# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages
# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats
# For example, here's several helpful packages to load in 

library(ggplot2) # Data visualization
library(readr) # CSV file I/O, e.g. the read_csv function

# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

system("ls ../input")

# Any results you write to the current directory are saved as output.
img_list = read_csv("../input/driver_imgs_list.csv")
img_list$filename <- paste("../input/train", img_list$classname, img_list$img, sep="/")

print(head(img_list))
img_list$wt <- 1

aggdata <-aggregate(img_list[,5], by=img_list[,1:2], FUN=sum, na.rm=TRUE)
print(aggdata)