120[
- **.hlb[Aes]thetic mappings** los datos a ser representados
]

--
.font120[
- **.hlb[Stat]istics**  datos procesados para ser visualizados
]

--
.font120[
- **.hlb[Coord]inates**  dispocision de los elementos
]

--
.font120[
- **.hlb[Scale]s** limites en los cuales varia  los **aes()**
]

--
.font120[
- **.hlb[Facet]s** Produce multiples paneles
]

---
layout: true
# Gramatica de visualizacion

.left-column[
### Data - Los datos

```r
ggplot(data)
```
]

---

.right-column[
#### **Tidy** Data

1. Cada variable una a .hl[columna]

2. Cada observaCion es una .hl[fila]

3. Cada mediocion es una unidad de la observacion
]

---

.right-column[
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:right;"> 1997 </th>
   <th style="text-align:right;"> 2002 </th>
   <th style="text-align:right;"> 2007 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Canada </td>
   <td style="text-align:right;"> 30.30584 </td>
   <td style="text-align:right;"> 31.90227 </td>
   <td style="text-align:right;"> 33.39014 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> China </td>
   <td style="text-align:right;"> 1230.07500 </td>
   <td style="text-align:right;"> 1280.40000 </td>
   <td style="text-align:right;"> 1318.68310 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> United States </td>
   <td style="text-align:right;"> 272.91176 </td>
   <td style="text-align:right;"> 287.67553 </td>
   <td style="text-align:right;"> 301.13995 </td>
  </tr>
</tbody>
</table>
]

.right-column[

```r
tidy_pop <- gather(messy_pop, 'year', 'pop', -country)
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> country </th>
   <th style="text-align:left;"> year </th>
   <th style="text-align:right;"> pop </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Canada </td>
   <td style="text-align:left;"> 1997 </td>
   <td style="text-align:right;"> 30.306 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> China </td>
   <td style="text-align:left;"> 1997 </td>
   <td style="text-align:right;"> 1230.075 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> United States </td>
   <td style="text-align:left;"> 1997 </td>
   <td style="text-align:right;"> 272.912 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Canada </td>
   <td style="text-align:left;"> 2002 </td>
   <td style="text-align:right;"> 31.902 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> China </td>
   <td style="text-align:left;"> 2002 </td>
   <td style="text-align:right;"> 1280.400 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> United States </td>
   <td style="text-align:left;"> 2002 </td>
   <td style="text-align:right;"> 287.676 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Canada </td>
   <td style="text-align:left;"> 2007 </td>
   <td style="text-align:right;"> 33.390 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> China </td>
   <td style="text-align:left;"> 2007 </td>
   <td style="text-align:right;"> 1318.683 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> United States </td>
   <td style="text-align:left;"> 2007 </td>
   <td style="text-align:right;"> 301.140 </td>
  </tr>
</tbody>
</table>
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data
### Estetica - **Aesthetics**

```r
+ aes()
```

]
---

.right-column[
Informacion a ser visualizada

- year

- pop

- country
]

---

.right-column[
Informacion a ser visualizada

- year → **x**

- pop → **y**

- country → *shape*, *color*, etc.
]

---

.right-column[
Informacion a ser visualizada

```r
aes(
  x = year,
  y = pop,
  color = country
)
```
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data - Datos
### Aesthetics - Estetica
### Geoms - Formas

```r
+ geom_*()
```
]

---

.right-column[
Formas geometricas que se mostraran en el grafico

<img src="index_files/figure-html/geom_demo-1.png" width="650px" />
]

---

.right-column[
[**geom_** mas usuales](https://eric.netlify.com/2017/08/10/most-popular-ggplot2-geoms/)

<https://eric.netlify.com/2017/08/10/most-popular-ggplot2-geoms/>
]
]

---

.right-column[

Visisten <http://ggplot2.tidyverse.org/reference/> para mas opciones

.font70[

```
##  [1] "geom_abline"     "geom_area"       "geom_bar"        "geom_bin2d"     
##  [5] "geom_blank"      "geom_boxplot"    "geom_col"        "geom_contour"   
##  [9] "geom_count"      "geom_crossbar"   "geom_curve"      "geom_density"   
## [13] "geom_density_2d" "geom_density2d"  "geom_dotplot"    "geom_errorbar"  
## [17] "geom_errorbarh"  "geom_freqpoly"   "geom_hex"        "geom_histogram" 
## [21] "geom_hline"      "geom_jitter"     "geom_label"      "geom_line"      
## [25] "geom_linerange"  "geom_map"        "geom_path"       "geom_point"     
## [29] "geom_pointrange" "geom_polygon"    "geom_qq"         "geom_qq_line"   
## [33] "geom_quantile"   "geom_raster"     "geom_rect"       "geom_ribbon"    
## [37] "geom_rug"        "geom_segment"    "geom_sf"         "geom_sf_label"  
## [41] "geom_sf_text"    "geom_smooth"     "geom_spoke"      "geom_step"      
## [45] "geom_text"       "geom_tile"       "geom_violin"     "geom_vline"
```
]
]
--

.right-column[
<img src="images/geom.gif" width="200px" style="float: right; margin-right: 100px; margin-top: -25px;">
O solo escriban `geom_` en la consola de RStudio
]

---
layout: true
# Nuestro primer grafico!
---

.left-code[

```r
ggplot(tidy_pop)
```
]

.right-plot[
<img src="index_files/figure-html/first-plot1a-out-1.png" width="100%" />
]

---

.left-code[

```r
ggplot(tidy_pop) +
* aes(x = year,
*     y = pop)
```
]

.right-plot[
<img src="index_files/figure-html/first-plot1b-out-1.png" width="100%" />
]

---

.left-code[

```r
ggplot(tidy_pop) +
  aes(x = year,
      y = pop) +
* geom_point()
```
]

.right-plot[
<img src="index_files/figure-html/first-plot1c-out-1.png" width="100%" />
]

---

.left-code[

```r
ggplot(tidy_pop) +
  aes(x = year,
      y = pop,
*     color = country) +
  geom_point()
```
]

.right-plot[
<img src="index_files/figure-html/first-plot1-out-1.png" width="100%" />
]

---

.left-code[

```r
ggplot(tidy_pop) +
  aes(x = year,
      y = pop,
      color = country) +
  geom_point() +
* geom_line()
```

.font80[
```r
geom_path: Cada grupo esta formado solo
por una observacion. 
Es necesario especificar el argumento group
en aes()
```
]
]

.right-plot[
<img src="index_files/figure-html/first-plot2-fake-out-1.png" width="100%" />
]
---

.left-code[

```r
ggplot(tidy_pop) +
  aes(x = year,
      y = pop,
      color = country) +
  geom_point() +
  geom_line(
*   aes(group = country))
```
]

.right-plot[
<img src="index_files/figure-html/first-plot2-out-1.png" width="100%" />
]

---

.left-code[

```r
g <- ggplot(tidy_pop) +
  aes(x = year,
      y = pop,
      color = country) +
  geom_point() +
  geom_line(
    aes(group = country))

g
```
]

.right-plot[
<img src="index_files/figure-html/first-plot3-out-1.png" width="100%" />
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### data
### aes()
### geom_*()

```r
+ geom_*()
```
]
---

.right-column[
```r
geom_*(mapping, data, stat, position)
```

- `data` cada geom puede tener su propia data
    - Mostrada en un sistema unico de coordenadas

- `map` geom_*, argumentos en aes()
    - geom_ puede usar aes globales
    - Algunos geom_ tienen argumentos especificos
        - `geom_point` requiere `x` - `y`, opcional `shape`, `color`, `size`, etc.
        - `geom_ribbon` requiere `x`, `ymin` - `ymax`, opcional `fill`
    - `?geom_ribbon`
]

---

.right-column[
```r
geom_*(mapping, data, position)
```
    
- `position` Ajusta lapocision de los objetos
    - `'dodge'`, `'stack'`, `'jitter'`
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data
### Aesthetics
### Geoms
### Facet

```r
+facet_wrap()

+facet_grid()
```
]
---

.right-column[

```r
g + facet_wrap(~ country)
```

<img src="index_files/figure-html/geom_facet-1.png" width="90%" />
]

---

.right-column[

```r
g + facet_grid(continent ~ country)
```

<img src="index_files/figure-html/geom_grid-1.png" width="90%" />
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data
### Aesthetics
### Geoms
### Facet
### Labels

```r
+ labs()
```
]
---

.right-column[

```r
g + labs(x = "Year", y = "Population")
```

<img src="index_files/figure-html/labs-ex-1.png" width="90%" />
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data
### Aesthetics
### Geoms
### Facet
### Labels
### Coords

```r
+ coord_*()
```
]
---

.right-column[

```r
g + coord_flip()
```

<img src="index_files/figure-html/coord-ex-1.png" width="90%" />
]

---

.right-column[

```r
g + coord_polar()
```

<img src="index_files/figure-html/coord-ex2-1.png" width="90%" />
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data
### Aesthetics
### Geoms
### Facet
### Labels
### Coords
### Scales

```r
+ scale_*_*()
```
]
---

.right-column[ 
`scale` + `_` + `<aes>` + `_` + `<type>` + `()`

Que parametr deseas modificar? → `<aes>` <br>
De que tipo es el parametro? → `<type>`

- Eje x discreto<br>`scale_x_discrete()`
- Ajustar los ejes a escala logaritmica<br>`scale_y_log10()`
- Para especificar los colores de forma manual<br>`scale_fill_discrete()`<br>`scale_color_manual()`
]

---

.right-column[

```r
g + scale_color_manual(values = c("peru", "pink", "plum"))
```

<img src="index_files/figure-html/scale_ex1-1.png" width="90%" />
]

---

.right-column[

```r
g + scale_y_log10()
```

<img src="index_files/figure-html/scale_ex2-1.png" width="90%" />
]

---

.right-column[

```r
g + scale_x_discrete(labels = c("MCMXCVII", "MMII", "MMVII"))
```

<img src="index_files/figure-html/scale_ex4-1.png" width="90%" />
]

---
layout: true
# Gramatica de Visualizacion

.left-column[
### Data
### Aesthetics
### Geoms
### Facet
### Labels
### Coords
### Scales
### Theme

```r
+ theme()
```
]

---

.right-column[
Se puede manipular la apariencia del grafico

Algunas opciones dentro de `ggplot2`

- `g + theme_bw()`
- `g + theme_dark()`
- `g + theme_gray()`
- `g + theme_light()`
- `g + theme_minimal()`

]

---

.right-column[
Se tiene un gran numero de parametros,<br>agrupadas por el area de trabajo:

- Opciones globales: `line`, `rect`, `text`, `title`
- `axis`: x-, y-, title, ticks, lines
- `legend`: leyenda
- `panel`: area actual de trabajo
- `plot`: todo el panel
- `strip`: etiquetas de los sub paneles
]
---

.right-column[
Para modificar los elementos se cuenta con:

- `element_blank()` elimina los elementos
- `element_line()`
- `element_rect()`
- `element_text()`
]

---

.right-column[

```r
g + theme_bw()
```

<img src="index_files/figure-html/unnamed-chunk-1-1.png" width="90%" />
]

---

.right-column[
.font80[

```r
g + theme_minimal() + theme(text = element_text(family = "Palatino"))
```

<img src="index_files/figure-html/unnamed-chunk-2-1.png" width="90%" />
]
]

---

.right-column[
Pueden cargar un tema como opcion por defecto con: `theme_set()`

```r
my_theme <- theme_bw() +
  theme(
    text = element_text(family = "Palatino", size = 12),
    panel.border = element_rect(colour = 'grey80'), 
    panel.grid.minor = element_blank()
  )

theme_set(my_theme)
```

Todos los graficos pueden usar ahora este tema!
]

---

.right-column[

```r
g
```

<img src="index_files/figure-html/unnamed-chunk-3-1.png" width="90%" />
]

---

.right-column[

```r
g + theme(legend.position = 'bottom')
```

<img src="index_files/figure-html/unnamed-chunk-4-1.png" width="90%" />
]

---
layout: false
# Como guardar las imagenes

Se tiene la funcion, **ggsave( )**

```r
ggsave(
  filename = "my_plot.png",
  plot = my_plot,
  width = 10,
  height = 8,
  dpi = 100,
  device = "png"
)
```

---
layout: false

# install.packages("ggalt")

.left-code[

```r
library(ggalt)
df <- tibble(trt = LETTERS[1 : 10],
             value = seq(100, 10, by = -10))

ggplot(df, aes(trt, value)) + 
  geom_lollipop()
```
]

.right-plot[
<img src="index_files/figure-html/unnamed-chunk-6-1.png" width="100%" />
]
---
layout: false

# install.packages("gqqplotr")

.left-code[

```r
library(qqplotr)
set.seed(0)
smp <- data.frame(norm = rnorm(100))

# Normal Q-Q plot of Normal data
gg <- ggplot(data = smp, mapping = aes(sample = norm)) +
 stat_qq_band() +
 stat_qq_line() +
 stat_qq_point()
gg + labs(x = "Theoretical Quantiles", y = "Sample Quantiles")
```
]

.right-plot[
<img src="index_files/figure-html/unnamed-chunk-8-1.png" width="100%" />
]

---

### Donde buscar ayuda

- **ggplot2 docs:** <http://ggplot2.tidyverse.org/>

- **R4DS - Data visualization:** <http://r4ds.had.co.nz/data-visualisation.html>

- **Hadley Wickham's ggplot2 book:** <https://www.amazon.com/dp/0387981403/>

---
class: inverse, center, middle

# Gracias!