这是我的。它不会帮助你着色，但我从ESS和Emacs…

options("width"=160)                # wide display with multiple monitors
options("digits.secs"=3)            # show sub-second time stamps

r <- getOption("repos")             # hard code the US repo for CRAN
r["CRAN"] <- "http://cran.us.r-project.org"
options(repos = r)
rm(r)

## put something this is your .Rprofile to customize the defaults
setHook(packageEvent("grDevices", "onLoad"),
        function(...) grDevices::X11.options(width=8, height=8, 
                                             xpos=0, pointsize=10, 
                                             #type="nbcairo"))  # Cairo device
                                             #type="cairo"))    # other Cairo dev
                                             type="xlib"))      # old default

## from the AER book by Zeileis and Kleiber
options(prompt="R> ", digits=4, show.signif.stars=FALSE)


options("pdfviewer"="okular")         # on Linux, use okular as the pdf viewer

setwd("C://path//to//my//prefered//working//directory")
library("ggplot2")
library("RMySQL")
library("foreign")
answer <- readline("What database would you like to connect to? ")
con <- dbConnect(MySQL(),user="root",password="mypass", dbname=answer)

我用mysql数据库做了很多工作，所以马上连接是天赐良机。我只希望有一种方法可以列出可用的数据库，这样我就不必记住所有不同的名称。

sink(file = 'R.log', split=T)

options(scipen=5)

.ls.objects <- function (pos = 1, pattern, order.by = "Size", decreasing=TRUE, head =     TRUE, n = 10) {
  # based on postings by Petr Pikal and David Hinds to the r-help list in 2004
  # modified by: Dirk Eddelbuettel (http://stackoverflow.com/questions/1358003/tricks-to-    manage-the-available-memory-in-an-r-session) 
  # I then gave it a few tweaks (show size as megabytes and use defaults that I like)
  # a data frame of the objects and their associated storage needs.
  napply <- function(names, fn) sapply(names, function(x)
          fn(get(x, pos = pos)))
  names <- ls(pos = pos, pattern = pattern)
  obj.class <- napply(names, function(x) as.character(class(x))[1])
  obj.mode <- napply(names, mode)
  obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class)
  obj.size <- napply(names, object.size) / 10^6 # megabytes
  obj.dim <- t(napply(names, function(x)
            as.numeric(dim(x))[1:2]))
  vec <- is.na(obj.dim)[, 1] & (obj.type != "function")
  obj.dim[vec, 1] <- napply(names, length)[vec]
  out <- data.frame(obj.type, obj.size, obj.dim)
  names(out) <- c("Type", "Size", "Rows", "Columns")
  out <- out[order(out[[order.by]], decreasing=decreasing), ]
  if (head)
    out <- head(out, n)
  out
}

我有这个，更动态的技巧来使用全终端宽度，它试图从COLUMNS环境变量中读取(在Linux上):

tryCatch(
  {options(
      width = as.integer(Sys.getenv("COLUMNS")))},
  error = function(err) {
    write("Can't get your terminal width. Put ``export COLUMNS'' in your \
           .bashrc. Or something. Setting width to 120 chars",
           stderr());
    options(width=120)}
)

这样，即使您调整终端窗口的大小，R也将使用全宽度。

我发现两个函数是非常必要的:首先，当我在几个函数上设置debug()并且我已经解决了错误，所以我想要undebug()所有函数-而不是一个接一个。在这里添加的undebug_all()函数作为接受的答案是最好的。

其次，当我定义了许多函数并正在寻找一个特定的变量名时，很难在ls()的所有结果中找到它，包括函数名。这里发布的lsnofun()函数真的很好。

Stephen Turner关于. rprofiles的帖子有几个有用的别名和启动函数。

我发现自己经常使用他的“ht”和“hh”。

#ht==headtail, i.e., show the first and last 10 items of an object
ht <- function(d) rbind(head(d,10),tail(d,10))

# Show the first 5 rows and first 5 columns of a data frame or matrix
hh <- function(d) d[1:5,1:5]