####set up####

rm(list=ls())

##packages
library(crawl)
library(dplyr)
library(sf)
library(ggplot2)
library(rgdal)
library(raster)
library(mapview)
library(tidyr)


####read in data and make large datasheet####

#want a large datasheet so can do global means across true and null steps for all

#list files

files <- list.files("data/find ladder/final SSF dataframes")


for (i in 1:length(files)){
  data1 <- read.csv(paste0("data/find ladder/final SSF dataframes/",files[[i]]))
  if(i==1){
    data_big <- data1
  }
  if(i>1){
    data_big <- rbind(data_big,data1)
  }
}

####check df####

str(data_big)
summary(data_big)


####summarise for means and sd####

params <- names(data_big)
names_to_standardise <- params[c(17,18,22:49)]


summaries <- vtable::sumtable(data_big[,c(17,18,22:49)],out="csv")


write.csv(summaries,"summary_stats_for_standardising.csv")