inst/shinyapps/v/ui.R
In thamstra/nCOV2019: Stats of the '2019-nCov' Cases
# Shiny app for showing the number of confirmed coronavirus cases across China
# Xijin Ge 2/5/2020
library(shiny)
library(plotly)
library(shinyBS,verbose=FALSE) # for popup figures
# Define server logic required to draw a histogram
ui <- fluidPage(
titlePanel(z("疫情统计和预测")),
tabsetPanel(
tabPanel(z("全国")
,h4( paste0(
z("全国确诊:"), y$chinaTotal$confirm, " (", finc(y$chinaAdd$confirm), ", ", finc( round(y$chinaAdd$confirm/(y$chinaTotal$confirm - y$chinaAdd$confirm)*100,1) ), "%)",
z(", 疑似:"), y$chinaTotal$suspect, " (", finc(y$chinaAdd$suspect), ", ", finc( round(y$chinaAdd$suspect/(y$chinaTotal$suspect - y$chinaAdd$suspect)*100,1) ), "%)",
z(", 死亡:"), y$chinaTotal$dead, " (", finc(y$chinaAdd$dead), ", ", finc( round(y$chinaAdd$dead/(y$chinaTotal$dead - y$chinaAdd$dead)*100,1) ), "%)",
z(", 痊愈:"), y$chinaTotal$heal, " (", finc(y$chinaAdd$heal), ", ", finc( round(y$chinaAdd$heal/(y$chinaTotal$heal - y$chinaAdd$heal)*100,1) ), "%)"
)
)
,h5( z("更新"), " ", z( paste0( gsub("-.*","", gsub(" .*|2020-","",y$lastUpdateTime)), "月")),
gsub(".*-","", gsub(" .*|2020-","",y$lastUpdateTime)), z("日")," ", z("北京时间"), " ", gsub(".* ","", y$lastUpdateTime),". ",
z("一天之内数字会有多次更新。") )
,fluidRow(
column(6, checkboxInput("logScale", z("所有的图对数坐标 log10"), value = FALSE) )
# ,column(2, downloadButton('dataDownload', z('下载') ) )
,column(6, align="right",a(z("英语"), href=myURL) )
)
#,plotlyOutput("historicalChinaDataPlotly")
,img(src='ChinaMapAnimated2.gif', align = "center",width="600", height="450")
,br(),br()
,plotOutput("realTimeProvinceConfirmed")
,br()
,plotlyOutput("historicalChinaData")
,br()
,plotlyOutput("historicalChinaDataAdd")
,br()
,plotOutput("confirmedByProvincesHistorical")
, br()
,plotlyOutput("deathRatesCities")
,br()
,plotlyOutput("deathRatesCitiesCountries")
,br()
) #tab1 --------------------------------------------------
,tabPanel(z("地图")
,h4(paste0( z(paste0(gsub("-.*","", gsub(" .*|2020-","",y$lastUpdateTime)), "月")),
gsub(".*-","", gsub(" .*|2020-","",y$lastUpdateTime)), z("日"), z("请稍等几秒钟，地图加载")))
,plotOutput("ChinaMap")
)
,tabPanel(z("省")
,selectInput("selectProvince0", NULL, choices = provinceNamesList)
#,tableOutput("todayTotalTable")
,plotOutput("realTimeCityConfirmed")
,br()
,plotlyOutput("provienceHistorical")
,plotlyOutput("provienceHistoricalAdd")
,plotOutput("cities_in_proviences")
,br()
#,plotlyOutput("cities_in_proviences_selected_plotly")
,plotOutput("provinceMap")
,br()
)
,tabPanel(z("市")
,fluidRow(
column(3, selectInput("selectProvince", NULL, choices = provinceNamesList) ),
column(3, selectInput("selectCity", NULL, choices = cityNames))
)
,plotlyOutput("cities_in_proviences_selected")
,plotlyOutput("cities_in_proviences_selectedAdd")
)
,tabPanel(z("世界")
,plotOutput("realTimeCityConfirmedWorld")
,br()
,plotlyOutput("historicalWorld")
,br()
,plotlyOutput("WorldDeathRate")
,br()
,plotOutput("worldMap")
)#tab2 --------------------------------------------------
,tabPanel(z("预测")
,sliderInput("daysForcasted", z("选择预测天数"),
min = 1, max = 7,
value = 10)
,h5(z("简单的算法进行的预测,程序没有认真检查，仅供参考。用了R的forecast 软件包里的exponential smoothing 和forecast函数。") )
,selectInput("selectCountry", NULL, choices = unique(contriesPrediction$country))
,plotOutput("forecastConfirmedChangeWorld")
,br(),br()
,h4(z("中国详细预测"))
,h5(z("先直接用全国的确诊总数的时间序列："))
,plotOutput("forecastConfirmedRaw")
,br()
,br()
,h5(z("把全国的确诊总数先换算成了每天比前一天增加的百分比，
去除了前面10天不稳定的数据, 再预测："))
,plotOutput("forecastConfirmedChange")
,br()
,br()
,h5(z("直接用全国的死亡累计数预测："))
,plotOutput("forecastDeadRaw")
,br()
,br()
,h5(z("把全国的死亡累计数先换算成了每天比前一天增加的百分比，去除了前面10天不稳定的数据,再预测：") )
,plotOutput("forecastDeadChange")
,br(),br()
) #tab2 --------------------------------------------------
,tabPanel(z("数据")
,br()
, downloadButton('dataDownload', z('中国数据下载') )
,br(),br()
, downloadButton('dataDownloadWorld', z('世界数据下载') )
,br()
) #tab2 --------------------------------------------------
,tabPanel("?"
,h4("不保证数据和分析的可靠性，仅供参考。", style = "color:red")
,h5("该网站是我工作之余仓促码出来的, 难免有错误。见",
a("源代码。 ", href="https://github.com/gexijin/wuhan"),
"主要目的是帮助朋友们了解疫情。纯粹个人行为。",
"bcloud.org 是以前注册的一个域名，随手拿来用了，不属于任何组织。"
)
,h5("之所以能很快写出来，最主要是因为南方医科大学的",
a("余光创教授", href="http://portal.smu.edu.cn/jcyxy/info/1084/2203.htm"),
"(微信公众号biobabble）写了一个功能强大的下载实时数据的软件包：",
a("nCov2019。", href="https://mp.weixin.qq.com/s?__biz=MzI5NjUyNzkxMg==&mid=2247488621&idx=1&sn=727f8bdec2801ddc0315b9fedaa40acc&scene=21"),
"实时数据来自腾讯API,历史数据整合自丁香园，",a("Github",href="https://github.com/canghailan/Wuhan-2019-nCoV"),"以及中国国家卫生健康委员会。")
,h5("有意见或建议可以给我发"
,a("邮件",href="mailto:xijin.ge@sdstate.edu?Subject=疫情网站" ),"。 ",
"我做生物信息学方面的研究，用计算的方法探索生命的奥秘 (",
a("研究室网页", href="http://ge-lab.org/"), ")。" )
,h5("武汉加油！ 中国加油！")
,h4("Accuracy not guaranteed. Not official data.", style = "color:red")
,h5("This website tracks the cases of the 2019-nCoV (SARS-Cov-2) coronavirus originated from Wuhan, China. Developed on Feb 5, 2020 by",a("Ge Xijin", href="https://twitter.com/StevenXGe"),
"based on the R package", a("nCov2019",href="https://github.com/GuangchuangYu/nCov2019"),
"by", a("Dr. Guangchuang Yu.", href="https://twitter.com/guangchuangyu"))
,h5("Feedbacks or suggestions please"
,a("email me",href="mailto:xijin.ge@sdstate.edu?Subject=Coronavirus website" ),".",
"I am bioinformatics researcher (",
a("lab", href="http://ge-lab.org/"), ")." )
,h5("I am not a epidemiologists, or statistician. Just got too much time on my hand")
,h5("All rights reserved.")
,h5("2/5/20 Version 0")
,h5("2/8/20 Version 0.1")
,h5("2/9/20 Version 0.2 ")
,h5("2/12/20 V 0.3 English version")
,h5("2/23/20 v. 0.4 Interactive plots.")
)
)
,tags$head(includeScript("ga.js")) # tracking usage with Google analytics
)
thamstra/nCOV2019 documentation built on April 1, 2020, 12:07 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# Shiny app for showing the number of confirmed coronavirus cases across China
# Xijin Ge 2/5/2020
library(shiny)
library(plotly)
library(shinyBS,verbose=FALSE) # for popup figures
# Define server logic required to draw a histogram
ui <- fluidPage(
titlePanel(z("疫情统计和预测")),
tabsetPanel(
tabPanel(z("全国")
,h4( paste0(
z("全国确诊:"), y$chinaTotal$confirm, " (", finc(y$chinaAdd$confirm), ", ", finc( round(y$chinaAdd$confirm/(y$chinaTotal$confirm - y$chinaAdd$confirm)*100,1) ), "%)",
z(", 疑似:"), y$chinaTotal$suspect, " (", finc(y$chinaAdd$suspect), ", ", finc( round(y$chinaAdd$suspect/(y$chinaTotal$suspect - y$chinaAdd$suspect)*100,1) ), "%)",
z(", 死亡:"), y$chinaTotal$dead, " (", finc(y$chinaAdd$dead), ", ", finc( round(y$chinaAdd$dead/(y$chinaTotal$dead - y$chinaAdd$dead)*100,1) ), "%)",
z(", 痊愈:"), y$chinaTotal$heal, " (", finc(y$chinaAdd$heal), ", ", finc( round(y$chinaAdd$heal/(y$chinaTotal$heal - y$chinaAdd$heal)*100,1) ), "%)"
)
)
,h5( z("更新"), " ", z( paste0( gsub("-.*","", gsub(" .*|2020-","",y$lastUpdateTime)), "月")),
gsub(".*-","", gsub(" .*|2020-","",y$lastUpdateTime)), z("日")," ", z("北京时间"), " ", gsub(".* ","", y$lastUpdateTime),". ",
z("一天之内数字会有多次更新。") )
,fluidRow(
column(6, checkboxInput("logScale", z("所有的图对数坐标 log10"), value = FALSE) )
# ,column(2, downloadButton('dataDownload', z('下载') ) )
,column(6, align="right",a(z("英语"), href=myURL) )
)
#,plotlyOutput("historicalChinaDataPlotly")
,img(src='ChinaMapAnimated2.gif', align = "center",width="600", height="450")
,br(),br()
,plotOutput("realTimeProvinceConfirmed")
,br()
,plotlyOutput("historicalChinaData")
,br()
,plotlyOutput("historicalChinaDataAdd")
,br()
,plotOutput("confirmedByProvincesHistorical")
, br()
,plotlyOutput("deathRatesCities")
,br()
,plotlyOutput("deathRatesCitiesCountries")
,br()
) #tab1 --------------------------------------------------
,tabPanel(z("地图")
,h4(paste0( z(paste0(gsub("-.*","", gsub(" .*|2020-","",y$lastUpdateTime)), "月")),
gsub(".*-","", gsub(" .*|2020-","",y$lastUpdateTime)), z("日"), z("请稍等几秒钟，地图加载")))
,plotOutput("ChinaMap")
)
,tabPanel(z("省")
,selectInput("selectProvince0", NULL, choices = provinceNamesList)
#,tableOutput("todayTotalTable")
,plotOutput("realTimeCityConfirmed")
,br()
,plotlyOutput("provienceHistorical")
,plotlyOutput("provienceHistoricalAdd")
,plotOutput("cities_in_proviences")
,br()
#,plotlyOutput("cities_in_proviences_selected_plotly")
,plotOutput("provinceMap")
,br()
)
,tabPanel(z("市")
,fluidRow(
column(3, selectInput("selectProvince", NULL, choices = provinceNamesList) ),
column(3, selectInput("selectCity", NULL, choices = cityNames))
)
,plotlyOutput("cities_in_proviences_selected")
,plotlyOutput("cities_in_proviences_selectedAdd")
)
,tabPanel(z("世界")
,plotOutput("realTimeCityConfirmedWorld")
,br()
,plotlyOutput("historicalWorld")
,br()
,plotlyOutput("WorldDeathRate")
,br()
,plotOutput("worldMap")
)#tab2 --------------------------------------------------
,tabPanel(z("预测")
,sliderInput("daysForcasted", z("选择预测天数"),
min = 1, max = 7,
value = 10)
,h5(z("简单的算法进行的预测,程序没有认真检查，仅供参考。用了R的forecast 软件包里的exponential smoothing 和forecast函数。") )
,selectInput("selectCountry", NULL, choices = unique(contriesPrediction$country))
,plotOutput("forecastConfirmedChangeWorld")
,br(),br()
,h4(z("中国详细预测"))
,h5(z("先直接用全国的确诊总数的时间序列："))
,plotOutput("forecastConfirmedRaw")
,br()
,br()
,h5(z("把全国的确诊总数先换算成了每天比前一天增加的百分比，
去除了前面10天不稳定的数据, 再预测："))
,plotOutput("forecastConfirmedChange")
,br()
,br()
,h5(z("直接用全国的死亡累计数预测："))
,plotOutput("forecastDeadRaw")
,br()
,br()
,h5(z("把全国的死亡累计数先换算成了每天比前一天增加的百分比，去除了前面10天不稳定的数据,再预测：") )
,plotOutput("forecastDeadChange")
,br(),br()
) #tab2 --------------------------------------------------
,tabPanel(z("数据")
,br()
, downloadButton('dataDownload', z('中国数据下载') )
,br(),br()
, downloadButton('dataDownloadWorld', z('世界数据下载') )
,br()
) #tab2 --------------------------------------------------
,tabPanel("?"
,h4("不保证数据和分析的可靠性，仅供参考。", style = "color:red")
,h5("该网站是我工作之余仓促码出来的, 难免有错误。见",
a("源代码。 ", href="https://github.com/gexijin/wuhan"),
"主要目的是帮助朋友们了解疫情。纯粹个人行为。",
"bcloud.org 是以前注册的一个域名，随手拿来用了，不属于任何组织。"
)
,h5("之所以能很快写出来，最主要是因为南方医科大学的",
a("余光创教授", href="http://portal.smu.edu.cn/jcyxy/info/1084/2203.htm"),
"(微信公众号biobabble）写了一个功能强大的下载实时数据的软件包：",
a("nCov2019。", href="https://mp.weixin.qq.com/s?__biz=MzI5NjUyNzkxMg==&mid=2247488621&idx=1&sn=727f8bdec2801ddc0315b9fedaa40acc&scene=21"),
"实时数据来自腾讯API,历史数据整合自丁香园，",a("Github",href="https://github.com/canghailan/Wuhan-2019-nCoV"),"以及中国国家卫生健康委员会。")
,h5("有意见或建议可以给我发"
,a("邮件",href="mailto:xijin.ge@sdstate.edu?Subject=疫情网站" ),"。 ",
"我做生物信息学方面的研究，用计算的方法探索生命的奥秘 (",
a("研究室网页", href="http://ge-lab.org/"), ")。" )
,h5("武汉加油！ 中国加油！")
,h4("Accuracy not guaranteed. Not official data.", style = "color:red")
,h5("This website tracks the cases of the 2019-nCoV (SARS-Cov-2) coronavirus originated from Wuhan, China. Developed on Feb 5, 2020 by",a("Ge Xijin", href="https://twitter.com/StevenXGe"),
"based on the R package", a("nCov2019",href="https://github.com/GuangchuangYu/nCov2019"),
"by", a("Dr. Guangchuang Yu.", href="https://twitter.com/guangchuangyu"))
,h5("Feedbacks or suggestions please"
,a("email me",href="mailto:xijin.ge@sdstate.edu?Subject=Coronavirus website" ),".",
"I am bioinformatics researcher (",
a("lab", href="http://ge-lab.org/"), ")." )
,h5("I am not a epidemiologists, or statistician. Just got too much time on my hand")
,h5("All rights reserved.")
,h5("2/5/20 Version 0")
,h5("2/8/20 Version 0.1")
,h5("2/9/20 Version 0.2 ")
,h5("2/12/20 V 0.3 English version")
,h5("2/23/20 v. 0.4 Interactive plots.")
)
)
,tags$head(includeScript("ga.js")) # tracking usage with Google analytics
)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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