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) |
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This is what i made for China province.