##Final R assignment in Intro to Statistics course, fall semster.
#+Written by Matan Horovitz (207130253) and Guy Amzaleg ()
#+We have chosen a dataset of the first 600,000 commits to the  Linux Kernel Git repository - as published on Kaggle:
#+https://www.kaggle.com/datasets/philschmidt/linux-kernel-git-revision-history
#+This dataset examines commits made to the Linux kernel project over the last 12 years.
raw_kernel_commits <- read.csv("/home/shmick/linux_kernel_git_revlog.csv")
##BONUS: convert from EPOCH: as.Date(as.POSIXct(1100171890,origin = "1970-01-01"))
View(raw_kernel_commits)
##For question 1, we have chosen to examine whether the amount of changes (additions and deletions) vary over time.
##A larger amount of changes per commit is correlated with a decrease in the quality of the code - as more changes
#+are harder to track and audit, while a smaller amount of changes per commit implies stricter coding standards
#+over time.
##To examine the correlation, we made a subset of the dataset, discarding data which is irrelevant to our question,
#+and summed all changes from the same commits into an aggregate - as we are not concerned about the files changed,
#+only the total amount of changes on each individual commit.

kernel_commits <- subset(raw_kernel_commits, select= c(author_timestamp,n_additions,n_deletions))
#  Make a subset  ^ of the dataset which includes  ^ the EPOCH time,^ additions ^ and deletions. 
#Rename the resulting dataset into friendlier column names
colnames(kernel_commits) <- c("EPOCH","Additions","Deletions")
#Sum additions and deletion into a new column, named "Total changes"
kernel_commits["Total changes"] <- kernel_commits["Additions"]+kernel_commits["Deletions"]
View(kernel_commits) #< examine the resulting dataset
#Unite all commits with same EPOCH to get changes PER COMMIT
kernel_commits_sum <- aggregate(. ~ EPOCH,data=kernel_commits,FUN=sum)
                          
View(kernel_commits_sum)
#Measure the correlation between EPOCH time (from oldest to newest) and the total number of changes per commit.
cor(kernel_commits_sum["EPOCH"],kernel_commits_sum["Total changes"])

##QUESTION 2: measure number of columns in our dataset and calculate a permutation and combination of 
#+that number, minus two, and 3.

#Calculate total number of columns in our dataset
n <- ncol(kernel_commits)
View(n)

##QUESTION 3: pick two categorial variables - month (?), is documentation