使用R进行分组统计

分组统计数据集是很常见的需求，R中也有相应的包支持数据集的分组统计。自己尝试了写了段R代码来完成分组统计数据集，支持公式，感觉用起来还算方便。代码分享在文章最后。

使用方式:

step 1: source('AggregateSummary.R')

step 2: pastecs_summary(mpg+hp+wt~am,data=mtcars)

执行结果如下：

AggregateSummary.R的源码：

library(plyr)
library(stringr)
library(pastecs)

parseformula <- function(formula = "...  ~ variable", varnames, value.var = "value") {
  remove.placeholder <- function(x) x[x != "."]
  replace.remainder <- function(x) {
    if (any(x == "...")) c(x[x != "..."], remainder) else x
  }

  if (is.formula(formula)) {
    formula <- str_c(deparse(formula, 500), collapse = "")
  }

  if (is.character(formula)) {
    dims <- str_split(formula, fixed("~"))[[1]]
    formula <- lapply(str_split(dims, "[+*]"), str_trim)

    formula <- lapply(formula, remove.placeholder)

    all_vars <- unlist(formula)
    if (any(all_vars == "...")) {
      remainder <- setdiff(varnames, c(all_vars, value.var))
      formula <- lapply(formula, replace.remainder)
    }
  }

  if (!is.list(formula)) {
    stop("Don't know how to parse", formula, call. = FALSE)
  }
  lapply(formula, as.quoted)
}

evalFormula <- function(formula,data){
  fo<-parseformula(formula)
  lapply(fo,eval.quoted,envir=data)
}

pastecs_Summary<- function(formula,data){
  tmplist<-evalFormula(formula,data)
  df1<-as.data.frame(tmplist[1])
  uni<-unique(tmplist[[2]][[1]])
  lst<-list()
  for(i in uni){
    lst[[paste(names(tmplist[[2]]),i)]]<-stat.desc(df1[which(tmplist[[2]][[1]]==i),])
  }

  return(lst)
}