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#---------------------------------------- |
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# Plotting the daily new confirmed cases |
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# China vs. rest of the world |
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#---------------------------------------- |
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# Data: coronavirus dataset from the coronavirus package |
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# Using github version as it update the data on daily bases |
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#---------------------------------------- |
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# Installing most recent version from Github |
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# must reset the R session after installation |
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# install.packages("devtools") |
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devtools::install_github("RamiKrispin/coronavirus") |
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#---------------------------------------- |
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# Loading the package and dataset |
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library(coronavirus) |
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data("coronavirus") |
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#---------------------------------------- |
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# Required packages |
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# Data manipulation - dplyr and tidyr |
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# Data viz - plotly |
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#---------------------------------------- |
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# Manipulate the data to daily confirmed cases China vs. rest of the world |
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|
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daily_confirmed <- coronavirus %>% |
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dplyr::mutate(country = dplyr::if_else(Country.Region == "Mainland China", |
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"China", |
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"Rest of the World")) %>% |
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dplyr::group_by(date, country) %>% |
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dplyr::summarise(total = sum(cases)) %>% |
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dplyr::ungroup() %>% |
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tidyr::pivot_wider(names_from = country, values_from = total) |
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#---------------------------------------- |
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# Plotting the data |
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daily_confirmed %>% |
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plotly::plot_ly(x = ~date, |
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y = ~ China, |
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name = 'China', |
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type = 'scatter', |
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mode = 'none', |
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stackgroup = 'one', |
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groupnorm = 'percent', |
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fillcolor = 'red') %>% |
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plotly::add_trace(y = ~ `Rest of the World`, name = 'Rest of the World', fillcolor = 'yellow') %>% |
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plotly::layout(title = "Coronavirus Daily Confirmed Cases Dist - China vs. Rest of the World", |
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yaxis = list(title = "Proportion of New Cases", ticksuffix = '%'), |
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xaxis = list(title = "Date"), |
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legend = list(orientation = 'h'), |
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paper_bgcolor = "black", |
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plot_bgcolor = "black", |
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font = list(color = 'white'), |
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margin = list( |
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l = 60, |
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r = 40, |
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b = 50, |
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t = 50, |
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pad = 4 |
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)) |
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