In ahorawzy/Mreport: Monthly Report of traffic condition

rm(list=ls())

library(Mreport)
library(leaflet)
library(leafletCN)
library(knitr)
library(plyr)
library(reshape2)

load_base()
load_sample_base()

基本情况

所有站点一共43200个

dim(station_useful)

连续型站点7959个

table(station_useful$观测站类型)

国高近3000个，省高不到1000个，普通国省道各近7000个。

table(station_useful$行政等级)

属于国高、省高、普通国省道的连续式交掉站有7440个

y <- table(station_useful$行政等级,station_useful$观测站类型)
y <- y[c(2,3,4,5),c(3,2,1)]
y

经纬度缺失情况

43200个点中，经纬度缺失38395个，缺失率88.87%.

sum(is.na(station_useful$经度))
sum(is.na(station_useful$经度))/43200

缺失情况汇总表

x <- ddply(station_useful,c("行政等级","观测站类型"),function(x) sum(is.na(x[["经度"]])))
x <- dcast(x,x$行政等级~x$观测站类型)
names(x)[1] <- "等级"
x <- x[c(2,3,4,5),c(1,4,3,2)]
x

extractnumcol <- function(df){
  return(df[sapply(df, is.numeric)])
}

经纬度缺失比例表

z <- extractnumcol(x)/extractnumcol(y)
rownames(z) <- x$等级
round(z,3)

allstation <- read.csv("D:\\交大云同步\\实习\\00_交调系统\\交调系统数据\\交调站点管理\\交调站数据.csv",stringsAsFactors=F)
dim(allstation)

ahorawzy/Mreport documentation built on May 3, 2019, 3:40 p.m.