jbryer

#' Parse a codebook file with variable and level information.
#' 
#' Parses a codebook file where lines starting at column zero (far left) represet
#' variable information (e.g. name, description, type) and indented lines 
#' (i.e. lines beginning with white space, either tabs or spaces, etc.) represent factor
#' levels and labels. 
#' 
#' Note that white space at the beginning and end of each line is stripped before
#' processing that line.
#' 

dsparks

doInstall <- TRUE
toInstall <- c("ggplot2", "poLCA", "reshape2")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

ANES <- read.csv("http://www.oberlin.edu/faculty/cdesante/assets/downloads/ANES.csv")
ANES <- ANES[ANES$year == 2008, -c(1, 11, 17)]  # Limit to just 2008 respondents,
head(ANES)  # remove some non-helpful variables
# Adjust so that 1 is the minimum value for each variable:
ANES <- data.frame(apply(ANES, 2, function(cc){  cc - min(cc, na.rm = T) + 1  }))

dsparks

SmoothCoefficientPlot <- function(models, modelnames = "", removeintercept = FALSE){
  # models must be a list()

  Alphas <- seq(1, 99, 2) / 100

  Multiplier <- qnorm(1 - Alphas / 2)
  zzTransparency <<- 1/(length(Multiplier)/4)
  CoefficientTables <- lapply(models, function(x){summary(x)$coef})
  TableRows <- unlist(lapply(CoefficientTables, nrow))

dsparks

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("sna", "ggplot2", "Hmisc", "reshape2")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Empty ggplot2 theme
new_theme_empty <- theme_bw()
new_theme_empty$line <- element_blank()
new_theme_empty$rect <- element_blank()
new_theme_empty$strip.text <- element_blank()

ikashnitsky

#===============================================================================
# 2019-07-19-- ikashnitsky.github.io
# Reproduce Figure 2 from http://doi.org/10.1007/s10708-018-9953-5
# Ilya Kashnitsky, ilya.kashnitsky@gmail.com
#===============================================================================

library(tidyverse)
library(hrbrthemes); import_roboto_condensed()

# the data as tribble

tonyfischetti

#!/usr/bin/Rscript --vanilla

###########################################################
##                                                       ##
##   elastic.R                                           ##
##                                                       ##
##                Author: Tony Fischetti                 ##
##                        tony.fischetti@gmail.com       ##
##                                                       ##
###########################################################

jeroen

library(magrittr)
library(magick)
image_read("logo:") %>%
  image_convert('png', colorspace = 'gray') %>%
  image_edge(radius = 1) %>%
  image_negate() %>%
  image_transparent('white', 10000) %>%
  image_background("white") %>%
  image_browse()

dsparks

# Sunlight Foundation style guide: http://design.sunlightlabs.com/projects/Sunlight-StyleGuide-DataViz.pdf
# Ram's original Wes Anderson code: https://github.com/karthik/wesanderson/blob/master/R/colors.R

#' A Wes Anderson palette generator
#'
#' These are a handful of color palettes from Wes Anderson movies. 
#' @param n Number of colors desired. Unfortunately most palettes now only have 4 or 5 colors. But hopefully we'll add more palettes soon. All color schemes are derived from the most excellent Tumblr blog: \href{http://wesandersonpalettes.tumblr.com/}{Wes Anderson Palettes}
#' @param  name Name of desired palette. Choices are: \code{GrandBudapest}, \code{Moonrise1},  \code{Royal1},  \code{Moonrise2}, \code{Cavalcanti},  \code{Royal2}, \code{GrandBudapest2},  \code{Moonrise3},  \code{Chevalier}, \code{BottleRocket}, \code{darjeeling}, \code{darjeeling2} 
#' @param type Set to continuous if you require a gradient of colors similar to how heat map works.
#' @export

dsparks

# Randomly allocating observations into groups, for, e.g. cross-validation
kk <- 10  # Number of partitions, as in "kk-fold cross-validation."

# Here is a data.frame full of good data:
nn <- 1003
myData <- data.frame(matrix(rnorm(nn * 3), ncol = 3))
colnames(myData) <- LETTERS[1:3]

# This does not work:
whichK <- sample(LETTERS[1:kk], nrow(myData), replace = T)

briatte

# removes characters from multiple data frame columns
# example removes * , % characters

dw <- data.frame(gsub("\\*|,|%", "", as.matrix(dw)), stringsAsFactors = FALSE)