Covid 2022 OMS

covidData <- read.csv("https://covid19.who.int/WHO-COVID-19-global-data.csv")
names(covidData)[1]<-("Date_reported")
covidData$Date_reported<-as.Date(covidData$Date_reported, format="%Y-%m-%d")

casos<-subset(covidData,covidData$Date_reported=="2022-01-28")


mapa <- read.csv2("map_2022.csv")
library(ggplot2)

mapaViz <- ggplot(mapa, aes(long, lat, group=as.factor(group)))
mapaViz <- mapaViz + geom_line()
mapaViz

casos<-subset(covidData,covidData$Date_reported=="2022-01-28")


mapa <- read.csv2("map_2022.csv")
library(ggplot2)

mapaViz <- ggplot(mapa, aes(long, lat, group=as.factor(group)))
mapaViz <- mapaViz + geom_polygon(aes (fill=sub.region))
mapaViz

#Cambiar dataframe

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

CovidMapa <- left_join(casos, mapa, by =c("Country_code"="ISO2"))
                       
mapaViz <- ggplot(CovidMapa, aes(long, lat, group=as.factor(group), fill=New_cases))
mapaViz <- mapaViz + geom_polygon()
mapaViz

CovidMapa <- left_join(casos, mapa, by =c("Country_code"="ISO2"))
                       
mapaViz <- ggplot(CovidMapa, aes(long, lat, group=as.factor(group), fill=log10(New_cases)))
mapaViz <- mapaViz + geom_polygon()
mapaViz <- mapaViz + scale_fill_viridis_c()
mapaViz

CovidMapa <- left_join(casos, mapa, by =c("Country_code"="ISO2"))
                       
mapaViz <- ggplot(CovidMapa, aes(long, lat, group=as.factor(group), fill=log10(New_cases)))
mapaViz <- mapaViz + geom_polygon()
#mapaViz <- mapaViz + scale_fill_viridis_c()
mapaViz <- mapaViz + scale_fill_gradient(low = "#132B43", high = "#56B1F7", space="lab", na.value = "grey50", trans="log10")

## Warning: Non Lab interpolation is deprecated

mapaViz <- mapaViz + labs(tittle="Nuevos Casos de Covid 19 en enero de 2022", caption = "Territorios sin datos en gris. Escala Cromatica en logaritmo base 10")
mapaViz

## Warning in self$trans$transform(x): Se han producido NaNs

# subset casos de ayer
casos <- subset(covidData, covidData$Date_reported =="2022-01-28")

# cargar el mapa
mapa <- read.csv2("map_2022.csv")
mapa <- subset(mapa, mapa$sub.region =="Latin America and the Caribbean")

library(ggplot2)

mapaViz <- ggplot(mapa, aes(long,lat, group= as.factor(group), fill=sub.region))
mapaViz <- mapaViz + geom_polygon()
mapaViz

# combinar dataframes

library(dplyr)

covidMapa <- left_join(casos, mapa, by = c("Country_code" = "ISO2"))

mapaViz <- ggplot(covidMapa, aes(long,lat, group= as.factor(group), fill=New_cases))
mapaViz <- mapaViz + geom_polygon()
#mapaViz <- mapaViz + scale_fill_viridis_c()
mapaViz <- mapaViz + scale_fill_gradient( low = "#132B43", high = "#56B1F7",  space = "Lab", na.value = "grey50",trans="log10")
mapaViz <- mapaViz + labs(title="Nuevos casos Covid-19 en enero 28 de 2022", caption="Tarritorios sin datos en gris. Escala cromatica en logaritmo base 10")
mapaViz

## Warning: Transformation introduced infinite values in discrete y-axis