In this document, the text file containing information about players in a chess tournament is imported and then formatted a specific way. First, the text file is imported. After it is imported, it is formatted into a new data frame that contains all relevant columns. Once the new data frame is completed, it is then output as a csv file. Lastly, the data frame is displayed as a table.
In this section, the file is imported and then formatted into a new table
test1 <- read.table(file = 'https://raw.githubusercontent.com/juliaDataScience-22/cuny-fall-23/manage-acquire-data/tournament-info.txt', fill = TRUE, header = FALSE, sep = " ", dec = "|")
test1 <- test1[,-1]
test1 <- test1[,-1]
test1 <- test1[,-1]
test1 <- test1[-149,]
test1 <- test1[-156,]
test1 <- test1[-163,]
test1 <- test1[-164,]
test1 <- test1[-167,]
test1 <- test1[-170,]
test1 <- test1[-173,]
test1 <- test1[-176,]
test1 <- test1[-179,]
test1 <- test1[-182,]
test1 <- test1[-185,]
test1 <- test1[-190,]
test1 <- test1[-191,]
test1 <- test1[-194,]
test1 <- test1[-136,]
library(tidyr)
test1 <- unite(test1, col = 'V9', c(V9, V10), sep="")
test2 <- data.frame(Name = c(1:64), State = c(1:64), Total.Points = c(1:64), Pre.Rating = c(1:64), Avg.Pre.Rating.Opponents = c(1:64))
test2$Pre.Rating <- test1$V9[c(seq(6,197,3))]
library(stringr)
test2[c('Pre.Rating', 'To.Delete')] <- str_split_fixed(test2$Pre.Rating, 'P', 2)
test2 <- test2[,-6]
test1 <- unite(test1, col = 'Names2', c(V6, V7, V8, V9), sep=" ")
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniontest1 <- test1 %>% mutate(Names2 = str_replace_all(Names2, '\\|', ""))
test2$Name <- test1$Names2[c(seq(5, 194, 3))]
test2$State <- test1$V4[c(seq(6, 195, 3))]
indices <- which(test1 == "|6.0" | test1 == "|5.5" | test1=="|5.0" | test1 == "|4.5" | test1 == "|4.0" | test1 == "|3.5" | test1 == "|3.0" | test1 == "|2.5" | test1 == "|2.0" | test1 == "|1.5" | test1 == "|1.0", arr.ind=TRUE)
indices <- indices[order(indices[,1],decreasing=FALSE),]
num <- 1
for (i in 1:64)
{
loc <- c(indices[[i]], indices[[i+64]])
test2$Total.Points[num] <- test1[loc[1],loc[2]]
num <- num + 1
}
test2[c('Total.Points', 'To Delete')] <- str_split_fixed(test2$Total.Points, "\\|", 2)
test2$Total.Points <- test2$`To Delete`
test2 <- test2[,-6]
count <- 1
for (i in seq(5, 194, 3))
{
test4 <- test1[i,9:43]
test4 <- test4 |> mutate_all(na_if,"")
indices <- which(!is.na(test4), arr.ind=TRUE)
indices <- indices[-1,]
indices <- indices[-1,]
avgRatingOpp <- 0
players <- 0
for (num in 1:nrow(indices))
{
loc <- indices[[num + nrow(indices)]]
player1 <- str_split_fixed(test4[loc], "\\|", 2)[1]
if(player1 != "")
{
value1 <- test2$Pre.Rating[as.numeric(player1)]
avgRatingOpp <- (as.numeric(value1) + avgRatingOpp)
players <- players + 1
}
}
test2$Avg.Pre.Rating.Opponents[count] <- round(avgRatingOpp / players)
count <- count + 1
}
write.csv(test2, "chessData.csv", row.names = FALSE)In this section, a table is created to display the results. To see the table as a csv file, locate the file named chessData.csv.
library(gt)
gt(test2) |>
tab_header(
title = "Table 1",
subtitle = "Chess Tournament - Player Information"
)| Table 1 | ||||
| Chess Tournament - Player Information | ||||
| Name | State | Total.Points | Pre.Rating | Avg.Pre.Rating.Opponents |
|---|---|---|---|---|
| GARY HUA | ON | 6.0 | 1794 | 1605 |
| DAKSHESH DARURI | MI | 6.0 | 1553 | 1469 |
| ADITYA BAJAJ | MI | 6.0 | 1384 | 1564 |
| PATRICK H SCHILLING | MI | 5.5 | 1716 | 1574 |
| HANSHI ZUO | MI | 5.5 | 1655 | 1501 |
| HANSEN SONG | OH | 5.0 | 1686 | 1519 |
| GARY DEE SWATHELL | MI | 5.0 | 1649 | 1372 |
| EZEKIEL HOUGHTON | MI | 5.0 | 1641 | 1468 |
| STEFANO LEE | ON | 5.0 | 1411 | 1523 |
| ANVIT RAO | MI | 5.0 | 1365 | 1554 |
| CAMERON WILLIAM MC LEMAN | MI | 4.5 | 1712 | 1468 |
| KENNETH J TACK | MI | 4.5 | 1663 | 1506 |
| TORRANCE HENRY JR | MI | 4.5 | 1666 | 1498 |
| BRADLEY SHAW | MI | 4.5 | 1610 | 1515 |
| ZACHARY JAMES HOUGHTON | MI | 4.5 | 1220 | 1484 |
| MIKE NIKITIN | MI | 4.0 | 1604 | 1386 |
| RONALD GRZEGORCZYK | MI | 4.0 | 1629 | 1499 |
| DAVID SUNDEEN | MI | 4.0 | 1600 | 1480 |
| DIPANKAR ROY | MI | 4.0 | 1564 | 1426 |
| JASON ZHENG | MI | 4.0 | 1595 | 1411 |
| DINH DANG BUI | ON | 4.0 | 1563 | 1470 |
| EUGENE L MCCLURE | MI | 4.0 | 1555 | 1300 |
| ALAN BUI | ON | 4.0 | 1363 | 1214 |
| MICHAEL R ALDRICH | MI | 4.0 | 1229 | 1357 |
| LOREN SCHWIEBERT | MI | 3.5 | 1745 | 1363 |
| MAX ZHU | ON | 3.5 | 1579 | 1507 |
| GAURAV GIDWANI | MI | 3.5 | 1552 | 1222 |
| SOFIA ADINA STANESCU-BELLU | MI | 3.5 | 1507 | 1571 |
| CHIEDOZIE OKORIE | MI | 3.5 | 1602 | 1314 |
| GEORGE AVERY JONES | ON | 3.5 | 1522 | 1144 |
| RISHI SHETTY | MI | 3.5 | 1494 | 1260 |
| JOSHUA PHILIP MATHEWS | ON | 3.5 | 1441 | 1379 |
| JADE GE | MI | 3.5 | 1449 | 1277 |
| MICHAEL JEFFERY THOMAS | MI | 3.5 | 1399 | 1375 |
| JOSHUA DAVID LEE | MI | 3.5 | 1438 | 1150 |
| SIDDHARTH JHA | MI | 3.5 | 1355 | 1388 |
| AMIYATOSH PWNANANDAM | MI | 3.5 | 980 | 1385 |
| BRIAN LIU | MI | 3.0 | 1423 | 1539 |
| JOEL R HENDON | MI | 3.0 | 1436 | 1430 |
| FOREST ZHANG | MI | 3.0 | 1348 | 1391 |
| KYLE WILLIAM MURPHY | MI | 3.0 | 1403 | 1248 |
| JARED GE | MI | 3.0 | 1332 | 1150 |
| ROBERT GLEN VASEY | MI | 3.0 | 1283 | 1107 |
| JUSTIN D SCHILLING | MI | 3.0 | 1199 | 1327 |
| DEREK YAN | MI | 3.0 | 1242 | 1152 |
| JACOB ALEXANDER LAVALLEY | MI | 3.0 | 377 | 1358 |
| ERIC WRIGHT | MI | 2.5 | 1362 | 1392 |
| DANIEL KHAIN | MI | 2.5 | 1382 | 1356 |
| MICHAEL J MARTIN | MI | 2.5 | 1291 | 1286 |
| SHIVAM JHA | MI | 2.5 | 1056 | 1296 |
| TEJAS AYYAGARI | MI | 2.5 | 1011 | 1356 |
| ETHAN GUO | MI | 2.5 | 935 | 1495 |
| JOSE C YBARRA | MI | 2.0 | 1393 | 1345 |
| LARRY HODGE | MI | 2.0 | 1270 | 1206 |
| ALEX KONG | MI | 2.0 | 1186 | 1406 |
| MARISA RICCI | MI | 2.0 | 1153 | 1414 |
| MICHAEL LU | MI | 2.0 | 1092 | 1363 |
| VIRAJ MOHILE | MI | 2.0 | 917 | 1391 |
| SEAN M MC CORMICK | MI | 2.0 | 853 | 1319 |
| JULIA SHEN | MI | 1.5 | 967 | 1330 |
| JEZZEL FARKAS | ON | 1.5 | 955 | 1327 |
| ASHWIN BALAJI | MI | 1.0 | 1530 | 1186 |
| THOMAS JOSEPH HOSMER | MI | 1.0 | 1175 | 1350 |
| BEN LI | MI | 1.0 | 1163 | 1263 |