Load Data / Import Data into R
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 3.4.4 ✔ 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 errors
library(readr)
library(dplyr)
library (stringr)
chess_tournament <- read.csv(paste0("/Users/blessinga/Desktop/chess.txt"), header=F)
head(chess_tournament)
## V1
## 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 |
summary(chess_tournament)
## V1
## Length:196
## Class :character
## Mode :character
Part 2: Remove and Divide Sequence
#Remove Uneeded Rows (heading)
chess_tournament2 <- chess_tournament[-c(1:3),]
#Pull out rows : (3n+2) and (3n+3)
n <- length(chess_tournament2)
row1 <- chess_tournament2[seq(2, n, 3)]
row2 <- chess_tournament2[seq(3, n, 3)]
Calculate Opponent Average Scores
O_PreRating <- numeric(n / 3)
for (i in 1:(n / 3)) {
O_PreRating[i] <- mean(Plr_PreRating[as.numeric(unlist(Opponents[Plr_Num[i]]))])
}
Create Data Frame
csv <- data.frame(Plr_Name, Plr_State, Plr_Points, Plr_PreRating, O_PreRating); csv
## Plr_Name Plr_State Plr_Points Plr_PreRating O_PreRating
## 1 GARY HUA ON 6.0 1794 1605.286
## 2 DAKSHESH DARURI MI 6.0 1553 1469.286
## 3 ADITYA BAJAJ MI 6.0 1384 1563.571
## 4 PATRICK H SCHILLING MI 5.5 1716 1573.571
## 5 HANSHI ZUO MI 5.5 1655 1500.857
## 6 HANSEN SONG OH 5.0 1686 1518.714
## 7 GARY DEE SWATHELL MI 5.0 1649 1372.143
## 8 EZEKIEL HOUGHTON MI 5.0 1641 1468.429
## 9 STEFANO LEE ON 5.0 1411 1523.143
## 10 ANVIT RAO MI 5.0 1365 1554.143
## 11 CAMERON WILLIAM MC MI 4.5 1712 1467.571
## 12 KENNETH J TACK MI 4.5 1663 1506.167
## 13 TORRANCE HENRY JR MI 4.5 1666 1497.857
## 14 BRADLEY SHAW MI 4.5 1610 1515.000
## 15 ZACHARY JAMES HOUGHTON MI 4.5 1220 1483.857
## 16 MIKE NIKITIN MI 4.0 1604 1385.800
## 17 RONALD GRZEGORCZYK MI 4.0 1629 1498.571
## 18 DAVID SUNDEEN MI 4.0 1600 1480.000
## 19 DIPANKAR ROY MI 4.0 1564 1426.286
## 20 JASON ZHENG MI 4.0 1595 1410.857
## 21 DINH DANG BUI ON 4.0 1563 1470.429
## 22 EUGENE L MCCLURE MI 4.0 1555 1300.333
## 23 ALAN BUI ON 4.0 1363 1213.857
## 24 MICHAEL R ALDRICH MI 4.0 1229 1357.000
## 25 LOREN SCHWIEBERT MI 3.5 1745 1363.286
## 26 MAX ZHU ON 3.5 1579 1506.857
## 27 GAURAV GIDWANI MI 3.5 1552 1221.667
## 28 SOFIA ADINA MI 3.5 1507 1522.143
## 29 CHIEDOZIE OKORIE MI 3.5 1602 1313.500
## 30 GEORGE AVERY JONES ON 3.5 1522 1144.143
## 31 RISHI SHETTY MI 3.5 1494 1259.857
## 32 JOSHUA PHILIP MATHEWS ON 3.5 1441 1378.714
## 33 JADE GE MI 3.5 1449 1276.857
## 34 MICHAEL JEFFERY THOMAS MI 3.5 1399 1375.286
## 35 JOSHUA DAVID LEE MI 3.5 1438 1149.714
## 36 SIDDHARTH JHA MI 3.5 1355 1388.167
## 37 AMIYATOSH PWNANANDAM MI 3.5 980 1384.800
## 38 BRIAN LIU MI 3.0 1423 1539.167
## 39 JOEL R HENDON MI 3.0 1436 1429.571
## 40 FOREST ZHANG MI 3.0 1348 1390.571
## 41 KYLE WILLIAM MURPHY MI 3.0 1403 1248.500
## 42 JARED GE MI 3.0 1332 1149.857
## 43 ROBERT GLEN VASEY MI 3.0 1283 1106.571
## 44 JUSTIN D SCHILLING MI 3.0 1199 1327.000
## 45 DEREK YAN MI 3.0 1242 1152.000
## 46 JACOB ALEXANDER LAVALLEY MI 3.0 377 1357.714
## 47 ERIC WRIGHT MI 2.5 1362 1392.000
## 48 DANIEL KHAIN MI 2.5 1382 1355.800
## 49 MICHAEL J MARTIN MI 2.5 1291 1285.800
## 50 SHIVAM JHA MI 2.5 1056 1296.000
## 51 TEJAS AYYAGARI MI 2.5 1011 1356.143
## 52 ETHAN GUO MI 2.5 935 1494.571
## 53 JOSE C YBARRA MI 2.0 1393 1345.333
## 54 LARRY HODGE MI 2.0 1270 1206.167
## 55 ALEX KONG MI 2.0 1186 1406.000
## 56 MARISA RICCI MI 2.0 1153 1414.400
## 57 MICHAEL LU MI 2.0 1092 1363.000
## 58 VIRAJ MOHILE MI 2.0 917 1391.000
## 59 SEAN M MC MI 2.0 853 1319.000
## 60 JULIA SHEN MI 1.5 967 1330.200
## 61 JEZZEL FARKAS ON 1.5 955 1327.286
## 62 ASHWIN BALAJI MI 1.0 1530 1186.000
## 63 THOMAS JOSEPH HOSMER MI 1.0 1175 1350.200
## 64 BEN LI MI 1.0 1163 1263.000
Writing the CVS file
write.table(csv, file = "Project1_607_chessinfo.csv", sep = ",", col.names = T)