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一篇关于国旗与奥运会奖牌的可视化笔记

一篇关于国旗与奥运会奖牌的可视化笔记

作者: taoyan | 来源:发表于2017-09-12 12:22 被阅读73次

    简介

    本文主要介绍一个R包ggflags,可以用于绘制国旗。安装的话从Github上利用包devtools安装。

    devtools::install_github("baptiste/ggflags")
    

    下面看个小例子来介绍一下

    数据集

    library(ggflags)#load package
    set.seed(1111)
    #create the dataset
    data <- data.frame(x=rnorm(50), y=rnorm(50),
                       country=sample(c("ar", "us", "cn", "fr", "gb", "es"), 50 ,replace = TRUE),
                       stringsAsFactors=FALSE)
    head(data)
        x                y       country
    -0.0865801  -0.7055274  gb
    1.3225244   -0.5910791  fr
    0.6397020   -0.2796410  us
    1.1747866   -1.3209782  cn
    0.1162903   0.5851085   gb
    -2.9308464  0.0198323   ar
    

    绘图

    library(ggplot2)
    ggplot(data, aes(x=x, y=y, country=country, size=x))+
      geom_flag()+
      scale_country()+
      scale_size(range = c(0, 10))
    

    国旗的图片是来自于EmojiOne数据集,有兴趣的可以去看看了解一下。
    题目有奥运会奖牌,所以接下来就可视化一下索契冬奥运会各国奖牌,本次用国旗与国家联系起来。

    爬取数据

    library(dplyr)
    library(rvest)
    url <- "http://www.nbcolympics.com/medals"
    medals <- read_html(url)%>%
      html_nodes("table")%>%
      .[[1]]%>%
      html_table()
    knitr::kable(head(medals))
    
    Country       Gold  Silver  Bronze  Total
    Russia         13   11  9   33
    United States   9   7   12  28
    Norway         11   5   10  26
    Canada         10   10  5   25
    Netherlands 8   7   9   24
    Germany         8   6   5   19
    

    爬取完数据之后进行清洗

    数据清洗

    本文重要的一环是将国家与国旗联系起来,因此首先要将国家名缩写弄出来,这就要用到countrycode这个包了。

    #install the package
    install.packages("countrycode")
    

    数据清洗

    library(countrycode)
    library(tidyr)
    medals <- medals%>%
      mutate(code=countrycode(Country, "country.name", "iso2c"))%>%
      mutate(code=tolower(code))%>%
      gather(medal_color, count, Gold, Silver, Bronze)%>%
      mutate(medal_color=factor(medal_color, levels = c("Gold", "Silver", "Bronze")))%>%
      drop_na(Country, code)
    knitr::kable(head(medals))
    
    Country       Total code    medal_color count
    Russia         33    ru    Gold       13
    United States  28    us    Gold        9
    Norway         26    no    Gold       11
    Canada         25    ca    Gold       10
    Netherlands    24    nl    Gold        8
    Germany        19    de    Gold        8
    

    绘图

    由于国家数量太多,并且好多国家奖牌数基本为零,因此我们筛选一下:只绘制总奖牌数不小于5的国家。

    medals%>%filter(Total>=5)%>%
      ggplot(aes(x=reorder(Country, Total), y=count))+
      geom_bar(stat = "identity", aes(fill=medal_color))+
      geom_flag(aes(y=-2,country=code), size=10)+
      theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 7, vjust = 0.5))+
      scale_fill_manual(values = c(
        "Gold"="gold",
        "Bronze" = "#cd7f32",
        "Silver" = "#C0C0C0"
      ))+
      scale_y_continuous(expand = c(0.1, 1))+
      xlab("Country")+
      ylab("Number of medals")+
      theme_bw()+
      theme(panel.grid = element_blank())+
      theme(legend.justification = c(1, 0), legend.position = c(1, 0))+
      theme(legend.title = element_blank())+
      coord_flip()
    

    SessionInfo

    sessionInfo()
    ## R version 3.4.1 (2017-06-30)
    ## Platform: x86_64-pc-linux-gnu (64-bit)
    ## Running under: Ubuntu 16.04.3 LTS
    ## 
    ## Matrix products: default
    ## BLAS: /usr/lib/atlas-base/atlas/libblas.so.3.0
    ## LAPACK: /usr/lib/atlas-base/atlas/liblapack.so.3.0
    ## 
    ## locale:
    ##  [1] LC_CTYPE=zh_CN.UTF-8       LC_NUMERIC=C              
    ##  [3] LC_TIME=zh_CN.UTF-8        LC_COLLATE=zh_CN.UTF-8    
    ##  [5] LC_MONETARY=zh_CN.UTF-8    LC_MESSAGES=zh_CN.UTF-8   
    ##  [7] LC_PAPER=zh_CN.UTF-8       LC_NAME=C                 
    ##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
    ## [11] LC_MEASUREMENT=zh_CN.UTF-8 LC_IDENTIFICATION=C       
    ## 
    ## attached base packages:
    ## [1] stats     graphics  grDevices utils     datasets  methods   base     
    ## 
    ## other attached packages:
    ## [1] bindrcpp_0.2     tidyr_0.7.1      countrycode_0.19 rvest_0.3.2     
    ## [5] xml2_1.1.1       dplyr_0.7.3      ggflags_0.0.1    ggplot2_2.2.1   
    ## 
    ## loaded via a namespace (and not attached):
    ##  [1] Rcpp_0.12.12     compiler_3.4.1   plyr_1.8.4       highr_0.6       
    ##  [5] bindr_0.1        tools_3.4.1      digest_0.6.12    evaluate_0.10.1 
    ##  [9] tibble_1.3.4     gtable_0.2.0     pkgconfig_2.0.1  rlang_0.1.2     
    ## [13] curl_2.8.1       yaml_2.1.14      stringr_1.2.0    httr_1.3.1      
    ## [17] knitr_1.17       tidyselect_0.2.0 rprojroot_1.2    grid_3.4.1      
    ## [21] glue_1.1.1       R6_2.2.2         XML_3.98-1.9     rmarkdown_1.6   
    ## [25] purrr_0.2.3      selectr_0.3-1    magrittr_1.5     backports_1.1.0 
    ## [29] scales_0.5.0     htmltools_0.3.6  assertthat_0.2.0 colorspace_1.3-2
    ## [33] labeling_0.3     stringi_1.1.5    lazyeval_0.2.0   munsell_0.4.3
    

    联系方式:

    wechat: yt056410
    Email: tyan@zju.edu.cn
    QQ: 1051927088
    GitHub: https://github.com/YTLogos
    简书: http://www.jianshu.com/u/bd001545cf0b
    博客: https://ytlogos.github.io/

    个人简介:

    严涛
    浙江大学作物遗传育种在读研究生(生物信息学方向)
    伪码农,R语言爱好者,爱开源

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