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Flourish可视化Covid-19

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偶尔在查阅资料的时候发现一种动态排名条形图（bar chart race），最初应该是在别人展示各国GDP的时候见过，我查了下，其是用Flourish完成的，我正好用其来可视化Covid-19全球疫情数据

数据来源跟这篇博文一样，是github上实时更新的数据，读取简便（不用爬虫），下面以确诊数据为例

library(dplyr)
library(countrycode)
library(tidyr)

data <- data.table::fread(url_comfirmed_global) %>%
  rename(Province_State = `Province/State`, Country_Region = `Country/Region`) %>%
  group_by(Country_Region) %>%
  summarise_at((5 - 1):(ncol(.) - 1), sum)

并通过转化生成一个每日新增确诊人数数据集

data_newcase <- plyr::ddply(data, "Country_Region", function(x) {
  diff(c(0, as.numeric(x[2:ncol(x)])))
})
names(data_newcase)[2:ncol(data_newcase)] <- colnames(data)[2:ncol(data)]

我取前20个最多确诊的国家，减少数据量

top20_country <- data %>%
  mutate(Total = .[[ncol(.)]]) %>%
  arrange(desc(Total)) %>%
  head(15) %>%
  .$Country_Region

以下我输出两个文件，Covid19-comfirmed.txt代表每日确诊总人数，Covid19-comfirmed_and_newcase.txt代表每日确诊新增人数；并且为了可视化美观，通过https://www.countryflags.io/#body增加了各国国旗logo

#-------------------------------------------------
# Total comfirmed number of top20 countries
country_comfirmed_df <- data %>%
  filter(Country_Region %in% top20_country) %>%
  mutate(Code = countrycode(Country_Region, origin = "country.name", destination = "iso2c"),
         URL = paste0("https://www.countryflags.io/", tolower(Code), "/flat/64.png")) %>%
  select(c(1, ncol(.)-1, ncol(.), 2:(ncol(.)-2)))

write.table(country_comfirmed_df, file = "../Desktop/Covid19-comfirmed.txt", sep = "\t", col.names = T, row.names = F, quote = F)


#------------------------------------------------
# Total newcase and comfirmed number of top20 countries

data_comfirmed_newcase <- left_join(gather(data, "year", "comfirm", colnames(data)[2:ncol(data)]), 
                                    gather(data_newcase, "year", "newcase", colnames(data_newcase)[2:ncol(data_newcase)])) %>%
  filter(Country_Region %in% top20_country) %>%
  mutate(Code = countrycode(Country_Region, origin = "country.name", destination = "iso2c"),
         URL = paste0("https://www.countryflags.io/", tolower(Code), "/flat/64.png"))

write.table(data_comfirmed_newcase, file = "../Desktop/Covid19-comfirmed_and_newcase.txt", sep = "\t", col.names = T, row.names = F, quote = F)

Flourish操作很简单，网页工具，有很友好的引导机制，跟着示例数据操作一遍即可上手，比如我以每日确诊总人数作为数据源，导入到Bar chart race工具中即可生成我们所想要的动态排名条形图，可点击链接查看：https://public.flourish.studio/visualisation/2149838/

接着我们可以试下导入Line chart race工具中，生成线条型的动态排名变化图，可点击链接查看：https://public.flourish.studio/visualisation/2298572/

最后我们用Flourish的Bubble chart来生成一个常见的气泡图，数据则用每日新增确诊人数作为纵坐标，每日确诊总人数为横坐标，可点击链接查看：https://public.flourish.studio/visualisation/2151764/

Covid-19BubbleChart

Flourish是一个蛮好用的工具，复杂的功能需要收费哈

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