#Plots

#Variables cualitativas (Categorías) ¬Ordinales ¬Nominales

#Cuantitativas ¬Continuas ¬Discretas

#clasificar de su dataset las variables

library(dslabs)
library(dplyr)
## 
## Adjuntando el paquete: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(viridisLite)
library(RColorBrewer)
data("stars")

#Descripción del dataset

#Variables cualitativas nominales:
"
  -Star
  -Type
  "
## [1] "\n  -Star\n  -Type\n  "
#Variables cuantitativas discretas:
  "
  -Temp
  "
## [1] "\n  -Temp\n  "
#Variables cuantitativas Continuas:
  "
  -Magnitude
  "
## [1] "\n  -Magnitude\n  "

#Diagrama de barras

#Orden especifico
tipos<-factor(stars$type,levels = c("M", "B", "K", "A", "F", "G", "DA", "DB", "DF", "O"))
tabla_tipos <- table(tipos)

#PRimero hay qeu hacer conteo
tabla_tipos
## tipos
##  M  B  K  A  F  G DA DB DF  O 
## 32 19 16 13  7  4  2  1  1  1
#Diagrama

barplot(
  tabla_tipos,                                     #Datos
  main = "Gráfico de barras (Tipos de estrellas)", #Título principal
  ylab ="Frecuencia",                              #titulo del eje X
  xlab = "Tipos de estrellas",                     #Título del eje Y
  ylim = c(0, 40),                                 #Frecuencias del eje Y
  col = viridis(4))                    #Colores (en lugar de viridis se puede especificar un color "blue")   
grid(nx=NA, ny=NULL, col = "lightgray", lty = "dotted", lwd = par("lwd"))

#Diagrama circular

porcentajes <- round(tabla_tipos*100/sum(tabla_tipos),1)
porcentajes
## tipos
##    M    B    K    A    F    G   DA   DB   DF    O 
## 33.3 19.8 16.7 13.5  7.3  4.2  2.1  1.0  1.0  1.0
pie(
  porcentajes,
  labels = paste(porcentajes, "%"),
  main = "Tipos de estrellas",
  col = brewer.pal(10, "Paired"),
  border = brewer.pal(10, "Paired"),
  cex=0.6
)

  legend("bottomright", legend = names(porcentajes), fill =  brewer.pal(10, "Paired"))

#Variables cuantitativas

media <- mean(stars$temp)
mediana <-median(stars$temp)

#HISTOGRAMAS MAGNITUDES

hist(stars$temp, 
     breaks = "Sturges",
     main = "Histogram of temperatures",
     xlab= "Population in US",
     ylim = c(0,50),
     col = brewer.pal(8, "Pastel2"),
   
     border = brewer.pal(8, "Set1"),
     labels = TRUE
     )
     axis(1, at = seq(floor(min(stars$temp)), ceiling(max(stars$temp)), by = 10000))

hist(stars$temp, 
     breaks = "Sturges",
     probability = TRUE,
     main = "Histogram of temperatures",
     xlab= "Population in US",
     col = brewer.pal(8, "Pastel2"),
     border = brewer.pal(4, "Set1"))
     lines(density(stars$temp), col ="black", lwd=2)
     
      abline(v = media, col = "red", lwd = 2, lty = 2)     # Línea de la media (roja)
      abline(v = mediana, col = "green", lwd = 2, lty = 2)  # Línea de la mediana (verde)
      
      legend("topright", legend = c("Media", "Mediana"), 
       col = c("red", "green"), lwd = 2, lty = 2)

       #Es una distribución asimétrica hacia la izquierda, donde el promedio es menor que la mediana en la curva

     
     #Interpretar los gráficos

     
     #Agregar dos lineas verticales (Mediana, Promedio)

5 BoxPlots

boxplot(stars$temp, col="Blue",ylab="Temperaturas",outline=FALSE,main="Boxplot",ylim=c(0,18500))
#Adicionar la media
points(mean(stars$temp),col="black",pch=21)
text(paste(" ", round(mean(stars$temp), 2)),x=1.1, y=8000)

4: Boxplot con media y mediana

############################################################3


#######################################

boxplot(stars$temp, col="Blue",ylab="Temperaturas",outline=FALSE,main="Boxplot",ylim=c(0,18000))
#Adicionar la media
points(mean(stars$temp),col="black",pch=21)
text(paste(" ", round(mean(stars$temp), 2)),x=1.1, y=8000) 


points(round(min(stars$temp)),col="red",pch=18)
text(paste(" ", min(stars$temp), 2),x=1.1, y=min(stars$temp)-1000)

  legend("topright", legend = c("Media", "Mediana"), 
       col = c("Orange", "red"), lwd = 2, lty = 2)

abline( h = mean(stars$temp), col="Orange",lwd = 1, lty = 2)
abline( h = median(stars$temp), col ="Red", lwd = 1, lty = 2)

##Comparación cuantitativas/Cualitativas

x<- stars$temp
y<- stars$magnitude




plot(x,y,main="Temperature vs Magnitude",col=as.factor(stars$type),pch=20,xlab = "Temperature",ylab="Magnitud")
legend("bottomright",legend=levels(as.factor(stars$type)),fill = unique(as.factor(stars$type)),cex=0.75)

Boxplots

boxplot(temp~type,data=stars,col=brewer.pal(9,"Set1"),outline=FALSE,ylim=c(2000,35000),main="Boxplot")
abline(h=mean(stars$temp),col="blue",lwd=2)
text(paste("",round(mean(stars$temp),2)),x=0.8,y=5500,col="blue")

## Tabla gráficos

par(mfrow=c(1,2))

plot(x,y,main="Temperature vs Magnitude",col=as.factor(stars$type),pch=20,xlab = "Temperature",ylab="Magnitud")
legend("bottomright",legend=levels(as.factor(stars$type)),fill = unique(as.factor(stars$type)),cex=0.75)

boxplot(temp~type,data=stars,col=brewer.pal(9,"Set1"),outline=FALSE,ylim=c(2000,35000),main="Boxplot")
abline(h=mean(stars$temp),col="blue",lwd=2)
text(paste("",round(mean(stars$temp),2)),x=0.8,y=5500,col="blue")