dgrtwo

parsetidy <- function(x, ...) UseMethod("parsetidy")


parsetidy.default <- function(x, ...) {
  # if it's not a call or name (e.g. it's numeric),
  # don't need it
  data.frame()
}

dgrtwo

# somewhat hackish solution to:
# https://twitter.com/EamonCaddigan/status/646759751242620928
# based mostly on copy/pasting from ggplot2 geom_violin source:
# https://github.com/hadley/ggplot2/blob/master/R/geom-violin.r

library(ggplot2)
library(dplyr)


"%||%" <- function(a, b) {

dgrtwo

## helper and setup functions

wrap_party_df <- function(func) {
    function(x, object, ...) {
        n <- col_name(substitute(object))
        
        # have to create an expression since we cannot rely on local
        # variables
        args <- list(...)
        expr <- substitute(do.call(func, c(list(.[[colname]][[1]]), args)),

dgrtwo

library(readr)
library(dplyr)

start <- read_delim("col3 col2 col4 col1
h a t t
i v i g
k s g n
n g n i", delim = " ")

start %>%

dgrtwo

theme_blank <- function(...) {
  ret <- theme_bw(...)
  ret$line <- element_blank()
  ret$rect <- element_blank()
  ret$strip.text <- element_blank()
  ret$axis.text <- element_blank()
  ret$plot.title <- element_blank()
  ret$axis.title <- element_blank()
  ret$plot.margin <- structure(c(0, 0, -1, -1), unit = "lines", valid.unit = 3L, class = "unit")
  ret

dgrtwo

Keybase proof

I hereby claim:

• I am dgrtwo on github.
• I am drobinson (https://keybase.io/drobinson) on keybase.
• I have a public key whose fingerprint is 2BFD FAC9 CDA9 669F FE2C 6973 C0B7 A65C CA30 6675

To claim this, I am signing this object:

dgrtwo

# data cleaning based on http://blog.dominodatalab.com/r-in-ecology/
library(dplyr)
library(tidyr)
library(readr)
library(stringr)
library(auriel)

infolder <- "night_files/"
masterdat2 <- data_frame(file = list.files(infolder)) %>%
  group_by(file) %>%

dgrtwo

#' Add a column counting or tallying observations within groups
#'
#' \code{add_tally} adds a column named "n" (or similar) to a table based on the number
#' of items within each group. These functions are to \code{tally} and
#' \code{count} as \code{mutate} is to \code{summarise}: they add an additional
#' column. They tally within the groups of the current data, and do not change them.
#'
#' @param x A table
#' @param wt (Optional) If omitted, will count the number of rows. Otherwise, use a weighted tally
#' @param sort Whether to sort the result in descending order of n

dgrtwo

grouply <- function(f, ...) {
  groups <- lazyeval::lazy_dots(...)
  
  function(tbl, ...) {
    dplyr::group_by_(tbl, .dots = groups) %>%
      f(...) %>%
      dplyr::ungroup()
  }
}

dgrtwo

#' Convert a dplyr expression to a list of step objects
separate_steps <- function(expr, iscall=FALSE) {
  if (iscall) {
    call <- expr
  } else {
    call <- match.call()[["expr"]]
  }
  
  len <- length(call)
  if (len == 1) {