---
title: Gapminder


output: 
  flexdashboard::flex_dashboard:
    theme: sandstone
    social: menu
    source_code: embed
    orientation: columns
    vertical_layout: fill
---


```{r setup, include=FALSE}
library(flexdashboard)
library(yaml)
library(knitr)
require(plotly)
library(ggplot2)
require(gganimate)
require(esquisse)
require(gapminder)
library(ggplot2)
library(kableExtra)
library(animation)
gap <- gapminder
```



**Descripción de la base** 
=======================================================================

Column {data-width=500}
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### **Descripción**

- Extracto de los datos de Gapminder sobre la esperanza de vida, el PIB per cápita y la población por país, el marco principal de datos de gapminder tiene 1704 filas y 6 variables:

- **país**: factor con 142 niveles
- **continente**: factor con 5 niveles
- **año**: va de 1952 a 2007 en incrementos de 5 años
- **lifeExp**: esperanza de vida al nacer, en años
- **pop**: población
- **gdpPercap**: PIB per cápita (dólares de los EE.UU., ajustado a la inflación)


Column {data-width=500}
-----------------------------------------------------------------------


### **Resumen**

```{r}
resumen <- summary(gap)
kable(resumen) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed"))
  
```


### **Estructura**

```{r}
st <- str(gap)
st
  
```


**Análisis descriptivo Part 1**
=======================================================================

Column {data-width=500}
-----------------------------------------------------------------------

### **Gráfico Interactivo**

```{r}
p <- ggplot(gap, aes(gdpPercap,lifeExp,size = pop, colour = continent))+
  geom_point(alpha = 0.5)+
  scale_x_log10()

gap %>% 
  plot_ly(
    x = ~log(gdpPercap),
    y = ~lifeExp,
    size = ~log(pop),
    color = ~continent,
    frame = gap$year,
    alpha = 0.5
    
  )
```



Column {data-width=500}
-----------------------------------------------------------------------

### **Gráfico de lineas**


```{r}
p <- ggplot(gap,aes(x=gdpPercap,y=lifeExp,colour=continent))+ geom_point() + transition_reveal(gap$year) +
  shadow_wake(wake_length = 0.8, alpha = T)
animate(p)
```



**Análisis descriptivo Part 2**
=======================================================================

Row
-----------------------------------------------------------------------

### **Boxplot**
```{r}
p <- ggplot(gap, aes(x=continent, y=lifeExp, fill=continent, color=continent)) + 
    geom_boxplot(alpha=0.3)+
  ggtitle('Boxplot')

ggplotly(p)

```



### **Densidad para LifeExp**

```{r}
k <- ggplot(gap, aes(x=lifeExp))+
  geom_histogram(fill='lightseagreen', color="lightseagreen", alpha=0.5)+
  ggtitle('Densidad para lifeExp')

ggplotly(k)

```


Row
-----------------------------------------------------------------------


### **Barplot**

```{r}
j <- ggplot(gap, aes(x=continent)) + geom_bar(fill=c('lightseagreen','lightskyblue','lightskyblue1',
                       'lightskyblue2', 'lightskyblue3')) +
  ggtitle('Barplot por continente') 

ggplotly(j)
 
```

### **Densidad por continente**

```{r}
m <- ggplot(gap, aes(x=lifeExp, colour=continent, fill=continent))+
  geom_density(alpha=0.4)
ggplotly(m)
```