knitr::opts_chunk$set(echo = F,message = F,warning = F)
options(stringsAsFactors = F) options(digits = 3) rm(list = ls()) source("D:\\R\\packages\\Mreport\\scripts\\caculate.R", encoding = "utf-8") source("D:\\R\\packages\\Mreport\\scripts\\select.R", encoding = "utf-8")
library(Mreport) library(plyr) library(ggplot2) library(reshape2) library(knitr) library(leaflet) library(leafletCN)
load_base() load_sample_base()
jdnew <- read.csv("D:\\data\\sx_raw\\交调数据\\jd2018_07_2.csv") jdlast <- read.csv("D:\\data\\sx_raw\\交调数据\\jd2018_06_new.csv") jdprevious <- read.csv("D:\\data\\sx_raw\\交调数据\\jd2017_07_2.csv")
jdnews <- handle_gather(jdnew) jdlasts <- handle_gather(jdlast) jdpreviouss <- handle_gather(jdprevious) usefulstation <- intersect(jdnews$index,jdlasts$index) jdnews <- jdnews[jdnews$index %in% usefulstation,] jdlasts <- jdlasts[jdlasts$index %in% usefulstation,] jdpreviouss <- jdpreviouss[jdpreviouss$index %in% usefulstation,]
x <- table(jdnews$province,jdnews$vertical10) write.csv(x,file="D:\\交大云同步\\实习\\15_通道站点统计\\十纵通道.csv")
x <- table(jdnews$province,jdnews$horizon10) write.csv(x,file="D:\\交大云同步\\实习\\15_通道站点统计\\十横通道.csv")
y <- handle_mergeplot(sample_base$vertical10,station_plot) geo_pointplot(y,na.rm = T,type=T)
y <- handle_mergeplot(sample_base$horizon10,station_plot) geo_pointplot(y,na.rm = T,type=T)
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