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 For the first player, the information would be: Gary Hua, ON, 6.0, 1794, 1605
Firstly, I download the lirbaries needed to manipulate the file and data. Next, I go through the data to understand the format.
library(readr, quietly = TRUE)
library(stringr, quietly = TRUE)
theUrl <- 'https://raw.githubusercontent.com/dcorrea614/MSDS/master/tournamentinfo.txt'
dfTournament <- read_csv(file = theUrl,col_names = FALSE)## Parsed with column specification:
## cols(
## X1 = col_character()
## )head(dfTournament)## # A tibble: 6 x 1
## X1
## <chr>
## 1 -----------------------------------------------------------------------------~
## 2 Pair | Player Name |Total|Round|Round|Round|Round|Round|R~
## 3 Num | USCF ID / Rtg (Pre->Post) | Pts | 1 | 2 | 3 | 4 | 5 | ~
## 4 -----------------------------------------------------------------------------~
## 5 1 | GARY HUA |6.0 |W 39|W 21|W 18|W 14|W 7|D 1~
## 6 ON | 15445895 / R: 1794 ->1817 |N:2 |W |B |W |B |W |B ~tail(dfTournament)## # A tibble: 6 x 1
## X1
## <chr>
## 1 63 | THOMAS JOSEPH HOSMER |1.0 |L 2|L 48|D 49|L 43|L 45|H ~
## 2 MI | 15057092 / R: 1175 ->1125 | |W |B |W |B |B | ~
## 3 -----------------------------------------------------------------------------~
## 4 64 | BEN LI |1.0 |L 22|D 30|L 31|D 49|L 46|L ~
## 5 MI | 15006561 / R: 1163 ->1112 | |B |W |W |B |W |B ~
## 6 -----------------------------------------------------------------------------~Here, I notice the pattern of where the data is stored. The first 4 lines are not part of the dataset. It is followed by player information and games played, repeating after every 3 lines. I, then, separate the data into 2 matrices to resemble a more tradition data set.
mTournament <- matrix(unlist(dfTournament), byrow=TRUE)
m1 <- mTournament[seq(5,length(mTournament),3)]
head(m1)## [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|"m2 <- mTournament[seq(6,length(mTournament),3)]
head(m2)## [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 |"The next step is to capture the feature values in vectors using string manipulation and regular expressions. All the features can be captured by standard extraction, besides the Average Pre Chess Rating of Opponents.
# matching first numbers
ID <- as.numeric(str_extract(m1, '\\d+'))
# matching the first combination of a letter, any amount of characters and "|"
Name <- str_extract(m1, '[A-z].{1,32}')
# extracting the name
Name <- str_trim(str_extract(Name, '.+\\s{2,}'))
# matching the first two letters (state) in the second matrix
State <- str_extract(m2, '[A-Z]{2}')
# matching at least 1 number, a period, and 1 number
TotalNumberofPoints <- as.numeric(str_extract(m1, '\\d+\\.\\d'))
# matching the combination of "R", any characters and "-"
PreRating <- str_extract(m2, 'R:.{8,}-')
# matching first 4 numbers
PreRating <- as.numeric(str_extract(PreRating, '\\d{1,4}'))
# matching all combinations of 1 letter 2 spaces and any numbers
Rounds <- str_extract_all(m1, '[A-Z]\\s{2,}\\d+')
# matching numbers
Rounds <- str_extract_all(Rounds, '\\d+')Using two vectors from the previous step, I am able to calculate the Average Pre Chess Rating of Opponents using a loop.
AvgOppPreChessRating <- c()
for(i in c(1:length(Rounds))){
AvgOppPreChessRating[i] <- round(mean(PreRating[as.numeric(Rounds[[i]])]),0)
}
AvgOppPreChessRating## [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 1263Project1 <- data.frame(ID,Name,State,TotalNumberofPoints,PreRating,AvgOppPreChessRating)
head(Project1)## ID Name State TotalNumberofPoints PreRating
## 1 1 GARY HUA ON 6.0 1794
## 2 2 DAKSHESH DARURI MI 6.0 1553
## 3 3 ADITYA BAJAJ MI 6.0 1384
## 4 4 PATRICK H SCHILLING MI 5.5 1716
## 5 5 HANSHI ZUO MI 5.5 1655
## 6 6 HANSEN SONG OH 5.0 1686
## AvgOppPreChessRating
## 1 1605
## 2 1469
## 3 1564
## 4 1574
## 5 1501
## 6 1519write_csv(Project1, 'tournament.csv' , append = FALSE)