arcaravaggi

# Read in all csv files in directory
files <- list.files(pattern = "*.csv")

# Create dfs for each csv then create list
for (i in 1:length(files)) 
  assign(files[i], 
         read.csv(files[i]))

lst <- mget(ls(pattern = "*.csv"))

arcaravaggi

#From https://stackoverflow.com/questions/1401904/painless-way-to-install-a-new-version-of-r

# Run in the old version of R (or via RStudio)
setwd("C:/Temp/") 
packages <- installed.packages()[,"Package"] 
save(packages, file="Rpackages") 

# INSTALL NEW R VERSION
if(!require(installr)) { install.packages("installr"); require(installr)} #load / install+load installr
# See here for more on installr: https://www.r-statistics.com/2013/03/updating-r-from-r-on-windows-using-the-installr-package/  

arcaravaggi

##arrange df vars by position
# from https://stackoverflow.com/questions/5620885/how-does-one-reorder-columns-in-a-data-frame
##'vars' must be a named vector, e.g. c("var.name"=1)
# e.g.
# table <- data.frame(Time=c(1,2), In=c(2,3), Out=c(3,4), Files=c(4,5))
# arrange.vars(table, c("Out"=2))
# arrange.vars(table, c("Out"=2, "Files"=1, "Time"=4))

arrange.vars <- function(data, vars){
  ##stop if not a data.frame (but should work for matrices as well)

arcaravaggi

# Split column into multiple based on spaces, extra characters, etc.

df <- data.frame(x= c("crust (5)","things (3)","stuff (8)"))

library(tidyr)

df2 <- extract(df, x, into = c("pet", "sampSize"), "([^(]+)\\s+\\(([0-9]+).")

arcaravaggi

# Create labelled list of all active dataframes

my.list <- mget(ls(pattern="*_UMAC"))

# Use write.csv in a for loop, creating files for each and naming
# according to label (i.e. df name)

for (i in seq_along(my.list)){
  write.csv(my.list[i], paste(names(my.list)[i], ".csv"), col.names = TRUE)
}