标签：plot document export func 汇总 ack ase mem tran
is.na can use which, it finds specific rows, is.element can‘t, it is designed to find NA in a whole table
d[is.na(d)] <- 0 is.element(NA,temp_city$city_name)
delete certain rows
df <- df[-c(1,2),]#drop discrete rows df <- df[-c(1：2),]#drop continous rows
delete certain columns
trade_month_final <- trade_month_final[,-(2:3)] shoppingmall_amap3 <- subset(shoppingmall_amap3,select=-c(origin_name)) shoppingmall_amap2 <- shoppingmall_amap2[,-c(‘origin_name‘)] tmpdata <- data_set[ , !names(data_set) %in% c(“var1”, “var2”)]
grepl,unique and gsub
content_int<-content_int[!grepl(‘TRUE‘,content_int$store_name)] content_int<-unique(content_int,by=c(‘store_name‘)) content_int$store_name<-gsub[‘[(].*|[)].*‘,‘‘,content_int$store_name)]
build a row which has the same number of rows in the table
table_temp1$month <- month
remember, this only applies to numeric variables. When month is a data frame(like when it is calculated by aggregate function),we have to transfer it into numeric ones with as.numeric.
city_statistic$group_freq<-ave(city_statistic$freq, city_statistic$group_final_id, FUN = sum)
这样每组的每个成员的记录行都会多一列相同的值，如上述函数按id汇总求freq的和，每一个id下的分店都有一个freq之和的属性
for character(0) #rlang::is_empty()
If
if (x< 0.2){
x <- x+1
print("success!")
}else{
x < x-1
print("else success!")
}
for (k in k:length(file)){}
##‘ gettianmap
##‘
##‘ Combine Repeated function
##‘
##‘ URLencode & getURL & fromJSON & tryCatch
##‘
##‘ @param url current URL address
##‘ @param timeout_set timeout value
##‘ @return amap
##‘ @author t.s.helianthus <\url{http://helianthus-code.lofter.com}>
##‘ @examples amap <- getMapData(url = ‘http://restapi.amap.com/v3/ip?key=389880a06e3f893ea46036f030c94700‘)
##‘ @import RCurl
##‘ @import rjson
##‘ @import httr
##‘ @export
gettianmap <- function (url, timeout_set = 15) {
tianmap <- NULL;
url <- URLencode(enc2utf8(url))
connect <- ‘‘
# print(url)
msg.load <- tryCatch ({
connect <- getURL(url,httpheader=myheader,.encoding="utf-8", .opts = list(timeout = timeout_set, maxredirs = 2))
tianmap <- fromJSON(connect)
msg.load <- "TRUE"
}, error = function (e) {
"FALSE"
}
)
if (msg.load == ‘FALSE‘) {
print(‘error >> reload‘)
msg.load <- tryCatch({
tianmap <- content(GET(url,verbose(),timeout(timeout_set),add_headers(myheader)))
msg.load <- "TRUE"
}, error = function(e) {
"FALSE"
})
}
#if ( length(grep(‘too fast‘,amap)) == 1) {print(‘********too_fast********‘);print(stop_curl)}
if ( length(grep(‘too fast‘,tianmap)) == 1) {print(‘********too_fast********‘);install.packages("ggplot2")}
if (msg.load == ‘FALSE‘) {tianmap <- NULL;print(‘reload false >> NULL‘)}
return(tianmap)
}
for(i in 1:5){
if(i=3){
break;
}
print(i);
}
for(i in 1:5){
if(i=3){
next;
}
print(i);
}
ggplot2
官方文档：https://ggplot2.tidyverse.org/reference/scale_manual.html
详细柱形图：https://www.r-bloggers.com/how-to-make-a-histogram-with-ggplot2/
添加横竖线：cnblogs.com/wkslearner/p/5697471.html
R cookbook:http://www.cookbook-r.com/Graphs/
所有关于坐标轴的信息：https://blog.csdn.net/Bone_ACE/article/details/47427453
查看图像的构造 ,如颜色
g <- ggplot_build(p) unique(g$data[[1]]$color)
标签：plot document export func 汇总 ack ase mem tran
原文地址：https://www.cnblogs.com/yuxuan320/p/12527194.html
