knitr::opts_chunk$set(echo = F,message = F,warning = F)
options(stringsAsFactors = F) options(digits = 3) rm(list = ls()) source("D:\\R\\packages\\Mreport\\scripts\\caculate.R", encoding = "utf-8") source("D:\\R\\packages\\Mreport\\scripts\\select.R", encoding = "utf-8")
library(Mreport) library(plyr) library(ggplot2) library(reshape2) library(knitr) library(leaflet) library(leafletCN)
load_base() load_sample_base()
jdnew <- read.csv("D:\\data\\sx_raw\\交调数据\\jd201809.csv") jdlast <- read.csv("D:\\data\\sx_raw\\交调数据\\jd201808.csv") jdprevious <- read.csv("D:\\data\\sx_raw\\交调数据\\jd201709.csv")
jdnews <- handle_gather(jdnew) jdlasts <- handle_gather(jdlast) jdpreviouss <- handle_gather(jdprevious) usefulstation <- intersect(jdnews$index,jdlasts$index) jdnews <- jdnews[jdnews$index %in% usefulstation,] jdlasts <- jdlasts[jdlasts$index %in% usefulstation,] jdpreviouss <- jdpreviouss[jdpreviouss$index %in% usefulstation,]
z <- result_present(jdnews,jdpreviouss,jdlasts,"level","cars") names(z) <- c("道路等级","本月","同比","环比") f <- factor(c("国家高速","普通国道","省级高速","普通省道"),ordered=T) z <- z[order(f),] kable(z)
z <- result_present(jdnews,jdpreviouss,jdlasts,"level","passcars") names(z) <- c("道路等级","本月","同比","环比") f <- factor(c("国家高速","普通国道","省级高速","普通省道"),ordered=T) z <- z[order(f),] kable(z)
z <- result_present(jdnews,jdpreviouss,jdlasts,"level","frecars") names(z) <- c("道路等级","本月","同比","环比") f <- factor(c("国家高速","普通国道","省级高速","普通省道"),ordered=T) z <- z[order(f),] kable(z)
t <- result_present(jdnews,jdpreviouss,jdlasts,"horizon10","cars") names(t) <- c("十横通道","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"horizon10","passcars") names(t) <- c("十横通道","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"horizon10","frecars") names(t) <- c("十横通道","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"vertical10","cars") names(t) <- c("十横通道","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"vertical10","passcars") names(t) <- c("十横通道","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"vertical10","frecars") names(t) <- c("十横通道","月平均日交通量","同比","环比") kable(t)
t <- typicalroute_horizon(jdnews,jdpreviouss,"上海-瑞丽") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- typicalroute_horizon(jdnews,jdpreviouss,"连云港-霍尔果斯") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- typicalroute_horizon(jdnews,jdpreviouss,"上海-樟木") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- typicalroute_horizon(jdnews,jdpreviouss,"天津-红其拉甫") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- typicalroute_vertical(jdnews,jdpreviouss,"北京-上海") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- typicalroute_vertical(jdnews,jdpreviouss,"同江-三亚") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- typicalroute_vertical(jdnews,jdpreviouss,"黑河-港澳台") names(t) <- c("省份","月平均日交通量","同比") t %>% kable()
t <- result_present(jdnews,jdpreviouss,jdlasts,"portroad","frecars") t$portroad <- substr(t$portroad,1,nchar(t$portroad)-1) t <- t[order(t$now,decreasing = T),] rownames(t) <- NULL names(t) <- c("港口","日均交通量","同比","环比") kable(t)
t <- merge(station_plot,sample_base$portroad,by.x = "popup",by.y = "index",all.y = T) p <- jdnews[,c(1,10,11,12)] tt <- merge(t,p,by.x = "popup",by.y="index") tt <- tt[,-c(1,2)] names(tt)[3] <- "label" tt <- tt[,c(1,2,3,6)] tt <- aggregate(tt,by=list(tt$label),FUN=mean) tt$label <- tt$Group.1
leaflet(tt) %>% addProviderTiles("CartoDB.PositronNoLabels") %>% addCircles(label = ~label,lng = ~lng,lat = ~lat, radius = ~cars/3,stroke = F, fillOpacity = 1, fillColor ="red", labelOptions = labelOptions(noHide = T,draggable=T,textsize=25))
t <- result_present(jdnews,jdpreviouss,jdlasts,"airport","cars") t <- t[order(t$now,decreasing = T),] names(t) <- c("机场","日均交通量","同比","环比") rownames(t) <- NULL kable(t)
t <- merge(station_plot,sample_base$airport,by.x = "popup",by.y = "index",all.y = T) p <- jdnews[,c(1,10,11,12)] tt <- merge(t,p,by.x = "popup",by.y="index") tt <- tt[,-2] names(tt)[4] <- "label" leaflet(tt) %>% addTiles() %>% addCircles(label = ~label,lng = ~lng,lat = ~lat,popup = ~popup, radius = ~cars/5,stroke = F, fillOpacity = 1, fillColor ="red")
t <- result_present(jdnews,jdpreviouss,jdlasts,"citygroup2","cars") names(t) <- c("城市群","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"citygroup2","passcars") names(t) <- c("城市群","月平均日交通量","同比","环比") kable(t)
t <- result_present(jdnews,jdpreviouss,jdlasts,"citygroup2","frecars") names(t) <- c("城市群","月平均日交通量","同比","环比") kable(t)
caculate_carsmean(jdnews,"province") %>% geojsonMap(mapName = "China",palette = "Reds",legendTitle = "交通量图例")
t <- result_present(jdnews,jdpreviouss,jdlasts,"province","cars") names(t) <- c("省级行政区","月平均日交通量","同比","环比") t$省级行政区 <- factor(t$省级行政区,ordered=T,levels = province_level) t <- t[order(t$省级行政区),] rownames(t) <- NULL kable(t)
caculate_carsmean(jdnews,"province") %>% gg_boxplot(xangle = 90,xlabname = "省级行政区", ylabname="月平均日机动车交通量") ggsave(filename = "D:\\交大云同步\\实习\\06_月度分析报告\\9月分析\\绘图\\省级机动车.jpg",dpi=600)
provincenewcars <- caculate_level_carsmean(jdnews,"province") provincenewcars$province <- factor(provincenewcars$province,ordered=T,levels = province_level) provincenewcars <- provincenewcars[order(provincenewcars$province),c("province","国家高速","普通国道","省级高速","普通省道")] rownames(provincenewcars) <- NULL kable(provincenewcars)
provincepreviouscars <- caculate_level_carsmean(jdpreviouss,"province") provincepreviouscars <- provincepreviouscars[,c("province","国家高速","普通国道","省级高速","普通省道")] t <- caculate_increaseratio(provincenewcars,provincepreviouscars) t$province <- factor(t$province,ordered=T,levels = province_level) t <- t[order(t$province),] rownames(t) <- NULL kable(t)
provincelastcars <- caculate_level_carsmean(jdlasts,"province") provincelastcars <- provincelastcars[,c("province","国家高速","普通国道","省级高速","普通省道")] t <- caculate_increaseratio(provincenewcars,provincelastcars) t$province <- factor(t$province,ordered=T,levels = province_level) t <- t[order(t$province),] rownames(t) <- NULL kable(t)
caculate_passcarsmean(jdnews,"province") %>% geojsonMap(mapName = "China",palette = "Reds",legendTitle = "交通量图例")
t <- result_present(jdnews,jdpreviouss,jdlasts,"province","passcars") names(t) <- c("省级行政区","月平均日交通量","同比","环比") t$省级行政区 <- factor(t$省级行政区,ordered=T,levels = province_level) t <- t[order(t$省级行政区),] rownames(t) <- NULL kable(t)
caculate_frecarsmean(jdnews,"province") %>% geojsonMap(mapName = "China",palette = "Reds",legendTitle = "交通量图例")
t <- result_present(jdnews,jdpreviouss,jdlasts,"province","frecars") names(t) <- c("省级行政区","月平均日交通量","同比","环比") t$省级行政区 <- factor(t$省级行政区,ordered=T,levels = province_level) t <- t[order(t$省级行政区),] rownames(t) <- NULL kable(t)
本月,上月,去年同月交调站数量分别为:
nrow(jdnews) nrow(jdlasts) nrow(jdpreviouss)
t <- data_use(jdnews)[[1]] rownames(t)[32] <- c("合计") t <- t[,c("国家高速","普通国道","省级高速","普通省道")] kable(t)
分道路等级分别占比
p <- data_use(jdnews)[[2]] kable(p)
东中西部数量合计
t$合计 <- rowSums(t) t$省份 <- rownames(t) t2 <- merge(t,province_region,by="省份") tapply(t2$合计, t2$地域, sum)
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