In this project, you’re given a text file with chess tournament results where the information has some structure. Your job is to create an R Markdown file that generates a .CSV file (that could for example be imported into a SQL database) with the following information for all of the players: Player’s Name, Player’s State, Total Number of Points, Player’s Pre-Rating, and Average Pre Chess Rating of Opponents
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(dplyr)
library(tidyr)gitlink <- "https://raw.githubusercontent.com/ErickH1/DATA607Project1/refs/heads/main/tournamentinfo.txt"
chess_raw_data <- readLines(gitlink)## Warning in readLines(gitlink): incomplete final line found on
## 'https://raw.githubusercontent.com/ErickH1/DATA607Project1/refs/heads/main/tournamentinfo.txt'head(chess_raw_data, 7)## [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 |"
## [7] "-----------------------------------------------------------------------------------------"Inserting text data into a matrix to make data capturing and processing easier.
chess_data_matrix <- matrix(unlist(chess_raw_data), byrow=TRUE)
matrix_1 <- chess_data_matrix[seq(5,length(chess_data_matrix),3)]
matrix_2 <- chess_data_matrix[seq(6,length(chess_data_matrix),3)]
head(chess_data_matrix,10)## [,1]
## [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 |"
## [7,] "-----------------------------------------------------------------------------------------"
## [8,] " 2 | DAKSHESH DARURI |6.0 |W 63|W 58|L 4|W 17|W 16|W 20|W 7|"
## [9,] " MI | 14598900 / R: 1553 ->1663 |N:2 |B |W |B |W |B |W |B |"
## [10,] "-----------------------------------------------------------------------------------------"head(matrix_1)## [1] " 1 | GARY HUA |6.0 |W 39|W 21|W 18|W 14|W 7|D 12|D 4|"
## [2] " 2 | DAKSHESH DARURI |6.0 |W 63|W 58|L 4|W 17|W 16|W 20|W 7|"
## [3] " 3 | ADITYA BAJAJ |6.0 |L 8|W 61|W 25|W 21|W 11|W 13|W 12|"
## [4] " 4 | PATRICK H SCHILLING |5.5 |W 23|D 28|W 2|W 26|D 5|W 19|D 1|"
## [5] " 5 | HANSHI ZUO |5.5 |W 45|W 37|D 12|D 13|D 4|W 14|W 17|"
## [6] " 6 | HANSEN SONG |5.0 |W 34|D 29|L 11|W 35|D 10|W 27|W 21|"head(matrix_2)## [1] " ON | 15445895 / R: 1794 ->1817 |N:2 |W |B |W |B |W |B |W |"
## [2] " MI | 14598900 / R: 1553 ->1663 |N:2 |B |W |B |W |B |W |B |"
## [3] " MI | 14959604 / R: 1384 ->1640 |N:2 |W |B |W |B |W |B |W |"
## [4] " MI | 12616049 / R: 1716 ->1744 |N:2 |W |B |W |B |W |B |B |"
## [5] " MI | 14601533 / R: 1655 ->1690 |N:2 |B |W |B |W |B |W |B |"
## [6] " OH | 15055204 / R: 1686 ->1687 |N:3 |W |B |W |B |B |W |B |"Using Regex and string manipulation to extract relevant information into vectors.
ID <- as.numeric(str_extract(matrix_1, '\\d+'))
Name <- str_trim(str_extract(str_extract(matrix_1, '[A-z].{1,32}'), '.+\\s{2,}'))
State <- str_extract(matrix_2, '[A-Z]{2}')
Total_Points <- as.numeric(str_extract(matrix_1, '\\d+\\.\\d'))
Pre_Rating <- as.numeric(str_extract(str_extract(matrix_2, 'R:.{8,}-'), '\\d{1,4}'))
Rounds <- str_extract_all(matrix_1, '[A-Z]\\s{2,}\\d+')
Rounds <- str_extract_all(Rounds, '\\d+')## Warning in stri_extract_all_regex(string, pattern, simplify = simplify, :
## argument is not an atomic vector; coercingCalculating avg opponent rating using pre rating and rounds vectors. Instead of for loops utilized sapply.
Avg_Opp_Pre_Rating <- sapply(Rounds, function(x) round(mean(Pre_Rating[as.numeric(x)]), 0))
Avg_Opp_Pre_Rating## [1] 1605 1469 1564 1574 1501 1519 1372 1468 1523 1554 1468 1506 1498 1515 1484
## [16] 1386 1499 1480 1426 1411 1470 1300 1214 1357 1363 1507 1222 1522 1314 1144
## [31] 1260 1379 1277 1375 1150 1388 1385 1539 1430 1391 1248 1150 1107 1327 1152
## [46] 1358 1392 1356 1286 1296 1356 1495 1345 1206 1406 1414 1363 1391 1319 1330
## [61] 1327 1186 1350 1263chess_data <- data.frame(ID,Name,State,Total_Points,Pre_Rating,Avg_Opp_Pre_Rating)
head(chess_data)write.csv(chess_data, "chesstournamentinfo.csv")