chess_raw <- read.delim("https://raw.githubusercontent.com/humbertohpgit/MSDS1stSem/master/chess_raw.txt", header = FALSE, sep = "\t", stringsAsFactors=FALSE)
chess_raw## 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 |
## 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 -----------------------------------------------------------------------------------------
## 11 3 | ADITYA BAJAJ |6.0 |L 8|W 61|W 25|W 21|W 11|W 13|W 12|
## 12 MI | 14959604 / R: 1384 ->1640 |N:2 |W |B |W |B |W |B |W |
## 13 -----------------------------------------------------------------------------------------
## 14 4 | PATRICK H SCHILLING |5.5 |W 23|D 28|W 2|W 26|D 5|W 19|D 1|
## 15 MI | 12616049 / R: 1716 ->1744 |N:2 |W |B |W |B |W |B |B |
## 16 -----------------------------------------------------------------------------------------
## 17 5 | HANSHI ZUO |5.5 |W 45|W 37|D 12|D 13|D 4|W 14|W 17|
## 18 MI | 14601533 / R: 1655 ->1690 |N:2 |B |W |B |W |B |W |B |
## 19 -----------------------------------------------------------------------------------------
## 20 6 | HANSEN SONG |5.0 |W 34|D 29|L 11|W 35|D 10|W 27|W 21|
## 21 OH | 15055204 / R: 1686 ->1687 |N:3 |W |B |W |B |B |W |B |
## 22 -----------------------------------------------------------------------------------------
## 23 7 | GARY DEE SWATHELL |5.0 |W 57|W 46|W 13|W 11|L 1|W 9|L 2|
## 24 MI | 11146376 / R: 1649 ->1673 |N:3 |W |B |W |B |B |W |W |
## 25 -----------------------------------------------------------------------------------------
## 26 8 | EZEKIEL HOUGHTON |5.0 |W 3|W 32|L 14|L 9|W 47|W 28|W 19|
## 27 MI | 15142253 / R: 1641P17->1657P24 |N:3 |B |W |B |W |B |W |W |
## 28 -----------------------------------------------------------------------------------------
## 29 9 | STEFANO LEE |5.0 |W 25|L 18|W 59|W 8|W 26|L 7|W 20|
## 30 ON | 14954524 / R: 1411 ->1564 |N:2 |W |B |W |B |W |B |B |
## 31 -----------------------------------------------------------------------------------------
## 32 10 | ANVIT RAO |5.0 |D 16|L 19|W 55|W 31|D 6|W 25|W 18|
## 33 MI | 14150362 / R: 1365 ->1544 |N:3 |W |W |B |B |W |B |W |
## 34 -----------------------------------------------------------------------------------------
## 35 11 | CAMERON WILLIAM MC LEMAN |4.5 |D 38|W 56|W 6|L 7|L 3|W 34|W 26|
## 36 MI | 12581589 / R: 1712 ->1696 |N:3 |B |W |B |W |B |W |B |
## 37 -----------------------------------------------------------------------------------------
## 38 12 | KENNETH J TACK |4.5 |W 42|W 33|D 5|W 38|H |D 1|L 3|
## 39 MI | 12681257 / R: 1663 ->1670 |N:3 |W |B |W |B | |W |B |
## 40 -----------------------------------------------------------------------------------------
## 41 13 | TORRANCE HENRY JR |4.5 |W 36|W 27|L 7|D 5|W 33|L 3|W 32|
## 42 MI | 15082995 / R: 1666 ->1662 |N:3 |B |W |B |B |W |W |B |
## 43 -----------------------------------------------------------------------------------------
## 44 14 | BRADLEY SHAW |4.5 |W 54|W 44|W 8|L 1|D 27|L 5|W 31|
## 45 MI | 10131499 / R: 1610 ->1618 |N:3 |W |B |W |W |B |B |W |
## 46 -----------------------------------------------------------------------------------------
## 47 15 | ZACHARY JAMES HOUGHTON |4.5 |D 19|L 16|W 30|L 22|W 54|W 33|W 38|
## 48 MI | 15619130 / R: 1220P13->1416P20 |N:3 |B |B |W |W |B |B |W |
## 49 -----------------------------------------------------------------------------------------
## 50 16 | MIKE NIKITIN |4.0 |D 10|W 15|H |W 39|L 2|W 36|U |
## 51 MI | 10295068 / R: 1604 ->1613 |N:3 |B |W | |B |W |B | |
## 52 -----------------------------------------------------------------------------------------
## 53 17 | RONALD GRZEGORCZYK |4.0 |W 48|W 41|L 26|L 2|W 23|W 22|L 5|
## 54 MI | 10297702 / R: 1629 ->1610 |N:3 |W |B |W |B |W |B |W |
## 55 -----------------------------------------------------------------------------------------
## 56 18 | DAVID SUNDEEN |4.0 |W 47|W 9|L 1|W 32|L 19|W 38|L 10|
## 57 MI | 11342094 / R: 1600 ->1600 |N:3 |B |W |B |W |B |W |B |
## 58 -----------------------------------------------------------------------------------------
## 59 19 | DIPANKAR ROY |4.0 |D 15|W 10|W 52|D 28|W 18|L 4|L 8|
## 60 MI | 14862333 / R: 1564 ->1570 |N:3 |W |B |W |B |W |W |B |
## 61 -----------------------------------------------------------------------------------------
## 62 20 | JASON ZHENG |4.0 |L 40|W 49|W 23|W 41|W 28|L 2|L 9|
## 63 MI | 14529060 / R: 1595 ->1569 |N:4 |W |B |W |B |W |B |W |
## 64 -----------------------------------------------------------------------------------------
## 65 21 | DINH DANG BUI |4.0 |W 43|L 1|W 47|L 3|W 40|W 39|L 6|
## 66 ON | 15495066 / R: 1563P22->1562 |N:3 |B |W |B |W |W |B |W |
## 67 -----------------------------------------------------------------------------------------
## 68 22 | EUGENE L MCCLURE |4.0 |W 64|D 52|L 28|W 15|H |L 17|W 40|
## 69 MI | 12405534 / R: 1555 ->1529 |N:4 |W |B |W |B | |W |B |
## 70 -----------------------------------------------------------------------------------------
## 71 23 | ALAN BUI |4.0 |L 4|W 43|L 20|W 58|L 17|W 37|W 46|
## 72 ON | 15030142 / R: 1363 ->1371 | |B |W |B |W |B |W |B |
## 73 -----------------------------------------------------------------------------------------
## 74 24 | MICHAEL R ALDRICH |4.0 |L 28|L 47|W 43|L 25|W 60|W 44|W 39|
## 75 MI | 13469010 / R: 1229 ->1300 |N:4 |B |W |B |B |W |W |B |
## 76 -----------------------------------------------------------------------------------------
## 77 25 | LOREN SCHWIEBERT |3.5 |L 9|W 53|L 3|W 24|D 34|L 10|W 47|
## 78 MI | 12486656 / R: 1745 ->1681 |N:4 |B |W |B |W |B |W |B |
## 79 -----------------------------------------------------------------------------------------
## 80 26 | MAX ZHU |3.5 |W 49|W 40|W 17|L 4|L 9|D 32|L 11|
## 81 ON | 15131520 / R: 1579 ->1564 |N:4 |B |W |B |W |B |W |W |
## 82 -----------------------------------------------------------------------------------------
## 83 27 | GAURAV GIDWANI |3.5 |W 51|L 13|W 46|W 37|D 14|L 6|U |
## 84 MI | 14476567 / R: 1552 ->1539 |N:4 |W |B |W |B |W |B | |
## 85 -----------------------------------------------------------------------------------------
## 86 28 | SOFIA ADINA STANESCU-BELLU |3.5 |W 24|D 4|W 22|D 19|L 20|L 8|D 36|
## 87 MI | 14882954 / R: 1507 ->1513 |N:3 |W |W |B |W |B |B |W |
## 88 -----------------------------------------------------------------------------------------
## 89 29 | CHIEDOZIE OKORIE |3.5 |W 50|D 6|L 38|L 34|W 52|W 48|U |
## 90 MI | 15323285 / R: 1602P6 ->1508P12 |N:4 |B |W |B |W |W |B | |
## 91 -----------------------------------------------------------------------------------------
## 92 30 | GEORGE AVERY JONES |3.5 |L 52|D 64|L 15|W 55|L 31|W 61|W 50|
## 93 ON | 12577178 / R: 1522 ->1444 | |W |B |B |W |W |B |B |
## 94 -----------------------------------------------------------------------------------------
## 95 31 | RISHI SHETTY |3.5 |L 58|D 55|W 64|L 10|W 30|W 50|L 14|
## 96 MI | 15131618 / R: 1494 ->1444 | |B |W |B |W |B |W |B |
## 97 -----------------------------------------------------------------------------------------
## 98 32 | JOSHUA PHILIP MATHEWS |3.5 |W 61|L 8|W 44|L 18|W 51|D 26|L 13|
## 99 ON | 14073750 / R: 1441 ->1433 |N:4 |W |B |W |B |W |B |W |
## 100 -----------------------------------------------------------------------------------------
## 101 33 | JADE GE |3.5 |W 60|L 12|W 50|D 36|L 13|L 15|W 51|
## 102 MI | 14691842 / R: 1449 ->1421 | |B |W |B |W |B |W |B |
## 103 -----------------------------------------------------------------------------------------
## 104 34 | MICHAEL JEFFERY THOMAS |3.5 |L 6|W 60|L 37|W 29|D 25|L 11|W 52|
## 105 MI | 15051807 / R: 1399 ->1400 | |B |W |B |B |W |B |W |
## 106 -----------------------------------------------------------------------------------------
## 107 35 | JOSHUA DAVID LEE |3.5 |L 46|L 38|W 56|L 6|W 57|D 52|W 48|
## 108 MI | 14601397 / R: 1438 ->1392 | |W |W |B |W |B |B |W |
## 109 -----------------------------------------------------------------------------------------
## 110 36 | SIDDHARTH JHA |3.5 |L 13|W 57|W 51|D 33|H |L 16|D 28|
## 111 MI | 14773163 / R: 1355 ->1367 |N:4 |W |B |W |B | |W |B |
## 112 -----------------------------------------------------------------------------------------
## 113 37 | AMIYATOSH PWNANANDAM |3.5 |B |L 5|W 34|L 27|H |L 23|W 61|
## 114 MI | 15489571 / R: 980P12->1077P17 | | |B |W |W | |B |W |
## 115 -----------------------------------------------------------------------------------------
## 116 38 | BRIAN LIU |3.0 |D 11|W 35|W 29|L 12|H |L 18|L 15|
## 117 MI | 15108523 / R: 1423 ->1439 |N:4 |W |B |W |W | |B |B |
## 118 -----------------------------------------------------------------------------------------
## 119 39 | JOEL R HENDON |3.0 |L 1|W 54|W 40|L 16|W 44|L 21|L 24|
## 120 MI | 12923035 / R: 1436P23->1413 |N:4 |B |W |B |W |B |W |W |
## 121 -----------------------------------------------------------------------------------------
## 122 40 | FOREST ZHANG |3.0 |W 20|L 26|L 39|W 59|L 21|W 56|L 22|
## 123 MI | 14892710 / R: 1348 ->1346 | |B |B |W |W |B |W |W |
## 124 -----------------------------------------------------------------------------------------
## 125 41 | KYLE WILLIAM MURPHY |3.0 |W 59|L 17|W 58|L 20|X |U |U |
## 126 MI | 15761443 / R: 1403P5 ->1341P9 | |B |W |B |W | | | |
## 127 -----------------------------------------------------------------------------------------
## 128 42 | JARED GE |3.0 |L 12|L 50|L 57|D 60|D 61|W 64|W 56|
## 129 MI | 14462326 / R: 1332 ->1256 | |B |W |B |B |W |W |B |
## 130 -----------------------------------------------------------------------------------------
## 131 43 | ROBERT GLEN VASEY |3.0 |L 21|L 23|L 24|W 63|W 59|L 46|W 55|
## 132 MI | 14101068 / R: 1283 ->1244 | |W |B |W |W |B |B |W |
## 133 -----------------------------------------------------------------------------------------
## 134 44 | JUSTIN D SCHILLING |3.0 |B |L 14|L 32|W 53|L 39|L 24|W 59|
## 135 MI | 15323504 / R: 1199 ->1199 | | |W |B |B |W |B |W |
## 136 -----------------------------------------------------------------------------------------
## 137 45 | DEREK YAN |3.0 |L 5|L 51|D 60|L 56|W 63|D 55|W 58|
## 138 MI | 15372807 / R: 1242 ->1191 | |W |B |W |B |W |B |W |
## 139 -----------------------------------------------------------------------------------------
## 140 46 | JACOB ALEXANDER LAVALLEY |3.0 |W 35|L 7|L 27|L 50|W 64|W 43|L 23|
## 141 MI | 15490981 / R: 377P3 ->1076P10 | |B |W |B |W |B |W |W |
## 142 -----------------------------------------------------------------------------------------
## 143 47 | ERIC WRIGHT |2.5 |L 18|W 24|L 21|W 61|L 8|D 51|L 25|
## 144 MI | 12533115 / R: 1362 ->1341 | |W |B |W |B |W |B |W |
## 145 -----------------------------------------------------------------------------------------
## 146 48 | DANIEL KHAIN |2.5 |L 17|W 63|H |D 52|H |L 29|L 35|
## 147 MI | 14369165 / R: 1382 ->1335 | |B |W | |B | |W |B |
## 148 -----------------------------------------------------------------------------------------
## 149 49 | MICHAEL J MARTIN |2.5 |L 26|L 20|D 63|D 64|W 58|H |U |
## 150 MI | 12531685 / R: 1291P12->1259P17 | |W |W |B |W |B | | |
## 151 -----------------------------------------------------------------------------------------
## 152 50 | SHIVAM JHA |2.5 |L 29|W 42|L 33|W 46|H |L 31|L 30|
## 153 MI | 14773178 / R: 1056 ->1111 | |W |B |W |B | |B |W |
## 154 -----------------------------------------------------------------------------------------
## 155 51 | TEJAS AYYAGARI |2.5 |L 27|W 45|L 36|W 57|L 32|D 47|L 33|
## 156 MI | 15205474 / R: 1011 ->1097 | |B |W |B |W |B |W |W |
## 157 -----------------------------------------------------------------------------------------
## 158 52 | ETHAN GUO |2.5 |W 30|D 22|L 19|D 48|L 29|D 35|L 34|
## 159 MI | 14918803 / R: 935 ->1092 |N:4 |B |W |B |W |B |W |B |
## 160 -----------------------------------------------------------------------------------------
## 161 53 | JOSE C YBARRA |2.0 |H |L 25|H |L 44|U |W 57|U |
## 162 MI | 12578849 / R: 1393 ->1359 | | |B | |W | |W | |
## 163 -----------------------------------------------------------------------------------------
## 164 54 | LARRY HODGE |2.0 |L 14|L 39|L 61|B |L 15|L 59|W 64|
## 165 MI | 12836773 / R: 1270 ->1200 | |B |B |W | |W |B |W |
## 166 -----------------------------------------------------------------------------------------
## 167 55 | ALEX KONG |2.0 |L 62|D 31|L 10|L 30|B |D 45|L 43|
## 168 MI | 15412571 / R: 1186 ->1163 | |W |B |W |B | |W |B |
## 169 -----------------------------------------------------------------------------------------
## 170 56 | MARISA RICCI |2.0 |H |L 11|L 35|W 45|H |L 40|L 42|
## 171 MI | 14679887 / R: 1153 ->1140 | | |B |W |W | |B |W |
## 172 -----------------------------------------------------------------------------------------
## 173 57 | MICHAEL LU |2.0 |L 7|L 36|W 42|L 51|L 35|L 53|B |
## 174 MI | 15113330 / R: 1092 ->1079 | |B |W |W |B |W |B | |
## 175 -----------------------------------------------------------------------------------------
## 176 58 | VIRAJ MOHILE |2.0 |W 31|L 2|L 41|L 23|L 49|B |L 45|
## 177 MI | 14700365 / R: 917 -> 941 | |W |B |W |B |W | |B |
## 178 -----------------------------------------------------------------------------------------
## 179 59 | SEAN M MC CORMICK |2.0 |L 41|B |L 9|L 40|L 43|W 54|L 44|
## 180 MI | 12841036 / R: 853 -> 878 | |W | |B |B |W |W |B |
## 181 -----------------------------------------------------------------------------------------
## 182 60 | JULIA SHEN |1.5 |L 33|L 34|D 45|D 42|L 24|H |U |
## 183 MI | 14579262 / R: 967 -> 984 | |W |B |B |W |B | | |
## 184 -----------------------------------------------------------------------------------------
## 185 61 | JEZZEL FARKAS |1.5 |L 32|L 3|W 54|L 47|D 42|L 30|L 37|
## 186 ON | 15771592 / R: 955P11-> 979P18 | |B |W |B |W |B |W |B |
## 187 -----------------------------------------------------------------------------------------
## 188 62 | ASHWIN BALAJI |1.0 |W 55|U |U |U |U |U |U |
## 189 MI | 15219542 / R: 1530 ->1535 | |B | | | | | | |
## 190 -----------------------------------------------------------------------------------------
## 191 63 | THOMAS JOSEPH HOSMER |1.0 |L 2|L 48|D 49|L 43|L 45|H |U |
## 192 MI | 15057092 / R: 1175 ->1125 | |W |B |W |B |B | | |
## 193 -----------------------------------------------------------------------------------------
## 194 64 | BEN LI |1.0 |L 22|D 30|L 31|D 49|L 46|L 42|L 54|
## 195 MI | 15006561 / R: 1163 ->1112 | |B |W |W |B |W |B |B |
## 196 -----------------------------------------------------------------------------------------is(chess_raw)## [1] "data.frame" "list" "oldClass" "vector"library(stringr)playernames <- data.frame(str_extract_all(chess_raw, "[[:upper:]]{3,} [[:upper:]]{1,} [[:upper:]]{0,}[ -][[:upper:]]{0,}"), stringsAsFactors=FALSE)
playernamesfmt <- data.frame(lapply(playernames, function(x) paste(x, ",")), stringsAsFactors=FALSE)
names(playernamesfmt) <- "PlayerName"
playernamesfmt## PlayerName
## 1 GARY HUA ,
## 2 DAKSHESH DARURI ,
## 3 ADITYA BAJAJ ,
## 4 PATRICK H SCHILLING ,
## 5 HANSHI ZUO ,
## 6 HANSEN SONG ,
## 7 GARY DEE SWATHELL ,
## 8 EZEKIEL HOUGHTON ,
## 9 STEFANO LEE ,
## 10 ANVIT RAO ,
## 11 CAMERON WILLIAM MC LEMAN ,
## 12 KENNETH J TACK ,
## 13 TORRANCE HENRY JR ,
## 14 BRADLEY SHAW ,
## 15 ZACHARY JAMES HOUGHTON ,
## 16 MIKE NIKITIN ,
## 17 RONALD GRZEGORCZYK ,
## 18 DAVID SUNDEEN ,
## 19 DIPANKAR ROY ,
## 20 JASON ZHENG ,
## 21 DINH DANG BUI ,
## 22 EUGENE L MCCLURE ,
## 23 ALAN BUI ,
## 24 MICHAEL R ALDRICH ,
## 25 LOREN SCHWIEBERT ,
## 26 MAX ZHU ,
## 27 GAURAV GIDWANI ,
## 28 SOFIA ADINA STANESCU-BELLU ,
## 29 CHIEDOZIE OKORIE ,
## 30 GEORGE AVERY JONES ,
## 31 RISHI SHETTY ,
## 32 JOSHUA PHILIP MATHEWS ,
## 33 JADE GE ,
## 34 MICHAEL JEFFERY THOMAS ,
## 35 JOSHUA DAVID LEE ,
## 36 SIDDHARTH JHA ,
## 37 AMIYATOSH PWNANANDAM ,
## 38 BRIAN LIU ,
## 39 JOEL R HENDON ,
## 40 FOREST ZHANG ,
## 41 KYLE WILLIAM MURPHY ,
## 42 JARED GE ,
## 43 ROBERT GLEN VASEY ,
## 44 JUSTIN D SCHILLING ,
## 45 DEREK YAN ,
## 46 JACOB ALEXANDER LAVALLEY ,
## 47 ERIC WRIGHT ,
## 48 DANIEL KHAIN ,
## 49 MICHAEL J MARTIN ,
## 50 SHIVAM JHA ,
## 51 TEJAS AYYAGARI ,
## 52 ETHAN GUO ,
## 53 JOSE C YBARRA ,
## 54 LARRY HODGE ,
## 55 ALEX KONG ,
## 56 MARISA RICCI ,
## 57 MICHAEL LU ,
## 58 VIRAJ MOHILE ,
## 59 SEAN M MC CORMICK ,
## 60 JULIA SHEN ,
## 61 JEZZEL FARKAS ,
## 62 ASHWIN BALAJI ,
## 63 THOMAS JOSEPH HOSMER ,
## 64 BEN LI ,playerstates <- str_extract_all(chess_raw, "[[:upper:]]{2} \\|")
playerstatesfmt <- data.frame(str_extract_all(playerstates, "[[:alpha:]]{2}"), stringsAsFactors=FALSE)
playerstatesfmt2 <- data.frame(lapply(playerstatesfmt, function(x) paste(x, ",")), stringsAsFactors=FALSE)
names(playerstatesfmt2) <- "PlayerState"
playerstatesfmt2## PlayerState
## 1 ON ,
## 2 MI ,
## 3 MI ,
## 4 MI ,
## 5 MI ,
## 6 OH ,
## 7 MI ,
## 8 MI ,
## 9 ON ,
## 10 MI ,
## 11 MI ,
## 12 MI ,
## 13 MI ,
## 14 MI ,
## 15 MI ,
## 16 MI ,
## 17 MI ,
## 18 MI ,
## 19 MI ,
## 20 MI ,
## 21 ON ,
## 22 MI ,
## 23 ON ,
## 24 MI ,
## 25 MI ,
## 26 ON ,
## 27 MI ,
## 28 MI ,
## 29 MI ,
## 30 ON ,
## 31 MI ,
## 32 ON ,
## 33 MI ,
## 34 MI ,
## 35 MI ,
## 36 MI ,
## 37 MI ,
## 38 MI ,
## 39 MI ,
## 40 MI ,
## 41 MI ,
## 42 MI ,
## 43 MI ,
## 44 MI ,
## 45 MI ,
## 46 MI ,
## 47 MI ,
## 48 MI ,
## 49 MI ,
## 50 MI ,
## 51 MI ,
## 52 MI ,
## 53 MI ,
## 54 MI ,
## 55 MI ,
## 56 MI ,
## 57 MI ,
## 58 MI ,
## 59 MI ,
## 60 MI ,
## 61 ON ,
## 62 MI ,
## 63 MI ,
## 64 MI ,playerpoints <- data.frame(str_extract_all(chess_raw, "[0-9]\\.[0-9]"), stringsAsFactors=FALSE)
playerpointsfmt <- data.frame(lapply(playerpoints, function(x) paste(x, ",")), stringsAsFactors=FALSE)
names(playerpointsfmt) <- "PlayerPoints"
playerpointsfmt## PlayerPoints
## 1 6.0 ,
## 2 6.0 ,
## 3 6.0 ,
## 4 5.5 ,
## 5 5.5 ,
## 6 5.0 ,
## 7 5.0 ,
## 8 5.0 ,
## 9 5.0 ,
## 10 5.0 ,
## 11 4.5 ,
## 12 4.5 ,
## 13 4.5 ,
## 14 4.5 ,
## 15 4.5 ,
## 16 4.0 ,
## 17 4.0 ,
## 18 4.0 ,
## 19 4.0 ,
## 20 4.0 ,
## 21 4.0 ,
## 22 4.0 ,
## 23 4.0 ,
## 24 4.0 ,
## 25 3.5 ,
## 26 3.5 ,
## 27 3.5 ,
## 28 3.5 ,
## 29 3.5 ,
## 30 3.5 ,
## 31 3.5 ,
## 32 3.5 ,
## 33 3.5 ,
## 34 3.5 ,
## 35 3.5 ,
## 36 3.5 ,
## 37 3.5 ,
## 38 3.0 ,
## 39 3.0 ,
## 40 3.0 ,
## 41 3.0 ,
## 42 3.0 ,
## 43 3.0 ,
## 44 3.0 ,
## 45 3.0 ,
## 46 3.0 ,
## 47 2.5 ,
## 48 2.5 ,
## 49 2.5 ,
## 50 2.5 ,
## 51 2.5 ,
## 52 2.5 ,
## 53 2.0 ,
## 54 2.0 ,
## 55 2.0 ,
## 56 2.0 ,
## 57 2.0 ,
## 58 2.0 ,
## 59 2.0 ,
## 60 1.5 ,
## 61 1.5 ,
## 62 1.0 ,
## 63 1.0 ,
## 64 1.0 ,playerprerating <- str_extract_all(chess_raw, "R:[[:space:]]{1,}[[:alnum:]]{3,}[[:space:]]{0,}")
playerpreratingfmt <- data.frame(str_extract_all(playerprerating, " [[:alnum:]]{3,}"), stringsAsFactors=FALSE)
playerpreratingfmt2 <- data.frame(lapply(playerpreratingfmt, function(x) paste(x, ",")), stringsAsFactors=FALSE)
names(playerpreratingfmt2) <- "PlayerPreRating"
playerpreratingfmt2## PlayerPreRating
## 1 1794 ,
## 2 1553 ,
## 3 1384 ,
## 4 1716 ,
## 5 1655 ,
## 6 1686 ,
## 7 1649 ,
## 8 1641P17 ,
## 9 1411 ,
## 10 1365 ,
## 11 1712 ,
## 12 1663 ,
## 13 1666 ,
## 14 1610 ,
## 15 1220P13 ,
## 16 1604 ,
## 17 1629 ,
## 18 1600 ,
## 19 1564 ,
## 20 1595 ,
## 21 1563P22 ,
## 22 1555 ,
## 23 1363 ,
## 24 1229 ,
## 25 1745 ,
## 26 1579 ,
## 27 1552 ,
## 28 1507 ,
## 29 1602P6 ,
## 30 1522 ,
## 31 1494 ,
## 32 1441 ,
## 33 1449 ,
## 34 1399 ,
## 35 1438 ,
## 36 1355 ,
## 37 980P12 ,
## 38 1423 ,
## 39 1436P23 ,
## 40 1348 ,
## 41 1403P5 ,
## 42 1332 ,
## 43 1283 ,
## 44 1199 ,
## 45 1242 ,
## 46 377P3 ,
## 47 1362 ,
## 48 1382 ,
## 49 1291P12 ,
## 50 1056 ,
## 51 1011 ,
## 52 935 ,
## 53 1393 ,
## 54 1270 ,
## 55 1186 ,
## 56 1153 ,
## 57 1092 ,
## 58 917 ,
## 59 853 ,
## 60 967 ,
## 61 955P11 ,
## 62 1530 ,
## 63 1175 ,
## 64 1163 ,opps <- str_extract_all(chess_raw, "\\|[1-6]\\.[0-5] \\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|")
opps2 <- str_extract_all(opps, "\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|[WDLHUBX][[:print:]]{1,4}\\|")
opps2 <- data.frame(opps2, stringsAsFactors=FALSE)
names(opps2) <- "Opps"
opps3 <- lapply(opps2, function(x) str_extract_all(x, "[[:digit:]]{1,2}"))
opps3## $Opps
## $Opps[[1]]
## [1] "39" "21" "18" "14" "7" "12" "4"
##
## $Opps[[2]]
## [1] "63" "58" "4" "17" "16" "20" "7"
##
## $Opps[[3]]
## [1] "8" "61" "25" "21" "11" "13" "12"
##
## $Opps[[4]]
## [1] "23" "28" "2" "26" "5" "19" "1"
##
## $Opps[[5]]
## [1] "45" "37" "12" "13" "4" "14" "17"
##
## $Opps[[6]]
## [1] "34" "29" "11" "35" "10" "27" "21"
##
## $Opps[[7]]
## [1] "57" "46" "13" "11" "1" "9" "2"
##
## $Opps[[8]]
## [1] "3" "32" "14" "9" "47" "28" "19"
##
## $Opps[[9]]
## [1] "25" "18" "59" "8" "26" "7" "20"
##
## $Opps[[10]]
## [1] "16" "19" "55" "31" "6" "25" "18"
##
## $Opps[[11]]
## [1] "38" "56" "6" "7" "3" "34" "26"
##
## $Opps[[12]]
## [1] "42" "33" "5" "38" "1" "3"
##
## $Opps[[13]]
## [1] "36" "27" "7" "5" "33" "3" "32"
##
## $Opps[[14]]
## [1] "54" "44" "8" "1" "27" "5" "31"
##
## $Opps[[15]]
## [1] "19" "16" "30" "22" "54" "33" "38"
##
## $Opps[[16]]
## [1] "10" "15" "39" "2" "36"
##
## $Opps[[17]]
## [1] "48" "41" "26" "2" "23" "22" "5"
##
## $Opps[[18]]
## [1] "47" "9" "1" "32" "19" "38" "10"
##
## $Opps[[19]]
## [1] "15" "10" "52" "28" "18" "4" "8"
##
## $Opps[[20]]
## [1] "40" "49" "23" "41" "28" "2" "9"
##
## $Opps[[21]]
## [1] "43" "1" "47" "3" "40" "39" "6"
##
## $Opps[[22]]
## [1] "64" "52" "28" "15" "17" "40"
##
## $Opps[[23]]
## [1] "4" "43" "20" "58" "17" "37" "46"
##
## $Opps[[24]]
## [1] "28" "47" "43" "25" "60" "44" "39"
##
## $Opps[[25]]
## [1] "9" "53" "3" "24" "34" "10" "47"
##
## $Opps[[26]]
## [1] "49" "40" "17" "4" "9" "32" "11"
##
## $Opps[[27]]
## [1] "51" "13" "46" "37" "14" "6"
##
## $Opps[[28]]
## [1] "24" "4" "22" "19" "20" "8" "36"
##
## $Opps[[29]]
## [1] "50" "6" "38" "34" "52" "48"
##
## $Opps[[30]]
## [1] "52" "64" "15" "55" "31" "61" "50"
##
## $Opps[[31]]
## [1] "58" "55" "64" "10" "30" "50" "14"
##
## $Opps[[32]]
## [1] "61" "8" "44" "18" "51" "26" "13"
##
## $Opps[[33]]
## [1] "60" "12" "50" "36" "13" "15" "51"
##
## $Opps[[34]]
## [1] "6" "60" "37" "29" "25" "11" "52"
##
## $Opps[[35]]
## [1] "46" "38" "56" "6" "57" "52" "48"
##
## $Opps[[36]]
## [1] "13" "57" "51" "33" "16" "28"
##
## $Opps[[37]]
## [1] "5" "34" "27" "23" "61"
##
## $Opps[[38]]
## [1] "11" "35" "29" "12" "18" "15"
##
## $Opps[[39]]
## [1] "1" "54" "40" "16" "44" "21" "24"
##
## $Opps[[40]]
## [1] "20" "26" "39" "59" "21" "56" "22"
##
## $Opps[[41]]
## [1] "59" "17" "58" "20"
##
## $Opps[[42]]
## [1] "12" "50" "57" "60" "61" "64" "56"
##
## $Opps[[43]]
## [1] "21" "23" "24" "63" "59" "46" "55"
##
## $Opps[[44]]
## [1] "14" "32" "53" "39" "24" "59"
##
## $Opps[[45]]
## [1] "5" "51" "60" "56" "63" "55" "58"
##
## $Opps[[46]]
## [1] "35" "7" "27" "50" "64" "43" "23"
##
## $Opps[[47]]
## [1] "18" "24" "21" "61" "8" "51" "25"
##
## $Opps[[48]]
## [1] "17" "63" "52" "29" "35"
##
## $Opps[[49]]
## [1] "26" "20" "63" "64" "58"
##
## $Opps[[50]]
## [1] "29" "42" "33" "46" "31" "30"
##
## $Opps[[51]]
## [1] "27" "45" "36" "57" "32" "47" "33"
##
## $Opps[[52]]
## [1] "30" "22" "19" "48" "29" "35" "34"
##
## $Opps[[53]]
## [1] "25" "44" "57"
##
## $Opps[[54]]
## [1] "14" "39" "61" "15" "59" "64"
##
## $Opps[[55]]
## [1] "62" "31" "10" "30" "45" "43"
##
## $Opps[[56]]
## [1] "11" "35" "45" "40" "42"
##
## $Opps[[57]]
## [1] "7" "36" "42" "51" "35" "53"
##
## $Opps[[58]]
## [1] "31" "2" "41" "23" "49" "45"
##
## $Opps[[59]]
## [1] "41" "9" "40" "43" "54" "44"
##
## $Opps[[60]]
## [1] "33" "34" "45" "42" "24"
##
## $Opps[[61]]
## [1] "32" "3" "54" "47" "42" "30" "37"
##
## $Opps[[62]]
## [1] "55"
##
## $Opps[[63]]
## [1] "2" "48" "49" "43" "45"
##
## $Opps[[64]]
## [1] "22" "30" "31" "49" "46" "42" "54"plyrpreratcalc <- data.frame(str_extract_all(playerprerating, " [[:digit:]]{3,}"), stringsAsFactors=FALSE)
plyrpreratcalcfmt <- data.frame(cbind(c(1:64), plyrpreratcalc))
names(plyrpreratcalcfmt) <- c("Player", "PlayerPreRating")
plyrpreratcalcfmt$PlayerPreRating <- as.numeric(plyrpreratcalcfmt$PlayerPreRating)
plyrpreratcalcfmt## Player PlayerPreRating
## 1 1 1794
## 2 2 1553
## 3 3 1384
## 4 4 1716
## 5 5 1655
## 6 6 1686
## 7 7 1649
## 8 8 1641
## 9 9 1411
## 10 10 1365
## 11 11 1712
## 12 12 1663
## 13 13 1666
## 14 14 1610
## 15 15 1220
## 16 16 1604
## 17 17 1629
## 18 18 1600
## 19 19 1564
## 20 20 1595
## 21 21 1563
## 22 22 1555
## 23 23 1363
## 24 24 1229
## 25 25 1745
## 26 26 1579
## 27 27 1552
## 28 28 1507
## 29 29 1602
## 30 30 1522
## 31 31 1494
## 32 32 1441
## 33 33 1449
## 34 34 1399
## 35 35 1438
## 36 36 1355
## 37 37 980
## 38 38 1423
## 39 39 1436
## 40 40 1348
## 41 41 1403
## 42 42 1332
## 43 43 1283
## 44 44 1199
## 45 45 1242
## 46 46 377
## 47 47 1362
## 48 48 1382
## 49 49 1291
## 50 50 1056
## 51 51 1011
## 52 52 935
## 53 53 1393
## 54 54 1270
## 55 55 1186
## 56 56 1153
## 57 57 1092
## 58 58 917
## 59 59 853
## 60 60 967
## 61 61 955
## 62 62 1530
## 63 63 1175
## 64 64 1163opps5 <- c(0,0)
for(i in 1:64){
opps4 <- data.frame(cbind(i, as.numeric(opps3$Opps[[i]])))
opps5 <- rbind(opps5, opps4)
}
names(opps5) <- c("Player", "Opps")
opps5 <- opps5[-1,]
opps5## Player Opps
## 2 1 39
## 3 1 21
## 4 1 18
## 5 1 14
## 6 1 7
## 7 1 12
## 8 1 4
## 9 2 63
## 10 2 58
## 11 2 4
## 12 2 17
## 13 2 16
## 14 2 20
## 15 2 7
## 16 3 8
## 17 3 61
## 18 3 25
## 19 3 21
## 20 3 11
## 21 3 13
## 22 3 12
## 23 4 23
## 24 4 28
## 25 4 2
## 26 4 26
## 27 4 5
## 28 4 19
## 29 4 1
## 30 5 45
## 31 5 37
## 32 5 12
## 33 5 13
## 34 5 4
## 35 5 14
## 36 5 17
## 37 6 34
## 38 6 29
## 39 6 11
## 40 6 35
## 41 6 10
## 42 6 27
## 43 6 21
## 44 7 57
## 45 7 46
## 46 7 13
## 47 7 11
## 48 7 1
## 49 7 9
## 50 7 2
## 51 8 3
## 52 8 32
## 53 8 14
## 54 8 9
## 55 8 47
## 56 8 28
## 57 8 19
## 58 9 25
## 59 9 18
## 60 9 59
## 61 9 8
## 62 9 26
## 63 9 7
## 64 9 20
## 65 10 16
## 66 10 19
## 67 10 55
## 68 10 31
## 69 10 6
## 70 10 25
## 71 10 18
## 72 11 38
## 73 11 56
## 74 11 6
## 75 11 7
## 76 11 3
## 77 11 34
## 78 11 26
## 79 12 42
## 80 12 33
## 81 12 5
## 82 12 38
## 83 12 1
## 84 12 3
## 85 13 36
## 86 13 27
## 87 13 7
## 88 13 5
## 89 13 33
## 90 13 3
## 91 13 32
## 92 14 54
## 93 14 44
## 94 14 8
## 95 14 1
## 96 14 27
## 97 14 5
## 98 14 31
## 99 15 19
## 100 15 16
## 101 15 30
## 102 15 22
## 103 15 54
## 104 15 33
## 105 15 38
## 106 16 10
## 107 16 15
## 108 16 39
## 109 16 2
## 110 16 36
## 111 17 48
## 112 17 41
## 113 17 26
## 114 17 2
## 115 17 23
## 116 17 22
## 117 17 5
## 118 18 47
## 119 18 9
## 120 18 1
## 121 18 32
## 122 18 19
## 123 18 38
## 124 18 10
## 125 19 15
## 126 19 10
## 127 19 52
## 128 19 28
## 129 19 18
## 130 19 4
## 131 19 8
## 132 20 40
## 133 20 49
## 134 20 23
## 135 20 41
## 136 20 28
## 137 20 2
## 138 20 9
## 139 21 43
## 140 21 1
## 141 21 47
## 142 21 3
## 143 21 40
## 144 21 39
## 145 21 6
## 146 22 64
## 147 22 52
## 148 22 28
## 149 22 15
## 150 22 17
## 151 22 40
## 152 23 4
## 153 23 43
## 154 23 20
## 155 23 58
## 156 23 17
## 157 23 37
## 158 23 46
## 159 24 28
## 160 24 47
## 161 24 43
## 162 24 25
## 163 24 60
## 164 24 44
## 165 24 39
## 166 25 9
## 167 25 53
## 168 25 3
## 169 25 24
## 170 25 34
## 171 25 10
## 172 25 47
## 173 26 49
## 174 26 40
## 175 26 17
## 176 26 4
## 177 26 9
## 178 26 32
## 179 26 11
## 180 27 51
## 181 27 13
## 182 27 46
## 183 27 37
## 184 27 14
## 185 27 6
## 186 28 24
## 187 28 4
## 188 28 22
## 189 28 19
## 190 28 20
## 191 28 8
## 192 28 36
## 193 29 50
## 194 29 6
## 195 29 38
## 196 29 34
## 197 29 52
## 198 29 48
## 199 30 52
## 200 30 64
## 201 30 15
## 202 30 55
## 203 30 31
## 204 30 61
## 205 30 50
## 206 31 58
## 207 31 55
## 208 31 64
## 209 31 10
## 210 31 30
## 211 31 50
## 212 31 14
## 213 32 61
## 214 32 8
## 215 32 44
## 216 32 18
## 217 32 51
## 218 32 26
## 219 32 13
## 220 33 60
## 221 33 12
## 222 33 50
## 223 33 36
## 224 33 13
## 225 33 15
## 226 33 51
## 227 34 6
## 228 34 60
## 229 34 37
## 230 34 29
## 231 34 25
## 232 34 11
## 233 34 52
## 234 35 46
## 235 35 38
## 236 35 56
## 237 35 6
## 238 35 57
## 239 35 52
## 240 35 48
## 241 36 13
## 242 36 57
## 243 36 51
## 244 36 33
## 245 36 16
## 246 36 28
## 247 37 5
## 248 37 34
## 249 37 27
## 250 37 23
## 251 37 61
## 252 38 11
## 253 38 35
## 254 38 29
## 255 38 12
## 256 38 18
## 257 38 15
## 258 39 1
## 259 39 54
## 260 39 40
## 261 39 16
## 262 39 44
## 263 39 21
## 264 39 24
## 265 40 20
## 266 40 26
## 267 40 39
## 268 40 59
## 269 40 21
## 270 40 56
## 271 40 22
## 272 41 59
## 273 41 17
## 274 41 58
## 275 41 20
## 276 42 12
## 277 42 50
## 278 42 57
## 279 42 60
## 280 42 61
## 281 42 64
## 282 42 56
## 283 43 21
## 284 43 23
## 285 43 24
## 286 43 63
## 287 43 59
## 288 43 46
## 289 43 55
## 290 44 14
## 291 44 32
## 292 44 53
## 293 44 39
## 294 44 24
## 295 44 59
## 296 45 5
## 297 45 51
## 298 45 60
## 299 45 56
## 300 45 63
## 301 45 55
## 302 45 58
## 303 46 35
## 304 46 7
## 305 46 27
## 306 46 50
## 307 46 64
## 308 46 43
## 309 46 23
## 310 47 18
## 311 47 24
## 312 47 21
## 313 47 61
## 314 47 8
## 315 47 51
## 316 47 25
## 317 48 17
## 318 48 63
## 319 48 52
## 320 48 29
## 321 48 35
## 322 49 26
## 323 49 20
## 324 49 63
## 325 49 64
## 326 49 58
## 327 50 29
## 328 50 42
## 329 50 33
## 330 50 46
## 331 50 31
## 332 50 30
## 333 51 27
## 334 51 45
## 335 51 36
## 336 51 57
## 337 51 32
## 338 51 47
## 339 51 33
## 340 52 30
## 341 52 22
## 342 52 19
## 343 52 48
## 344 52 29
## 345 52 35
## 346 52 34
## 347 53 25
## 348 53 44
## 349 53 57
## 350 54 14
## 351 54 39
## 352 54 61
## 353 54 15
## 354 54 59
## 355 54 64
## 356 55 62
## 357 55 31
## 358 55 10
## 359 55 30
## 360 55 45
## 361 55 43
## 362 56 11
## 363 56 35
## 364 56 45
## 365 56 40
## 366 56 42
## 367 57 7
## 368 57 36
## 369 57 42
## 370 57 51
## 371 57 35
## 372 57 53
## 373 58 31
## 374 58 2
## 375 58 41
## 376 58 23
## 377 58 49
## 378 58 45
## 379 59 41
## 380 59 9
## 381 59 40
## 382 59 43
## 383 59 54
## 384 59 44
## 385 60 33
## 386 60 34
## 387 60 45
## 388 60 42
## 389 60 24
## 390 61 32
## 391 61 3
## 392 61 54
## 393 61 47
## 394 61 42
## 395 61 30
## 396 61 37
## 397 62 55
## 398 63 2
## 399 63 48
## 400 63 49
## 401 63 43
## 402 63 45
## 403 64 22
## 404 64 30
## 405 64 31
## 406 64 49
## 407 64 46
## 408 64 42
## 409 64 54library(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, unionopps6 <- opps5 %>% left_join(plyrpreratcalcfmt, by = c("Opps" = "Player"))
opps6## Player Opps PlayerPreRating
## 1 1 39 1436
## 2 1 21 1563
## 3 1 18 1600
## 4 1 14 1610
## 5 1 7 1649
## 6 1 12 1663
## 7 1 4 1716
## 8 2 63 1175
## 9 2 58 917
## 10 2 4 1716
## 11 2 17 1629
## 12 2 16 1604
## 13 2 20 1595
## 14 2 7 1649
## 15 3 8 1641
## 16 3 61 955
## 17 3 25 1745
## 18 3 21 1563
## 19 3 11 1712
## 20 3 13 1666
## 21 3 12 1663
## 22 4 23 1363
## 23 4 28 1507
## 24 4 2 1553
## 25 4 26 1579
## 26 4 5 1655
## 27 4 19 1564
## 28 4 1 1794
## 29 5 45 1242
## 30 5 37 980
## 31 5 12 1663
## 32 5 13 1666
## 33 5 4 1716
## 34 5 14 1610
## 35 5 17 1629
## 36 6 34 1399
## 37 6 29 1602
## 38 6 11 1712
## 39 6 35 1438
## 40 6 10 1365
## 41 6 27 1552
## 42 6 21 1563
## 43 7 57 1092
## 44 7 46 377
## 45 7 13 1666
## 46 7 11 1712
## 47 7 1 1794
## 48 7 9 1411
## 49 7 2 1553
## 50 8 3 1384
## 51 8 32 1441
## 52 8 14 1610
## 53 8 9 1411
## 54 8 47 1362
## 55 8 28 1507
## 56 8 19 1564
## 57 9 25 1745
## 58 9 18 1600
## 59 9 59 853
## 60 9 8 1641
## 61 9 26 1579
## 62 9 7 1649
## 63 9 20 1595
## 64 10 16 1604
## 65 10 19 1564
## 66 10 55 1186
## 67 10 31 1494
## 68 10 6 1686
## 69 10 25 1745
## 70 10 18 1600
## 71 11 38 1423
## 72 11 56 1153
## 73 11 6 1686
## 74 11 7 1649
## 75 11 3 1384
## 76 11 34 1399
## 77 11 26 1579
## 78 12 42 1332
## 79 12 33 1449
## 80 12 5 1655
## 81 12 38 1423
## 82 12 1 1794
## 83 12 3 1384
## 84 13 36 1355
## 85 13 27 1552
## 86 13 7 1649
## 87 13 5 1655
## 88 13 33 1449
## 89 13 3 1384
## 90 13 32 1441
## 91 14 54 1270
## 92 14 44 1199
## 93 14 8 1641
## 94 14 1 1794
## 95 14 27 1552
## 96 14 5 1655
## 97 14 31 1494
## 98 15 19 1564
## 99 15 16 1604
## 100 15 30 1522
## 101 15 22 1555
## 102 15 54 1270
## 103 15 33 1449
## 104 15 38 1423
## 105 16 10 1365
## 106 16 15 1220
## 107 16 39 1436
## 108 16 2 1553
## 109 16 36 1355
## 110 17 48 1382
## 111 17 41 1403
## 112 17 26 1579
## 113 17 2 1553
## 114 17 23 1363
## 115 17 22 1555
## 116 17 5 1655
## 117 18 47 1362
## 118 18 9 1411
## 119 18 1 1794
## 120 18 32 1441
## 121 18 19 1564
## 122 18 38 1423
## 123 18 10 1365
## 124 19 15 1220
## 125 19 10 1365
## 126 19 52 935
## 127 19 28 1507
## 128 19 18 1600
## 129 19 4 1716
## 130 19 8 1641
## 131 20 40 1348
## 132 20 49 1291
## 133 20 23 1363
## 134 20 41 1403
## 135 20 28 1507
## 136 20 2 1553
## 137 20 9 1411
## 138 21 43 1283
## 139 21 1 1794
## 140 21 47 1362
## 141 21 3 1384
## 142 21 40 1348
## 143 21 39 1436
## 144 21 6 1686
## 145 22 64 1163
## 146 22 52 935
## 147 22 28 1507
## 148 22 15 1220
## 149 22 17 1629
## 150 22 40 1348
## 151 23 4 1716
## 152 23 43 1283
## 153 23 20 1595
## 154 23 58 917
## 155 23 17 1629
## 156 23 37 980
## 157 23 46 377
## 158 24 28 1507
## 159 24 47 1362
## 160 24 43 1283
## 161 24 25 1745
## 162 24 60 967
## 163 24 44 1199
## 164 24 39 1436
## 165 25 9 1411
## 166 25 53 1393
## 167 25 3 1384
## 168 25 24 1229
## 169 25 34 1399
## 170 25 10 1365
## 171 25 47 1362
## 172 26 49 1291
## 173 26 40 1348
## 174 26 17 1629
## 175 26 4 1716
## 176 26 9 1411
## 177 26 32 1441
## 178 26 11 1712
## 179 27 51 1011
## 180 27 13 1666
## 181 27 46 377
## 182 27 37 980
## 183 27 14 1610
## 184 27 6 1686
## 185 28 24 1229
## 186 28 4 1716
## 187 28 22 1555
## 188 28 19 1564
## 189 28 20 1595
## 190 28 8 1641
## 191 28 36 1355
## 192 29 50 1056
## 193 29 6 1686
## 194 29 38 1423
## 195 29 34 1399
## 196 29 52 935
## 197 29 48 1382
## 198 30 52 935
## 199 30 64 1163
## 200 30 15 1220
## 201 30 55 1186
## 202 30 31 1494
## 203 30 61 955
## 204 30 50 1056
## 205 31 58 917
## 206 31 55 1186
## 207 31 64 1163
## 208 31 10 1365
## 209 31 30 1522
## 210 31 50 1056
## 211 31 14 1610
## 212 32 61 955
## 213 32 8 1641
## 214 32 44 1199
## 215 32 18 1600
## 216 32 51 1011
## 217 32 26 1579
## 218 32 13 1666
## 219 33 60 967
## 220 33 12 1663
## 221 33 50 1056
## 222 33 36 1355
## 223 33 13 1666
## 224 33 15 1220
## 225 33 51 1011
## 226 34 6 1686
## 227 34 60 967
## 228 34 37 980
## 229 34 29 1602
## 230 34 25 1745
## 231 34 11 1712
## 232 34 52 935
## 233 35 46 377
## 234 35 38 1423
## 235 35 56 1153
## 236 35 6 1686
## 237 35 57 1092
## 238 35 52 935
## 239 35 48 1382
## 240 36 13 1666
## 241 36 57 1092
## 242 36 51 1011
## 243 36 33 1449
## 244 36 16 1604
## 245 36 28 1507
## 246 37 5 1655
## 247 37 34 1399
## 248 37 27 1552
## 249 37 23 1363
## 250 37 61 955
## 251 38 11 1712
## 252 38 35 1438
## 253 38 29 1602
## 254 38 12 1663
## 255 38 18 1600
## 256 38 15 1220
## 257 39 1 1794
## 258 39 54 1270
## 259 39 40 1348
## 260 39 16 1604
## 261 39 44 1199
## 262 39 21 1563
## 263 39 24 1229
## 264 40 20 1595
## 265 40 26 1579
## 266 40 39 1436
## 267 40 59 853
## 268 40 21 1563
## 269 40 56 1153
## 270 40 22 1555
## 271 41 59 853
## 272 41 17 1629
## 273 41 58 917
## 274 41 20 1595
## 275 42 12 1663
## 276 42 50 1056
## 277 42 57 1092
## 278 42 60 967
## 279 42 61 955
## 280 42 64 1163
## 281 42 56 1153
## 282 43 21 1563
## 283 43 23 1363
## 284 43 24 1229
## 285 43 63 1175
## 286 43 59 853
## 287 43 46 377
## 288 43 55 1186
## 289 44 14 1610
## 290 44 32 1441
## 291 44 53 1393
## 292 44 39 1436
## 293 44 24 1229
## 294 44 59 853
## 295 45 5 1655
## 296 45 51 1011
## 297 45 60 967
## 298 45 56 1153
## 299 45 63 1175
## 300 45 55 1186
## 301 45 58 917
## 302 46 35 1438
## 303 46 7 1649
## 304 46 27 1552
## 305 46 50 1056
## 306 46 64 1163
## 307 46 43 1283
## 308 46 23 1363
## 309 47 18 1600
## 310 47 24 1229
## 311 47 21 1563
## 312 47 61 955
## 313 47 8 1641
## 314 47 51 1011
## 315 47 25 1745
## 316 48 17 1629
## 317 48 63 1175
## 318 48 52 935
## 319 48 29 1602
## 320 48 35 1438
## 321 49 26 1579
## 322 49 20 1595
## 323 49 63 1175
## 324 49 64 1163
## 325 49 58 917
## 326 50 29 1602
## 327 50 42 1332
## 328 50 33 1449
## 329 50 46 377
## 330 50 31 1494
## 331 50 30 1522
## 332 51 27 1552
## 333 51 45 1242
## 334 51 36 1355
## 335 51 57 1092
## 336 51 32 1441
## 337 51 47 1362
## 338 51 33 1449
## 339 52 30 1522
## 340 52 22 1555
## 341 52 19 1564
## 342 52 48 1382
## 343 52 29 1602
## 344 52 35 1438
## 345 52 34 1399
## 346 53 25 1745
## 347 53 44 1199
## 348 53 57 1092
## 349 54 14 1610
## 350 54 39 1436
## 351 54 61 955
## 352 54 15 1220
## 353 54 59 853
## 354 54 64 1163
## 355 55 62 1530
## 356 55 31 1494
## 357 55 10 1365
## 358 55 30 1522
## 359 55 45 1242
## 360 55 43 1283
## 361 56 11 1712
## 362 56 35 1438
## 363 56 45 1242
## 364 56 40 1348
## 365 56 42 1332
## 366 57 7 1649
## 367 57 36 1355
## 368 57 42 1332
## 369 57 51 1011
## 370 57 35 1438
## 371 57 53 1393
## 372 58 31 1494
## 373 58 2 1553
## 374 58 41 1403
## 375 58 23 1363
## 376 58 49 1291
## 377 58 45 1242
## 378 59 41 1403
## 379 59 9 1411
## 380 59 40 1348
## 381 59 43 1283
## 382 59 54 1270
## 383 59 44 1199
## 384 60 33 1449
## 385 60 34 1399
## 386 60 45 1242
## 387 60 42 1332
## 388 60 24 1229
## 389 61 32 1441
## 390 61 3 1384
## 391 61 54 1270
## 392 61 47 1362
## 393 61 42 1332
## 394 61 30 1522
## 395 61 37 980
## 396 62 55 1186
## 397 63 2 1553
## 398 63 48 1382
## 399 63 49 1291
## 400 63 43 1283
## 401 63 45 1242
## 402 64 22 1555
## 403 64 30 1522
## 404 64 31 1494
## 405 64 49 1291
## 406 64 46 377
## 407 64 42 1332
## 408 64 54 1270oppsavgprerating <- summarise(group_by(opps6,Player), mean(PlayerPreRating))
names(oppsavgprerating) <- c("Player", "OppsAvgPreRating")
oppsavgpreratingfmt <- oppsavgprerating[,-1]
oppsavgpreratingfmt## # A tibble: 64 x 1
## OppsAvgPreRating
## <dbl>
## 1 1605.
## 2 1469.
## 3 1564.
## 4 1574.
## 5 1501.
## 6 1519.
## 7 1372.
## 8 1468.
## 9 1523.
## 10 1554.
## # ... with 54 more rowsplayer_df <- cbind(playernamesfmt, playerstatesfmt2, playerpointsfmt, playerpreratingfmt2, oppsavgpreratingfmt)
str(player_df)## 'data.frame': 64 obs. of 5 variables:
## $ PlayerName : chr "GARY HUA ," "DAKSHESH DARURI ," "ADITYA BAJAJ ," "PATRICK H SCHILLING ," ...
## $ PlayerState : chr "ON ," "MI ," "MI ," "MI ," ...
## $ PlayerPoints : chr "6.0 ," "6.0 ," "6.0 ," "5.5 ," ...
## $ PlayerPreRating : chr " 1794 ," " 1553 ," " 1384 ," " 1716 ," ...
## $ OppsAvgPreRating: num 1605 1469 1564 1574 1501 ...head(player_df,1)## PlayerName PlayerState PlayerPoints PlayerPreRating OppsAvgPreRating
## 1 GARY HUA , ON , 6.0 , 1794 , 1605.286player_df## PlayerName PlayerState PlayerPoints PlayerPreRating
## 1 GARY HUA , ON , 6.0 , 1794 ,
## 2 DAKSHESH DARURI , MI , 6.0 , 1553 ,
## 3 ADITYA BAJAJ , MI , 6.0 , 1384 ,
## 4 PATRICK H SCHILLING , MI , 5.5 , 1716 ,
## 5 HANSHI ZUO , MI , 5.5 , 1655 ,
## 6 HANSEN SONG , OH , 5.0 , 1686 ,
## 7 GARY DEE SWATHELL , MI , 5.0 , 1649 ,
## 8 EZEKIEL HOUGHTON , MI , 5.0 , 1641P17 ,
## 9 STEFANO LEE , ON , 5.0 , 1411 ,
## 10 ANVIT RAO , MI , 5.0 , 1365 ,
## 11 CAMERON WILLIAM MC LEMAN , MI , 4.5 , 1712 ,
## 12 KENNETH J TACK , MI , 4.5 , 1663 ,
## 13 TORRANCE HENRY JR , MI , 4.5 , 1666 ,
## 14 BRADLEY SHAW , MI , 4.5 , 1610 ,
## 15 ZACHARY JAMES HOUGHTON , MI , 4.5 , 1220P13 ,
## 16 MIKE NIKITIN , MI , 4.0 , 1604 ,
## 17 RONALD GRZEGORCZYK , MI , 4.0 , 1629 ,
## 18 DAVID SUNDEEN , MI , 4.0 , 1600 ,
## 19 DIPANKAR ROY , MI , 4.0 , 1564 ,
## 20 JASON ZHENG , MI , 4.0 , 1595 ,
## 21 DINH DANG BUI , ON , 4.0 , 1563P22 ,
## 22 EUGENE L MCCLURE , MI , 4.0 , 1555 ,
## 23 ALAN BUI , ON , 4.0 , 1363 ,
## 24 MICHAEL R ALDRICH , MI , 4.0 , 1229 ,
## 25 LOREN SCHWIEBERT , MI , 3.5 , 1745 ,
## 26 MAX ZHU , ON , 3.5 , 1579 ,
## 27 GAURAV GIDWANI , MI , 3.5 , 1552 ,
## 28 SOFIA ADINA STANESCU-BELLU , MI , 3.5 , 1507 ,
## 29 CHIEDOZIE OKORIE , MI , 3.5 , 1602P6 ,
## 30 GEORGE AVERY JONES , ON , 3.5 , 1522 ,
## 31 RISHI SHETTY , MI , 3.5 , 1494 ,
## 32 JOSHUA PHILIP MATHEWS , ON , 3.5 , 1441 ,
## 33 JADE GE , MI , 3.5 , 1449 ,
## 34 MICHAEL JEFFERY THOMAS , MI , 3.5 , 1399 ,
## 35 JOSHUA DAVID LEE , MI , 3.5 , 1438 ,
## 36 SIDDHARTH JHA , MI , 3.5 , 1355 ,
## 37 AMIYATOSH PWNANANDAM , MI , 3.5 , 980P12 ,
## 38 BRIAN LIU , MI , 3.0 , 1423 ,
## 39 JOEL R HENDON , MI , 3.0 , 1436P23 ,
## 40 FOREST ZHANG , MI , 3.0 , 1348 ,
## 41 KYLE WILLIAM MURPHY , MI , 3.0 , 1403P5 ,
## 42 JARED GE , MI , 3.0 , 1332 ,
## 43 ROBERT GLEN VASEY , MI , 3.0 , 1283 ,
## 44 JUSTIN D SCHILLING , MI , 3.0 , 1199 ,
## 45 DEREK YAN , MI , 3.0 , 1242 ,
## 46 JACOB ALEXANDER LAVALLEY , MI , 3.0 , 377P3 ,
## 47 ERIC WRIGHT , MI , 2.5 , 1362 ,
## 48 DANIEL KHAIN , MI , 2.5 , 1382 ,
## 49 MICHAEL J MARTIN , MI , 2.5 , 1291P12 ,
## 50 SHIVAM JHA , MI , 2.5 , 1056 ,
## 51 TEJAS AYYAGARI , MI , 2.5 , 1011 ,
## 52 ETHAN GUO , MI , 2.5 , 935 ,
## 53 JOSE C YBARRA , MI , 2.0 , 1393 ,
## 54 LARRY HODGE , MI , 2.0 , 1270 ,
## 55 ALEX KONG , MI , 2.0 , 1186 ,
## 56 MARISA RICCI , MI , 2.0 , 1153 ,
## 57 MICHAEL LU , MI , 2.0 , 1092 ,
## 58 VIRAJ MOHILE , MI , 2.0 , 917 ,
## 59 SEAN M MC CORMICK , MI , 2.0 , 853 ,
## 60 JULIA SHEN , MI , 1.5 , 967 ,
## 61 JEZZEL FARKAS , ON , 1.5 , 955P11 ,
## 62 ASHWIN BALAJI , MI , 1.0 , 1530 ,
## 63 THOMAS JOSEPH HOSMER , MI , 1.0 , 1175 ,
## 64 BEN LI , MI , 1.0 , 1163 ,
## OppsAvgPreRating
## 1 1605.286
## 2 1469.286
## 3 1563.571
## 4 1573.571
## 5 1500.857
## 6 1518.714
## 7 1372.143
## 8 1468.429
## 9 1523.143
## 10 1554.143
## 11 1467.571
## 12 1506.167
## 13 1497.857
## 14 1515.000
## 15 1483.857
## 16 1385.800
## 17 1498.571
## 18 1480.000
## 19 1426.286
## 20 1410.857
## 21 1470.429
## 22 1300.333
## 23 1213.857
## 24 1357.000
## 25 1363.286
## 26 1506.857
## 27 1221.667
## 28 1522.143
## 29 1313.500
## 30 1144.143
## 31 1259.857
## 32 1378.714
## 33 1276.857
## 34 1375.286
## 35 1149.714
## 36 1388.167
## 37 1384.800
## 38 1539.167
## 39 1429.571
## 40 1390.571
## 41 1248.500
## 42 1149.857
## 43 1106.571
## 44 1327.000
## 45 1152.000
## 46 1357.714
## 47 1392.000
## 48 1355.800
## 49 1285.800
## 50 1296.000
## 51 1356.143
## 52 1494.571
## 53 1345.333
## 54 1206.167
## 55 1406.000
## 56 1414.400
## 57 1363.000
## 58 1391.000
## 59 1319.000
## 60 1330.200
## 61 1327.286
## 62 1186.000
## 63 1350.200
## 64 1263.000setwd("C:/DATA/HHP/Personal/Degrees/Ms. Data Science (CUNY)/R Working Dir")
write.csv(player_df, "ChessPlayerStats.csv", row.names = TRUE)