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用emoji表情包来可视化北京市历史天气状况!

用emoji表情包来可视化北京市历史天气状况!

作者: RainDu | 来源:发表于2017-04-12 12:37 被阅读0次

    The emoji-weather visualization of beijing in 2016

    =================================================

    Use the emoji-icon to visualize weather state of beijing in 2016!

    ------------------------------------------------------

    library(RCurl)
    library(XML)
    library(dplyr)
    library(stringr)
    library(tidyr)
    library(plyr)
    library(rvest)
    library(ggimage)
    library(Cairo)
    library(showtext)
    library(lubridate)
    
    url<-"http://lishi.tianqi.com/beijing/index.html"
    myheader <-c("User-Agent"="Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36")
    webpage<-getURL(url,httpheader=myheader)
    mymonthlink<-getHTMLLinks(url,externalOnly=TRUE)%>%grep(".*?2016\\d{2}.html",.,value=T)
    

    a failure attempt:

    ####
    #page1<-getURL(mymonthlink[2],.encoding="gbk")
    #rd<-iconv(page1,"gbk","utf-8")
    #rdhtml<-htmlParse(rd,encoding="UTF-8")
    #cesh<-readHTMLList(rdhtml,trim=TRUE,elFun=xmlValue)%>%grep("\\d{4}-\\d{2}-\\d{2}",.,value=T)
    #cesh<-cesh%>%sub("([a-z])(\\()(\\\)","",.)
    #cesh<-cesh1%>%str_split(',')%>%plyr::ldply(.fun=NULL)
    #cesh$V1<-cesh$V1%>%sub("[a-z]\\(","",.)%>%as.Date()
    #names(cesh)<-c("date","high","low","state","wind","index")
    ####
    以上代码写了一半写不下去了,我有rvest为啥要用RCurl,肯定自己脑抽筋了!
    

    then i find a batter way to get the target data.

    mynewdata<-c()
    for (i in mymonthlink){
    mymonthdata<-read_html(i,encoding="gbk")%>%html_nodes("div.tqtongji2>ul")%>%html_text(trim=FALSE)%>%str_trim(.,side="right")%>%.[-1]
    mynewdata<-c(mynewdata,mymonthdata)
    }
    
    mynewdata1<-mynewdata
    mynewdata<-mynewdata1%>%gsub("\t\t\t|\t|\r\n","",.)%>%str_split('   ')%>%plyr::ldply(.fun=NULL)%>%.[,-2]
    names(mynewdata)<-c("date","high","low","state","wind","index")
    mynewdata$date<-as.Date(mynewdata$date)
    mynewdata$high<-as.numeric(mynewdata$high)
    mynewdata$low<-as.numeric(mynewdata$low)
    
    #cleanning the dirty data.
    unique(mynewdata$state)
    happy<-c("晴","阵雨~晴","多云转晴","多云~晴","雷阵雨~晴","阴~晴","霾~晴","浮尘~晴")
    depressed<-c("霾","阴","多云","晴~多云","霾~多云","晴~霾","多云~霾","阵雨转多云","多云转阴","阴~多云","多云~阴","晴~阴","阵雨~多云","小雨~多云","小雨~阴","霾~雾","小雪~阴","阴~小雪","小雨~雨夹雪")
    angry<-c("小雨","雨夹雪","小雪","雷阵雨","阵雨","中雨","小到中雨","雷阵雨~阴","多云~雷阵雨","阴~雷阵雨","霾~雷阵雨","多云~阵雨","晴~阵雨","阴~小雨","阵雨~小雨")
    Terrified<-c("中到大雨","暴雨","雷阵雨~中到大雨")
    
    #create a new factor[categorical] varibale.
    mynewdata$mode<-NULL
    mynewdata$mood<-ifelse(mynewdata$state%in% happy,"happy",ifelse(mynewdata$state%in% depressed,"depressed",ifelse(mynewdata$state%in% angry,"angry","Terrified")))
    mynewdata <- within(mynewdata,{
    mood_code <- NA
    mood_code[mood=="happy"]<-"1f604"
    mood_code[mood=="depressed"]<-"1f633"
    mood_code[mood=="angry"]<-"1f62d"
    mood_code[mood=="Terrified"]<-"1f621"
    })
    
    #tidy the time/date varibales.
    mynewdata$month<-as.numeric(as.POSIXlt(mynewdata$date)$mon+1)
    mynewdata$monthf<-factor(mynewdata$month,levels=as.character(1:12),labels=c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"),ordered=TRUE)
    mynewdata$weekday<-as.POSIXlt(mynewdata$date)$wday
    mynewdata$weekdayf<-factor(mynewdata$weekday,levels=rev(0:6),labels=rev(c("Sun","Mon","Tue","Wed","Thu","Fri","Sat")),ordered=TRUE)
    mynewdata$week <- as.numeric(format(mynewdata$date,"%W"))
    mynewdata<-ddply(mynewdata,.(monthf),transform,monthweek=1+week-min(week))
    mynewdata$day<-day(mynewdata$date)
    
    setwd("F:/数据可视化/R/R语言学习笔记/可视化/ggplot2/商务图表")
    write.table(mynewdata,"historyweather.csv",sep=",",row.names=FALSE)
    mynewdata<-read.csv("historyweather.csv",stringsAsFactors = FALSE,check.names = FALSE)
    
    #first theme:
    mytheme<-theme(
    rect=element_blank(),
    axis.ticks=element_blank(),
    text=element_text(face="plain",lineheight=0.9,hjust=0.5,vjust=0.5,size=15),
    title=element_text(face="plain",lineheight=0.9,hjust=0,vjust=0.5,size=30),
    axis.title=element_blank(),
    strip.text=element_text(size = rel(0.8)),
    plot.margin = unit(c(5,2,5,2),"lines")
    )
    

    the first photo:

    CairoPNG("emoji1.png",1000,870)
    showtext.begin()
    ggplot(mynewdata,aes(weekdayf,monthweek,fill=high))+
    geom_tile(colour='white')+
    scale_fill_gradient(low=NA, high=NA,guide=FALSE)+
    ggtitle("The emoji-weather visualization of beijing in 2016")+
    scale_y_reverse(breaks=seq(from=6,to=0,by=-1))+
    ggimage::geom_emoji(aes(image=mood_code),size=.1)+
    facet_wrap(~monthf ,nrow=3)+
    mytheme
    showtext.end()
    dev.off()


    second theme:

    mytheme2<-theme(
    rect=element_blank(),
    axis.ticks=element_blank(),
    text=element_text(face="plain",lineheight=0.9,hjust=0.5,vjust=0.5,size=15),
    title=element_text(face="plain",lineheight=0.9,hjust=0,vjust=0.5,size=30),
    axis.title=element_blank(),
    strip.text=element_text(size = rel(0.8)),
    plot.margin = unit(c(1,1,1,1),"lines")
    )
    

    second photo:

    CairoPNG("emoji2.png",1200,1200)
    showtext.begin()
    ggplot(mynewdata,aes(x=factor(day),y=monthf,fill=high))+
    geom_tile(colour='white')+
    expand_limits(y =c(-12,12))+
    scale_x_discrete(position=c("bottom"))+
    coord_polar(theta="x")+
    scale_fill_gradient(low=NA, high=NA,guide=FALSE)+
    ggimage::geom_emoji(aes(image=mood_code),size=.015)+
    geom_image(aes(x=0,y=-12),image ="weather.png", size =.15)+
    ggtitle("The emoji-weather visualization of beijing in 2016")+
    mytheme2
    showtext.end()
    dev.off()

    ​联系方式:

    ----------------------------------------------------

    wechat:ljty1991

    Mail:578708965@qq.com

    个人公众号:数据小魔方(datamofang)

    团队公众号:EasyCharts

    qq交流群:[魔方学院]553270834个人简介:

    -------------------------------------------------

    **杜雨**

    财经专业研究僧;

    伪数据可视化达人;

    文科背景的编程小白;

    喜欢研究商务图表与地理信息数据可视化,爱倒腾PowerBI、SAP DashBoard、Tableau、R ggplot2、Think-cell chart等诸如此类的数据可视化软件,创建并运营微信公众号“数据小魔方”。

    Mail:578708965@qq.com


    本作品采用知识共享署名-非商业性使用 4.0 国际许可协议进行许可。

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