TInfor

library(tidyverse)

## Warning: package 'tidyverse' was built under R version 4.1.3

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## v tidyr   1.2.0     v stringr 1.4.0
## v readr   2.1.2     v forcats 0.5.1

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::between()   masks data.table::between()
## x dplyr::filter()    masks stats::filter()
## x dplyr::first()     masks data.table::first()
## x dplyr::lag()       masks stats::lag()
## x dplyr::last()      masks data.table::last()
## x purrr::map()       masks maps::map()
## x purrr::transpose() masks data.table::transpose()

cel %>%
  filter(congress == 115) %>% 
  mutate( Mayoria = ifelse(majority == 1, "Majority", "Minority")) %>% 
  ggplot(aes(Mayoria, les)) + 
  geom_boxplot() + 
  ggtitle("LES in the 115th Congress") + # Título del plot
  xlab("Majority or Minority") +
  ylab ("Legislative Effectiveness")

####PuntoDos  
library(stats)
# Creando Vectores.

Estudiante <- c("Diana","David","Carol")

Semestre <- c(1,1,1,2,2,2,
              3,3,3,4,4,4,
              5,5,5,6,6,6)

set.seed(1234)
Grado <- runif(18, min=80, max=100) 

#Data.Frame
datos <- data.frame(Estudiante, Semestre, Grado)

#Gráfico
library(ggplot2)
ggplot(datos, aes(x=Semestre, y=Grado, group = Estudiante, colour =Estudiante )) + 
  geom_line()  + 
  geom_point( size=2, shape=21, fill="white") + 
  theme_gray()+
  facet_wrap(vars(Estudiante), nrow = 1)

####PuntoTres
cel %>%
  filter(congress == 115) %>%
  mutate (Genre = ifelse(female == 1,"Male","Female")) %>%
  ggplot(aes(x= year, y=all_pass, fill = Genre ))+
  geom_col()+
  ggthemes::theme_fivethirtyeight()+
  scale_y_continuous(labels = scales::percent)

####PuntoCuatro 
library(sf)

## Warning: package 'sf' was built under R version 4.1.3

## Linking to GEOS 3.9.1, GDAL 3.2.1, PROJ 7.2.1; sf_use_s2() is TRUE

## 
## Attaching package: 'sf'

## The following object is masked from 'package:transformr':
## 
##     st_normalize

library(rnaturalearth)

## Warning: package 'rnaturalearth' was built under R version 4.1.3

library(rnaturalearthdata)

## Warning: package 'rnaturalearthdata' was built under R version 4.1.3

library(rgeos)

## Warning: package 'rgeos' was built under R version 4.1.3

## Loading required package: sp

## Warning: package 'sp' was built under R version 4.1.3

## rgeos version: 0.5-9, (SVN revision 684)
##  GEOS runtime version: 3.9.1-CAPI-1.14.2 
##  Please note that rgeos will be retired by the end of 2023,
## plan transition to sf functions using GEOS at your earliest convenience.
##  GEOS using OverlayNG
##  Linking to sp version: 1.4-6 
##  Polygon checking: TRUE

library(ggplot2)

#Base de datos #1
mapa_mundo = map_data("world")
View(mapa_mundo)
ggplot(data = mapa_mundo, aes(x = long, y = lat, group=group))+
  geom_polygon(color= "black", fill = "white")

suramerica<- mapa_mundo %>%
  filter(region == c("Argentina","Colombia", "Ecuador", "Peru","Bolivia","Brazil","Chile","Ecuador","Guyana",
                     "Paraguay","Suriname","Uruguay","Venezuela")) 

## Warning in region == c("Argentina", "Colombia", "Ecuador", "Peru", "Bolivia", :
## longitud de objeto mayor no es múltiplo de la longitud de uno menor

#Base de datos #2
s_america<-ne_countries(scale="medium",continent='south america',returnclass="sf")%>%
  rename(region=sovereignt)

#Base de datos unificada
data_unificada <- suramerica %>%
  left_join(s_america, by = "region")

#Map
ggplot(data_unificada, aes(x= long, y = lat,group=group, fill = pop_est))+
  geom_polygon(color = "black")+
  theme(axis.text.x = element_text(),
        axis.text.y = element_text(),
        axis.ticks = element_blank())+
  labs(x="long", y="lat")+
  scale_fill_distiller(palette=10)

##PuntoCinco
library(tidyverse)
library(gganimate)

## Warning: package 'gganimate' was built under R version 4.1.3

#Base de datos
Category<-c("Alpha","Beta","Zeta")
City<-c("Hong Kong","London","Nairobi")

my_dat<-expand_grid(Category,City)
set.seed(84684)
my_dat$Value<-sample(1:10,9,replace=T)


#Gráfico
library(ggplot2)
animacion<- ggplot(my_dat, aes(x = Category, y= Value, fill= City) ) +                        
  geom_bar(width = 0.9, stat="identity", position = position_dodge())+                    
  labs(x="Category", y= "Value") +   
  labs(fill = "City")+
  transition_states(City)+
  enter_fade()+
  exit_shrink() + 
  ease_aes("sine-in-out") 

animacion

```