CUNY Data 607 Proj-1

Assignment Overview

This project was to read in a formatted for reading dataset in table format, and appropriately subset and filter the data so only certain portions were saved into a .csv type file, as well as add in a computed column based on data from many other rows.

The specifics…The file to read in was a file of a chess touranment, containing a list of players (two lines per player) their state, chess ID, pre and post-ratings, and the results of the tournament (wins/losses/draws etc., and the points won). Then from that file, select the Player Name, State, Points Won, Pre-Rating, and average of his/her opponents pre-ratings and save those values into a .csv formatted file.

Thoughts (or Assumptions):

The solution should work for any sized input file (within reason of course) and the input file’S formatting cannot change (results will be unpredictable if is…).

To use the solution (outside of the markdown) call the functions in this order:

• initialization
• createPlayerDataFrame (passing in filename to read from)
• computeOppAvgRating (using result of prior function as parameter)
• createSubsettedPlayerDF (using results of prior two functions as parameters)
• writeCSV (with df from prior function, and a file name)

##Initialization Function, loads needed library
intialization <- function()
{
    library(stringr)
}

##Creates a Data Frame from the passed in or deafaulted tournament file
createPlayerDataFrame <- function(fileName = "")
{
    if (is.null(fileName)|| fileName=="")
    {
        rawTournament <- readLines("tournamentinfo.txt")
    }
    else
    {
        rawTournament <- readLines(fileName)
    }
    ##the file has three lines repeated, two of are interest,  filter to the two sets of lines we care about
    player1stLine <- rawTournament[str_detect(rawTournament, "^ *\\d+ | Pair")]
    player2ndLine <- rawTournament[str_detect(rawTournament, "^ *[[:alpha:]]{2} | Num ")]  ## gets player 2nd line
    
    ##read the delmited lines into variables
    player1stLineDelim <- read.delim(text = player1stLine, sep = "|", stringsAsFactors = FALSE)
    player2ndLineDelim <- read.delim(text = player2ndLine, sep = "|", stringsAsFactors = FALSE)
    
    ##merge the two delmited variables into one dataframe
    dfPlayers <- data.frame(player1stLineDelim, player2ndLineDelim)
    dfPlayers <- subset(dfPlayers, select = c(-X, -X.1))  #(remove the "X" column")
    
    
    
    ##using regex, find the prerating value of each player and append to end of dataframe
    preRating <- str_replace(str_extract(dfPlayers[["USCF.ID...Rtg..Pre..Post."]], "R: +\\d{1,4}"),"R: *", "")
    dfPlayers <- data.frame(dfPlayers, preRating, stringsAsFactors = FALSE)
    dfPlayers <- populateHeaders(dfPlayers)
    return(dfPlayers) 
}

##function returns a numeric of the opp average rating from the passed in vector 
##of rounds which contains entries into the vector of oppsRatings
getOppAvgRating <- function(vRounds, vOppsRating)
{
    round(mean(vOppsRating[unlist(vRounds)], na.rm = TRUE))
}

##funciton takes in the players data.frame, and computes a vector of the
## average opponent ratings
computeOppAvgRating <- function(dfPlayers)
{
    
    rounds <- data.frame(lapply(lapply(lapply
                        (dfPlayers[,grepl("ROUND", names(dfPlayers))], str_replace, "[[:alpha:]]", "")
                        ,str_trim)
                        ,as.numeric)
                        ,stringsAsFactors = FALSE)
    
    apply(rounds, 1, getOppAvgRating, as.numeric(dfPlayers$PRERATING))
}



##creates dataframe of player information required in the asignment
createSubsettedPlayerDF <-function(dfPlayers, vOppsAvgRating)
{
        df <- data.frame(dfPlayers$PLAYER_NAME, dfPlayers$STATE, 
                         dfPlayers$TOTAL_PTS, dfPlayers$PRERATING, vOppsAvgRating)
        names(df) <- c( "Player Name", "State", "Total Points", "Pre-Tournament Rating", "Average Opp Rating")
        return(df)
}

##generic wrapper for csv, doesn't really do anything useful, 
##other than provide a function to demonstrate in the markdown file
writeCSV <- function(df, fileName)
{
    write.csv(df, file = fileName)
}

##Populate row headers with more meaningful names, especially if we might want to 
##do further data analysis on the input file later
populateHeaders <- function(dfp)
{
     names(dfp) <-(c("NAME",
      "PLAYER_NAME",
      "TOTAL_PTS",
      "ROUND1",
      "ROUND2",
      "ROUND3",
      "ROUND4",
      "ROUND5",
      "ROUND6",
      "ROUND7",
      "STATE",
      "ID_AND_PREPOST_RATING",
      "PTS",
      "RESULT1",
      "RESULT2",
      "RESULT3",
      "RESULT4",
      "RESULT5",
      "RESULT6",
      "RESULT7",
      "PRERATING"))
    return(dfp)

}

Here is the “head”" of the input file, to show how the input looks:

head(readLines("tournamentinfo.txt"))

## Warning in readLines("tournamentinfo.txt"): incomplete final line found on
## 'tournamentinfo.txt'

## [1] "-----------------------------------------------------------------------------------------" 
## [2] " Pair | Player Name                     |Total|Round|Round|Round|Round|Round|Round|Round| "
## [3] " Num  | USCF ID / Rtg (Pre->Post)       | Pts |  1  |  2  |  3  |  4  |  5  |  6  |  7  | "
## [4] "-----------------------------------------------------------------------------------------" 
## [5] "    1 | GARY HUA                        |6.0  |W  39|W  21|W  18|W  14|W   7|D  12|D   4|" 
## [6] "   ON | 15445895 / R: 1794   ->1817     |N:2  |W    |B    |W    |B    |W    |B    |W    |"

Below is the execution of the solution’s functions in the order suggested above

intialization()
dfP <- createPlayerDataFrame("tournamentInfo.txt")

## Warning in readLines(fileName): incomplete final line found on
## 'tournamentInfo.txt'

writeCSV(createSubsettedPlayerDF(dfP, computeOppAvgRating(dfP)), file = "chessResults.csv")

Finally below is the head of the .csv file, demonstrating the output is generated as expected

head(read.csv("chessResults.csv"))

##   X                       Player.Name  State Total.Points
## 1 1  GARY HUA                            ON           6.0
## 2 2  DAKSHESH DARURI                     MI           6.0
## 3 3  ADITYA BAJAJ                        MI           6.0
## 4 4  PATRICK H SCHILLING                 MI           5.5
## 5 5  HANSHI ZUO                          MI           5.5
## 6 6  HANSEN SONG                         OH           5.0
##   Pre.Tournament.Rating Average.Opp.Rating
## 1                  1794               1605
## 2                  1553               1469
## 3                  1384               1564
## 4                  1716               1574
## 5                  1655               1501
## 6                  1686               1519