Unidad 1.3 Representación gráfica

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# Unidad 1.3 Representación gráfica
## Módulo 1
### 
### Daniel Enrique González Gómez Universidad Javeriana Cali
### 2021-08-06

---

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# AGENDA
 
## 1. Presentación guía de aprendizaje 1.3

## 2.  Varios
---

## Introducción

Una gráfica o una representación gráfica o un gráfico, es un tipo de representación de datos, generalmente cuantitativos, mediante recursos visuales (líneas, vectores, superficies o símbolos), para que se manifieste visualmente la relación matemática o correlación estadística que guardan entre sí.

Wikipedia

## Paquetes de R para realizar graficos

---
### Gráficos variables cualitativas con R base

[//]: <> (---------------------------------------------------------------------)
.panelset[
 .panel[.panel-name[Grafico de tortas]

```r
cc=c(20, 10, 20, 20, 20, 20, 20, 20, 20, 30, 20, 20, 20, 10, 30, 20, 20, 30, 20, 
     30, 30, 20, 10, 30, 20, 20, 30, 30, 10, 20, 10, 20, 20, 20, 10, 20, 10, 20, 
     20, 30, 30, 30, 10, 30, 20, 20, 20, 20, 20, 20, 10, 20, 30, 30, 10, 10, 10, 
     20, 10, 20, 10, 30, 20, 10, 20, 30, 10, 30, 30, 30, 20, 30, 30, 30, 30, 30, 
     30, 20, 10, 30, 10, 20, 20, 10, 20, 20, 20, 20, 10, 20)

labs=c("Ing. Mecánica","Ing. Civil ","Ing.Sistemas") 
pct=round(table(cc)/sum(table(cc))*100) 
labs=paste(labs, pct);labs=paste(labs, "%", sep = " ") 
t1=table(cc)
pie(t1, 
    labels=labs, 
    main=" Distribución por carrera")
```

![](punidad107_files/figure-html/unnamed-chunk-2-1.png)
]
[//]: <> (---------------------------------------------------------------------)
 .panel[.panel-name[Diagrama de barras]

```r
ev=table(rbinom(90,5,0.80)); 
barplot(ev, col=c("red","yellow","orange","green","blue"), main = "Evaluación proceso de inducción")
```

![](punidad107_files/figure-html/unnamed-chunk-3-1.png)
 ]
 
.panel[.panel-name[Diag. de barras dos variables]

```r
counts <- table(mtcars$vs, mtcars$gear); rownames(counts)=c("Montor en linea", "Motor en V")
barplot(counts, main="Número de cambios adelante por Tipo de motor", xlab="Número de cambios adelante ",col=c("dodgerblue3","orange"),
 legend = rownames(counts))
```

![](punidad107_files/figure-html/unnamed-chunk-4-1.png)
 ]

]
[//]: <> (---------------------------------------------------------------------)

---
### Graficas variables cuantitativas con R base

.panelset[
  .panel[.panel-name[Diag.de arbol]

```
## 
##   The decimal point is at the |
## 
##   1 | 67
##   2 | 00012244444
##   2 | 555677777778
##   3 | 0000000000000011111111222222223344
##   3 | 555555566677777777888999
##   4 | 0111123
```
]
  .panel[.panel-name[Histograma]

```r
h1=hist(nf, main = "Nota final matemáticas fundamentales", xlab = "nota", ylab="frecuencias absolutas", labels=TRUE, col="dodgerblue3", ylim = c(0,30))
abline(v=3,col="red")
grid()
```

![](punidad107_files/figure-html/unnamed-chunk-7-1.png)
 ]

.panel[.panel-name[Diag.de Densidad]

![](punidad107_files/figure-html/unnamed-chunk-8-1.png)
 ]
 
.panel[.panel-name[Diag.de Cajas]

![](punidad107_files/figure-html/unnamed-chunk-9-1.png)
 ] 
 
.panel[.panel-name[Diag.de cajas~factor]

```r
nf=c(4.1, 2.7, 3.1, 3.2, 3.0, 3.2, 2.0, 2.4, 1.6, 3.2, 3.1, 2.6, 2.0, 2.4, 2.8, 3.3, 4.0, 3.4, 3.0, 3.1, 2.7, 2.7, 3.0, 3.8, 3.2, 2.2, 3.5, 3.5, 3.8, 3.5, 3.9, 4.2, 4.3, 3.9, 3.2, 3.5, 3.5, 3.7, 4.1, 3.7, 3.5, 3.6, 3.2, 3.1, 3.4, 3.0, 3.0, 3.0, 2.7, 1.7, 3.6, 2.1, 2.4, 3.0, 3.1, 2.5, 2.5, 3.6, 2.2, 2.4, 3.1, 3.3, 2.7, 3.7, 3.0, 2.7, 3.0, 3.2, 3.1, 2.4, 3.0, 2.7, 2.5, 3.0, 3.0, 3.0, 3.2, 3.1, 3.8, 4.1, 3.7, 3.5, 3.0, 3.7, 3.7, 4.1, 3.7, 3.9, 3.7, 2.0)
cc=c(20, 10, 20, 20, 20, 20, 20, 20, 20, 30, 20, 20, 20, 10, 30, 20, 20, 30, 20, 30, 30, 20, 10, 30, 20, 20, 30, 30, 10, 20, 10, 20, 20, 20, 10, 20, 10, 20, 20, 30, 30, 30, 10, 30, 20, 20, 20, 20, 20, 20, 10, 20, 30, 30, 10, 10, 10, 20, 10, 20, 10, 30, 20, 10, 20, 30, 10, 30, 30, 30, 20, 30, 30, 30, 30, 30, 30, 20, 10, 30, 10, 20, 20, 10, 20, 20, 20, 20, 10, 20)
labs=c("Ing. Industrial","Administración ","Contaduría ")
boxplot((nf~cc),main="Nota final matemáticas fundamentales por carrera", col="dodgerblue3"); abline(h=3, col="red"); abline(h=4, col="blue")
```

![](punidad107_files/figure-html/unnamed-chunk-10-1.png)
 ] 
.panel[.panel-name[Diag.de Dispersiòn]

```r
ed=round(rnorm(90,18,1),1)
plot(ed,nf, main="Edad vs Nota final matemáticas fundamentales", ylim = c(0,5), xlab = "Edad", ylab = "Nota final",col="dodgerblue3",pch=19, las=1)
grid()
```

![](punidad107_files/figure-html/unnamed-chunk-11-1.png)
 ] 
 
.panel[.panel-name[Series de tiempo]

```r
plot(AirPassengers, main="Número de pasajeros por mes", col="dodgerblue3", lwd = 2)
```

![](punidad107_files/figure-html/unnamed-chunk-12-1.png)
 ]
.panel[.panel-name[Resumen]

```r
x=rnorm(100,100,20)
y=rnorm(100,100,25)
z=rbinom(100,4,0.30)
t=1:100
par(mfrow=c(1, 5))
pie(table(z))
barplot(table(z))
stem(x)
hist(x)
boxplot(x)
plot(x,y)
plot(t,y, type="l")
plot(density(x))
```

] 
]
---
[//]: <> (---------------------------------------------------------------------)
### Gráficos con **ggplot2**
.pull-left[

+ **Data**: capa de los datos

+ **Aesthetics**: capa estetica (**aes**), definimos las variables a utilizar en el gráfico

+ **Geometries**: capa de geometrias, se define el tipo de gráfica a realizar

+ **Facets**: capa de facetas, permite detallar la gráfica por categorias

+ **Statistics**: capa de estadística, permite agregar modelos

+ **Coordinates**: capa de coordenadas, permite ajustar las escalas de los ejes

+ **Theme**: capas de características del gráfico que no dependen de  los datos

]
.pull-right[
![](img/ge_themes.png)
]

**Gramática de los gráficos**
---
.pull-left[

[Visualización de datos con ggplot2](https://rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf)

```r
library(readr)
library(ggplot2)
clasificacion=read.csv("data/futbol.csv")
ggplot(clasificacion, aes(x=off , y=def))
```

![](punidad107_files/figure-html/unnamed-chunk-14-1.png)
]
.pull-right[
![](img/ge_data.png)
]

---
.pull-left[

```r
ggplot(clasificacion, aes(x=off , y=def))+
  geom_point()
```

![](punidad107_files/figure-html/unnamed-chunk-15-1.png)
]
.pull-right[
![](img/ge_aes.png)
]

---
.pull-left[

```r
ggplot(clasificacion, aes(x=off , y=def))+
  geom_point()
```

![](punidad107_files/figure-html/unnamed-chunk-16-1.png)

]
.pull-right[
![](img/ge_geom.png)
+ geo_point()
+ geom_bar()  geom_col()  stat_count()
+ geom_boxplot()         stat_boxplot()
+ geom_density()         stat_density()
+ geom_histogram()
+ geom_violin()
+ ...
]
---
.pull-left[

```r
ggplot(clasificacion, aes(x=off , y=def))+
  geom_point()+
  facet_wrap(~ confed)
```

![](punidad107_files/figure-html/unnamed-chunk-17-1.png)

]
.pull-right[
![](img/ge_facet.png)
]
---
.pull-left[

```r
ggplot(clasificacion, aes(x=off , y=def))+  geom_point()+
  facet_wrap(~ confed)+ stat_smooth(method = "loess" , formula =y ~ x)
```

![](punidad107_files/figure-html/unnamed-chunk-18-1.png)
]
.pull-right[
![](img/ge_stats.png)
]
---
.pull-left[
![](img/ge_coord.png)
]
.pull-right[

```r
ggplot(clasificacion, aes(x=off , y=def))+  geom_point()+  facet_wrap(~ confed)+ stat_smooth(method = "loess" , formula =y ~ x)+
  	coord_cartesian(ylim = c(0, 10))
```

![](punidad107_files/figure-html/unnamed-chunk-19-1.png)
]

---

```r
library(ggplot2)
data=data.frame(grupo=c("A","B","E"),frecuencia=c(26,35,19))
ggplot(data, aes(x=grupo, y=frecuencia)) +
  geom_bar(stat="identity", fill="steelblue")+
  geom_text(aes(label=grupo), vjust=1.6, color="white", size=3.5)+
  theme_minimal()
```

![](punidad107_files/figure-html/unnamed-chunk-20-1.png)

---

```r
library(ggplot2)
ggplot(mtcars, aes(x=mpg, y=wt, colour = cyl)) + 
  geom_point()
```

![](punidad107_files/figure-html/unnamed-chunk-21-1.png)

---

```r
data("iris")
ggplot(iris, aes(Sepal.Length)) +
       geom_histogram(bins = 7,fill="#69b3a2", color="#e9ecef", alpha=0.9)+
       theme_minimal() +
       labs(x = "Nota", y = "n") +
       ggtitle(" Promedio acumulado estudiantes de PyE 2021-1")
```

![](punidad107_files/figure-html/unnamed-chunk-22-1.png)

---

```r
library(ggplot2)
ventas = read.csv("data/ventas.csv")
ggplot(ventas, aes(x=Edad, y=Tipo_Cliente)) +
  geom_boxplot(fill="#313ae8",              # color de relleno
               color="#bf6f2e",             # color de lineas
               alpha=0.5)+
  geom_point(color="#b431e8",alpha=0.9) 
```

![](punidad107_files/figure-html/unnamed-chunk-23-1.png)

```r
# Colour picker
```

[Análisis de datos con R Cap,7 ggplot2](https://rafalab.github.io/dslibro/ggplot2.html) 
[ggplot2 resumen](https://rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf)

---
## Gráficos con highcharter
<img src="img/highcharter.png" width="300">

https://jkunst.com/highcharter/

https://rstudio-pubs-static.s3.amazonaws.com/320413_6ab300527e8548b1a3cbd0d4c6200fcc.html

---
## Gráficos con plotly

https://plotly.com/r/

https://plotly-r.com/

---
## Gráficos con Shiny

+ [Genoma humano](https://shiny.rstudio.com/gallery/genome-browser.html)

+ [Paquetes de R](https://gallery.shinyapps.io/087-crandash/)

+ [Galeria](https://shiny.rstudio.com/gallery/)

---
### RMarkdown
<img src="img/hex-rmarkdown.png" width="300">

[RMarkdown resumen](https://rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf)

[R flexdashboard - ejemplo](https://rpubs.com/joscani/flexdashboard_examples) 
[R flexdashboard - implementaciòn](https://geoprocesamiento-2020i.github.io/tutorial-flexdashboard/)

---
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background-image: url("img/pujcali.jpeg")

### Una imagen dice mas que mil palabras... 
##### Daniel Enrique González Gómez 
Imagen tomada de :https://javerianacali.edu.co/noticias/la-javeriana-bogota-y-cali-1-de-colombia