U1A3
Andres
9/2/2020
U1A3 Distribución de frecuencia de casos confirmados, decesos, recuperados de
COVID-19 en Venezuela usando datos de la universidad Johns Hopkins
Importar paquetes
library(readr) #leer archivos
library(plotly) #Graficos interactivos## Loading required package: ggplot2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutlibrary(tidyverse) #paquete de ciencia de datos## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --## v tibble 3.0.3 v dplyr 1.0.2
## v tidyr 1.1.1 v stringr 1.4.0
## v purrr 0.3.4 v forcats 0.5.0## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks plotly::filter(), stats::filter()
## x dplyr::lag() masks stats::lag()library(gganimate) #Animar graficas
library(gifski) #Hacer GIF'sLeer las URL de datos del repositorio de JHU
url_conf <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv"
url_decesos <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv"
url_recuperados <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv"*Descargar los archivos Archivos de valores separados por comas
datos_conf <- read.csv(url_conf)
datos_decesos <-read.csv(url_decesos)
datos_recuperados <- read.csv(url_recuperados)- Extraer los datos para Venezuela
conf_ven <- t(datos_conf [datos_conf$Country.Region=="Venezuela" ,])
dec_ven <- t(datos_decesos [datos_decesos$Country.Region=="Venezuela" ,])
rec_ven <- t(datos_recuperados [datos_recuperados$Country.Region=="Venezuela" ,])Ordenar y transformar
Primaras graficas para reconocimiento
plot(conf_ven)## Warning in xy.coords(x, y, xlabel, ylabel, log): NAs introduced by coercion
plot(dec_ven)## Warning in xy.coords(x, y, xlabel, ylabel, log): NAs introduced by coercion
plot(rec_ven)## Warning in xy.coords(x, y, xlabel, ylabel, log): NAs introduced by coercion
- Transformacion de datos
Fecha <- seq(from = as.Date("2020-01-22"), to = as.Date("2020-09-03"),
by = "day")
#Datos transformados a vector numéricos
#Confirmados
vec1 <- as.vector(conf_ven) # Transformaciön lista a vector
vec2 <- vec1[5:230] #filtrado de los primeros 4 valores
num1 <- as.numeric(vec2) #transformación a datos numérico
Confirmados <- as.vector(num1) #vector numérico
#Datos transformados a vector numéricos
#decesos
vec1 <- as.vector(dec_ven) # Transformaciön lista a vector
vec2 <- vec1[5:230] #filtrado de los primeros 4 valores
num1 <- as.numeric(vec2) #transformación a datos numérico
Decesos <- as.vector(num1) #vector numérico
#Datos transformados a vector numéricos
#Recuperados
vec1 <- as.vector(rec_ven) # Transformaciön lista a vector
vec2 <- vec1[5:230] #filtrado de los primeros 4 valores
num1 <- as.numeric(vec2) #transformación a datos numérico
Recuperados <- as.vector(num1) #vector numérico
#generación de un data frame
datos1 <- data.frame(Fecha, Confirmados, Decesos, Recuperados)
#Figura 2 Confirmados ggplot
ggplot(data = datos1) +
geom_line(mapping = aes(x = Fecha, y = Confirmados))
#Figura 3 Recuperados ggplot
ggplot(data = datos1) +
geom_line(mapping = aes(x = Fecha, y = Recuperados))
#Figura 4 Decesos ggplot
ggplot(data = datos1) +
geom_line(mapping = aes(x = Fecha, y = Decesos))
#Animación 1 simple
ggplot(data = datos1) +
geom_line(mapping = aes(x = Fecha, y = Confirmados)) +
ggtitle("Casos acumulados confirmados de COVID-19 en Venezuela") +
transition_reveal(Fecha)
#Gráfica multiejes
ggplot(data=datos1) +
geom_line(aes(x=Fecha, y=Confirmados), colour="red") +
geom_line(aes(x=Fecha, y=Decesos), colour="green") +
geom_line(aes(x=Fecha, y=Recuperados), colour="blue") +
ylab("COVID-19 en Venezuela") + xlab("Fecha")
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## - attr(*, "validate")= logi TRUE#Animacion 2
gcov <- ggplot(data=datos1) +
geom_line(aes(x=Fecha, y=Confirmados), colour="red") +
geom_line(aes(x=Fecha, y=Decesos), colour="blue") +
geom_line(aes(x=Fecha, y=Recuperados), colour="green") +
ylab("COVID-19 en Venezuela") + xlab("Fecha")
transition_reveal(Fecha)## <ggproto object: Class TransitionReveal, Transition, gg>
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## super: <ggproto object: Class TransitionReveal, Transition, gg>ggplotly(gcov)