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@RamiKrispin
Created May 9, 2020 23:29
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#---------------------------------------------------------
# Creating a trajectory plot for covid19 confirmed cases
# Required packages - dplyr, tidyr, and plotly packages
# Data - coronavirus package
#---------------------------------------------------------
# To get the most update data use the Github version
#devtools::install_github("RamiKrispin/coronavirus")
library(coronavirus)
`%>%` <- magrittr::`%>%`
# Trajectory function
covid_trajec <- function(min_case = 100, max_days = 80, country){
country_df <- lapply(country, function(i){
df <- coronavirus %>% dplyr::filter(type == "confirmed", Country.Region == i) %>%
dplyr::group_by(date) %>%
dplyr::summarise(cases = sum(cases)) %>%
dplyr::ungroup() %>%
dplyr::arrange(date) %>%
dplyr::mutate(total = cumsum(cases),
country = i) %>%
dplyr::filter(total > min_case) %>%
dplyr::select(-cases, -date)
if(nrow(df) > max_days){
df <- df[1:max_days,]
}
df$index <- 1:nrow(df)
return(df)
}) %>% dplyr::bind_rows() %>%
tidyr::pivot_wider(names_from = country, values_from = total) %>%
as.data.frame()
p <- plotly::plot_ly()
for(i in 2:ncol(country_df)){
p <- p %>%
plotly::add_lines(x = country_df$index,
y = country_df[, i],
name = names(country_df)[i], line = list(width = 2))
}
# Set or modify here the layout/titles
p <- p %>% plotly::layout(title = "Covid19 Confirmed Cases Trajectory Plot",
yaxis = list(title = "Cumulative Positive Cases",type = "log"),
xaxis = list(title = paste("Days since the total positive cases surpass", min_case)),
hovermode = "compare")
return(p)
}
# Example for function setting
min_case <- 100
max_days <- 80
country <- c("China", "Italy", "Iran", "United Kingdom", "Spain", "France", "Russia", "Korea, South", "US")
covid_trajec(min_case = min_case, max_days = max_days, country = country)
@liamxg
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liamxg commented Jan 28, 2021

image

This is what i made for China province.

image

@liamxg
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liamxg commented Jan 28, 2021

This is very nice.

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