Andrew MacDonald aammd

Is there an easy way to convert a named list into a dataframe, preserving the elements of the list in a "list-column"?

    library(dplyr)
    library(magrittr)

    ## make a random matrix
    rand_mat <- function() {

Apparently, there is a simple problem called Fizz buzz which is sometimes used to identify competent programmers. A good opportunity to practice some dplyr and magrittr tricks.

library(dplyr)
library(magrittr)
library(knitr)

1:100 %>%
 data.frame %&gt;%

Simple data manipulations in R

Many years ago, I was introduced to R by Cam Webb . At the time, his website contained a list of common data manipulations (original here). This list dated from Cam's early experience with R, and contained the R-help mailing list responses to a series of data manipulations. For a long time, I kept this file as a handy reference. I printed it out. I recommended it to friends.

Now I have been using R for years, and the state of the art has advanced considerably. Particulary, Hadley Wickham's reshape2 and dplyr packages have transformed the way most useRs manipulate their data. I decided that it would be interesting to revisit my favourite resource and try my hand at solving these problems with tools from these two packages.

library(reshape2)
library(dplyr)

x1 <- rnorm(100,5,sd=2)
x2 <- rnorm(200,15,3)
x3 <- c(x1,x2)

## calculate the density function 
den_x <- density(x3)]
## this can be plotted:
plot(den_x)

	## a demonstration of ordered contrasts

	## three levels, A, B, and C
	factor1 <- rep(LETTERS[1:3],c(15,15,15))

	## Another factor
	factor2 <- rep(letters[1:3],15)

	## check combinations
	table(factor1,factor2)

	## make a fake data frame
	test <- data.frame(foo=gl(n=3,k=2,labels=c("low","med","high")),bar=rep(letters[1:2],3),zoop=runif(6))

	## these are all factors
	str(test)

	## I want them to be characters, not factors, but I am too lazy to run as.character on every categorical factor

	library(plyr)
	test_char <- catcolwise(as.character)(test)

	library(lme4)
	library(ggplot2)

	#create some levels
	levs <- as.factor(c("l1","l2","l3","l4","l5"))

	#set the factor means
	f_means <- c(6,16,2,10,13)

	# set individual as a factor

	## file-scan.r
	## Function to find a pattern in files with user-defined extension (.r by default)
	## Returns file name and approximate row matches if positive.
	## -------------------------------------------------------
	## Author: Laura Tremblay-Boyer ([email protected])
	## Written on: March 26, 2013
	## Time-stamp: <2013-03-26 16:19:28 Laura>

	file.scan <- function(pattern, dir=getwd(), fpattern=NA, ftype=".r") {

	eps <- function(file, onefile=FALSE, width=5.5, height = 5.5, horizontal=FALSE,paper="special", ...){
	postscript(file=file,width=width,height=height,onefile=onefile,horizontal=horizontal,paper=paper,title=file,...)
	par(bty='l')
	}

	getmatch <<- function(x,str2match,...) {
	unlist(regmatches(x,regexpr(str2match,x,...))) }