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swsoyee/test_anther_cluster.R

Created April 4, 2020 05:06
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  1. swsoyee created this gist Apr 4, 2020.
    33 changes: 33 additions & 0 deletions test_anther_cluster.R
    View file
    Original file line number Diff line number Diff line change
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    signateDetail<- fread(paste0(DATA_PATH, 'SIGNATE COVID-2019 Dataset - 罹患者.csv'), header = T)
    signateDetail$公表日 <- as.Date(signateDetail$公表日)
    signateDetail[, 受診都道府県 := gsub('県', '', 受診都道府県)]
    signateDetail[, 受診都道府県 := gsub('府', '', 受診都道府県)]
    signateDetail[, 受診都道府県 := gsub('東京都', '東京', 受診都道府県)]
    signateDetail[, regionId := paste0(都道府県コード, '-', 都道府県別罹患者No)]

    oldYear <- c('0 - 9', '10 - 19', '20 - 29', '30 - 39', '40 - 49', '50 - 59', '60 - 69', '70 - 79', '80 - 89', '-90', '非公表', '', NA)
    newYear <- c(10, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 100, 100)
    names(oldYear) <- newYear
    for (i in oldYear) {
    signateDetail[年代 == i, 年代 := names(oldYear[i == oldYear][1])]
    }
    signateDetail$ageSize <- as.numeric(signateDetail$年代)

    signateDetail <- signateDetail[order(公表日, 性別, 都道府県別罹患者No)]
    dt <- signateDetail[受診都道府県 == '東京']
    dt <- dt[, rank := order(性別), by = 公表日]
    tmp <- dt[, .(公表日, 性別, 都道府県別罹患者No, rank)]

    dt %>%
    group_by(性別) %>%
    e_chart(公表日) %>%
    e_scatter(
    rank,
    ageSize, scale = log1p, symbol_size = 3) %>%
    e_tooltip() %>%
    e_grid(left = '5%', right = '5%', top = '5%', bottom = '15%') %>%
    e_y_axis(show = F) %>%
    e_x_axis(splitLine = list(show = F)) %>%
    e_toolbox_feature(feature = 'dataZoom') %>%
    e_datazoom(x_index = 0) %>%
    e_datazoom(y_index = 0)