In averissimo/r-analysis-covid19: COVID-19 Data Analysis
Main Analysis
Deaths / Cases rate {.tabset .tabset-fade .tabset-pills}
Rate of death per number of confirmed case. Note that this is heavily dependand on the number of tests being performed (data not available in this report)
death.vs.cases.plot(death.vs.cases, state.filter = countries, expand = FALSE)
Cases over time {.tabset .tabset-fade .tabset-pills}
Confirmed cases {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
suppressWarnings({
p <- ommit.start(after.100.dat$all, 'confirmed', params$confirmed.start, filter.states = countries, per.100k.flag = TRUE) %>% ggplotly() %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE),
absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text, absolute) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d.tmp <- d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = ~absolute,
hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
d.tmp
per 100k population (log10 scale)
d.tmp %>%
layout(yaxis = list(type = 'log'))
Total values
suppressWarnings({
p <- ommit.start(after.100.dat$all, 'confirmed', params$confirmed.start, filter.states = countries) %>% ggplotly() %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Log10 scale
suppressWarnings({
p <- ommit.start(after.100.dat$all, 'confirmed', params$confirmed.start, filter.states = countries, log2.flag = TRUE) %>% ggplotly() %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = gsub('log2', 'log10', p$x$layout$yaxis$title$text), type = 'log')) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
suppressWarnings({
p <- ommit.start(after.100.dat$all, 'death', params$death.start, filter.states = countries, per.100k.flag = TRUE) %>% ggplotly() %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE),
absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text, absolute) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d.tmp <- d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = ~absolute,
hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
d.tmp
per 100k population (log10 scale)
d.tmp %>%
layout(yaxis = list(type = 'log'))
Total deaths
suppressWarnings({
p <- ommit.start(after.100.dat$all, 'death', params$death.start, filter.states = countries) %>% ggplotly() %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Log10 scale
suppressWarnings({
p <- ommit.start(after.100.dat$all, 'death', params$death.start, filter.states = countries, log2.flag = TRUE) %>% ggplotly() %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = gsub('log2', 'log10', p$x$layout$yaxis$title$text), type = 'log')) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
New Cases and Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
Cases {.tabset .tabset-fade .tabset-pills}
per 100k population
New Confirmed Cases (per 100k population).
suppressWarnings({
p <- last.days(last.days.dat, 'confirmed', params$last.days, countries, log2.flag = FALSE, per.100k.flag = TRUE, new.flag = TRUE) %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE),
absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Confirmed Cases' = cumul, text, absolute) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = ~absolute,
hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Total
suppressWarnings({
p <- last.days(last.days.dat, 'confirmed', params$last.days, countries, log2.flag = FALSE, per.100k.flag = FALSE, new.flag = TRUE) %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Confirmed Cases' = cumul, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Confirmed Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
New Deaths (per 100k population).
suppressWarnings({
p <- last.days(last.days.dat, 'death', params$last.days, countries, log2.flag = FALSE, per.100k.flag = TRUE, new.flag = TRUE) %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE),
absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Deaths' = cumul, text, absolute) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Deaths`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = ~absolute,
hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Total
suppressWarnings({
p <- last.days(last.days.dat, 'death', params$last.days, countries, log2.flag = FALSE, per.100k.flag = FALSE, new.flag = TRUE) %>%
ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Deaths' = cumul, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Deaths`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Rolling averages of last 7 days {.tabset .tabset-fade .tabset-pills}
Average Cases {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
Each data point is an average of new cases from the previous 7 days (per 100k population).
suppressWarnings({
p <- last.week.cumulative(last.week.dat, 'confirmed', 7, countries, log2.flag = FALSE, per.100k.flag = TRUE) %>% ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(round(last.week.var, digits = 2), big.mark = ',', trim = TRUE),
absolute = format(last.week.var * population / 100000, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Average Cases' = last.week.var, text, absolute) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d.tmp <- d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Average Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = ~absolute,
hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
d.tmp
per 100k population Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>%
layout(yaxis = list(type = 'log'))
Total
Each data point is an average of new cases from the previous 7 days.
suppressWarnings({
p <- last.week.cumulative(last.week.dat, 'confirmed', 7, countries, log2.flag = FALSE, per.100k.flag = FALSE) %>% ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(last.week.var, digits = 2, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Average Cases' = last.week.var, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d.tmp <- d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Average Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
d.tmp
Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>%
layout(yaxis = list(type = 'log'))
Average Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
Each data point is an average of new cases from the previous 7 days (per 100k population).
suppressWarnings({
p <- last.week.cumulative(last.week.dat, 'death', 7, countries, log2.flag = FALSE, per.100k.flag = TRUE) %>% ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(round(last.week.var, digits = 2), big.mark = ',', trim = TRUE),
absolute = format(last.week.var * population / 100000, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Average Deaths' = last.week.var, text, absolute) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d.tmp <- d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Average Deaths`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = ~absolute,
hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
d.tmp
per 100k population Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>%
layout(yaxis = list(type = 'log'))
Total
Each data point is an average of new cases from the previous 7 days.
suppressWarnings({
p <- last.week.cumulative(last.week.dat, 'death', 7, countries, log2.flag = FALSE, per.100k.flag = FALSE) %>% ggplotly()
})
d <- plotly_data(p) %>%
mutate(text = format(last.week.var, big.mark = ',', trim = TRUE)) %>%
select(Country = state, Date = date, 'Average Cases' = last.week.var, text) %>%
arrange(Date) %>%
highlight_key(~Country)
pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A')
d.tmp <- d %>% plot_ly() %>%
add_trace(x = ~Date,
y = ~`Average Cases`,
color = ~Country,
type = 'scatter',
mode = 'lines+markers',
colors = pal,
name = ~Country,
customdata = '',
hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'),
text = ~text
) %>%
layout(legend = list(x = 0.1, y = 1), dragmode = FALSE,
title = p$x$layout$title$text,
xaxis = list(title = p$x$layout$xaxis$title$text),
yaxis = list(title = p$x$layout$yaxis$title$text)) %>%
highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
d.tmp
Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>%
layout(yaxis = list(type = 'log'))
averissimo/r-analysis-covid19 documentation built on April 24, 2021, 11:01 a.m.
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Main Analysis
Deaths / Cases rate {.tabset .tabset-fade .tabset-pills}
Rate of death per number of confirmed case. Note that this is heavily dependand on the number of tests being performed (data not available in this report)
death.vs.cases.plot(death.vs.cases, state.filter = countries, expand = FALSE)
Cases over time {.tabset .tabset-fade .tabset-pills}
Confirmed cases {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
suppressWarnings({ p <- ommit.start(after.100.dat$all, 'confirmed', params$confirmed.start, filter.states = countries, per.100k.flag = TRUE) %>% ggplotly() %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE), absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text, absolute) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d.tmp <- d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = ~absolute, hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE) d.tmp
per 100k population (log10 scale)
d.tmp %>% layout(yaxis = list(type = 'log'))
Total values
suppressWarnings({ p <- ommit.start(after.100.dat$all, 'confirmed', params$confirmed.start, filter.states = countries) %>% ggplotly() %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Log10 scale
suppressWarnings({ p <- ommit.start(after.100.dat$all, 'confirmed', params$confirmed.start, filter.states = countries, log2.flag = TRUE) %>% ggplotly() %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = gsub('log2', 'log10', p$x$layout$yaxis$title$text), type = 'log')) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
suppressWarnings({ p <- ommit.start(after.100.dat$all, 'death', params$death.start, filter.states = countries, per.100k.flag = TRUE) %>% ggplotly() %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE), absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text, absolute) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d.tmp <- d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = ~absolute, hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE) d.tmp
per 100k population (log10 scale)
d.tmp %>% layout(yaxis = list(type = 'log'))
Total deaths
suppressWarnings({ p <- ommit.start(after.100.dat$all, 'death', params$death.start, filter.states = countries) %>% ggplotly() %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Log10 scale
suppressWarnings({ p <- ommit.start(after.100.dat$all, 'death', params$death.start, filter.states = countries, log2.flag = TRUE) %>% ggplotly() %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = days.after.100, 'Confirmed Cases' = cumul, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = gsub('log2', 'log10', p$x$layout$yaxis$title$text), type = 'log')) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
New Cases and Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
Cases {.tabset .tabset-fade .tabset-pills}
per 100k population
New Confirmed Cases (per 100k population).
suppressWarnings({ p <- last.days(last.days.dat, 'confirmed', params$last.days, countries, log2.flag = FALSE, per.100k.flag = TRUE, new.flag = TRUE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE), absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Confirmed Cases' = cumul, text, absolute) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = ~absolute, hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Total
suppressWarnings({ p <- last.days(last.days.dat, 'confirmed', params$last.days, countries, log2.flag = FALSE, per.100k.flag = FALSE, new.flag = TRUE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Confirmed Cases' = cumul, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Confirmed Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
New Deaths (per 100k population).
suppressWarnings({ p <- last.days(last.days.dat, 'death', params$last.days, countries, log2.flag = FALSE, per.100k.flag = TRUE, new.flag = TRUE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(round(cumul, digits = 2), big.mark = ',', trim = TRUE), absolute = format(cumul * population / 100000, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Deaths' = cumul, text, absolute) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Deaths`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = ~absolute, hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Total
suppressWarnings({ p <- last.days(last.days.dat, 'death', params$last.days, countries, log2.flag = FALSE, per.100k.flag = FALSE, new.flag = TRUE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(cumul, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Deaths' = cumul, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Deaths`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE)
Rolling averages of last 7 days {.tabset .tabset-fade .tabset-pills}
Average Cases {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
Each data point is an average of new cases from the previous 7 days (per 100k population).
suppressWarnings({ p <- last.week.cumulative(last.week.dat, 'confirmed', 7, countries, log2.flag = FALSE, per.100k.flag = TRUE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(round(last.week.var, digits = 2), big.mark = ',', trim = TRUE), absolute = format(last.week.var * population / 100000, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Average Cases' = last.week.var, text, absolute) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d.tmp <- d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Average Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = ~absolute, hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE) d.tmp
per 100k population Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>% layout(yaxis = list(type = 'log'))
Total
Each data point is an average of new cases from the previous 7 days.
suppressWarnings({ p <- last.week.cumulative(last.week.dat, 'confirmed', 7, countries, log2.flag = FALSE, per.100k.flag = FALSE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(last.week.var, digits = 2, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Average Cases' = last.week.var, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d.tmp <- d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Average Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE) d.tmp
Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>% layout(yaxis = list(type = 'log'))
Average Deaths {.tabset .tabset-fade .tabset-pills}
Latest data from r source.by
per 100k population
Each data point is an average of new cases from the previous 7 days (per 100k population).
suppressWarnings({ p <- last.week.cumulative(last.week.dat, 'death', 7, countries, log2.flag = FALSE, per.100k.flag = TRUE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(round(last.week.var, digits = 2), big.mark = ',', trim = TRUE), absolute = format(last.week.var * population / 100000, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Average Deaths' = last.week.var, text, absolute) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d.tmp <- d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Average Deaths`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = ~absolute, hovertemplate = paste0('<b>%{text}</b> <i>(%{customdata})</i>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE) d.tmp
per 100k population Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>% layout(yaxis = list(type = 'log'))
Total
Each data point is an average of new cases from the previous 7 days.
suppressWarnings({ p <- last.week.cumulative(last.week.dat, 'death', 7, countries, log2.flag = FALSE, per.100k.flag = FALSE) %>% ggplotly() }) d <- plotly_data(p) %>% mutate(text = format(last.week.var, big.mark = ',', trim = TRUE)) %>% select(Country = state, Date = date, 'Average Cases' = last.week.var, text) %>% arrange(Date) %>% highlight_key(~Country) pal <- viridis(plotly_data(p) %>% nrow, end = .8, option = 'A') d.tmp <- d %>% plot_ly() %>% add_trace(x = ~Date, y = ~`Average Cases`, color = ~Country, type = 'scatter', mode = 'lines+markers', colors = pal, name = ~Country, customdata = '', hovertemplate = paste0('<b>%{text}</b>', '<br><i>%{x}</i>'), text = ~text ) %>% layout(legend = list(x = 0.1, y = 1), dragmode = FALSE, title = p$x$layout$title$text, xaxis = list(title = p$x$layout$xaxis$title$text), yaxis = list(title = p$x$layout$yaxis$title$text)) %>% highlight(on = 'plotly_click', off = 'plotly_doubleclick', persistent = FALSE) d.tmp
Log10 scale
Each data point is an average of new cases from the previous 7 days.
d.tmp %>% layout(yaxis = list(type = 'log'))
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