3

私は明確な問題をより明確にするように求められたので、ここでそれらは一番上にあります：

  • 今週を除く、チームの移動平均を計算する方法
  • 対戦相手チームの同様の統計を含む列を追加する方法

元のテキストは次のとおりです。

私はスポーツのアームチェア分析を行うためにRを学んでいます。現在、NFLシーズンにプレイされたすべてのゲームのリストがあるという問題に悩まされており、このゲームに至るまでの数週間の攻撃のAvgTotalYdsを計算しようとしています。最終的には、過去X期間の移動平均だけでなく、現在までのシーズンの平均も実行できるようにしたいと思います。

さらに複雑なのは、問題の週に至るまでの対戦相手についても同じ情報を取得したいということです。同様の問題をたくさん検索しましたが、解決策が見つかりませんでした。

以下はデータのサンプルです。私が与えられたデータベースには、いくつかの不幸な列名があります。ScoreOffは、実際には、攻撃的、防御的、または特別なチームプレイであるかどうかに関係なく、TeamNameフィールドでチームが獲得した合計ポイントを指します。* Defも同様に、対戦相手を指します。コード例では、「df2」というラベルの付いたデータフレームを使用しています。

dput(head(df2))

structure(list(Date = structure(c(14126, 14126, 14129, 14129, 
14129, 14129), class = "Date"), TeamName = structure(c(21L, 32L, 
1L, 2L, 3L, 4L), .Label = c("Arizona Cardinals", "Atlanta Falcons", 
"Baltimore Ravens", "Buffalo Bills", "Carolina Panthers", "Chicago Bears", 
"Cincinnati Bengals", "Cleveland Browns", "Dallas Cowboys", "Denver Broncos", 
"Detroit Lions", "Green Bay Packers", "Houston Texans", "Indianapolis Colts", 
"Jacksonville Jaguars", "Kansas City Chiefs", "Miami Dolphins", 
"Minnesota Vikings", "New England Patriots", "New Orleans Saints", 
"New York Giants", "New York Jets", "Oakland Raiders", "Philadelphia Eagles", 
"Pittsburgh Steelers", "San Diego Chargers", "San Francisco 49ers", 
"Seattle Seahawks", "St Louis Rams", "Tampa Bay Buccaneers", 
"Tennessee Titans", "Washington Redskins"), class = "factor"), 
    ScoreOff = c(16L, 7L, 23L, 34L, 17L, 34L), FirstDownOff = c(21L, 
    11L, 18L, 23L, 21L, 13L), ThirdDownPctOff = structure(c(34L, 
    14L, 20L, 21L, 35L, 16L), .Label = c("0%", "10%", "11%", 
    "12%", "13%", "14%", "15%", "17%", "18%", "19%", "20%", "21%", 
    "22%", "23%", "24%", "25%", "27%", "29%", "30%", "31%", "33%", 
    "35%", "36%", "37%", "38%", "40%", "41%", "42%", "43%", "44%", 
    "45%", "46%", "47%", "50%", "53%", "54%", "55%", "56%", "57%", 
    "58%", "59%", "60%", "61%", "62%", "63%", "64%", "65%", "67%", 
    "69%", "73%", "77%", "8%", "80%", "9%", "92%"), class = "factor"), 
    RushAttOff = c(32L, 24L, 39L, 42L, 46L, 29L), RushYdsOff = c(154L, 
    84L, 109L, 318L, 229L, 106L), PassAttOff = c(35L, 27L, 30L, 
    13L, 29L, 31L), PassCompOff = c(19L, 15L, 19L, 9L, 15L, 20L
    ), PassYdsOff = c(216L, 133L, 197L, 161L, 129L, 234L), PassIntOff = c(1L, 
    0L, 0L, 0L, 0L, 0L), FumblesOff = c(0L, 0L, 0L, 0L, 2L, 0L
    ), SackYdsOff = c(16L, 8L, 21L, 5L, 0L, 2L), PenYdsOff = c(70L, 
    35L, 40L, 68L, 64L, 14L), TimePossOff = structure(c(348L, 
    52L, 368L, 175L, 354L, 239L), .Label = c("14:45", "18:15", 
    "18:27", "19:31", "19:56", "20:11", "20:12", "20:26", "20:48", 
    "21:03", "21:08", "21:16", "21:26", "21:28", "21:35", "21:44", 
    "21:45", "21:52", "21:54", "22:03", "22:08", "22:12", "22:16", 
    "22:25", "22:30", "22:31", "22:33", "22:34", "22:38", "22:39", 
    "22:53", "22:55", "22:59", "23:09", "23:10", "23:12", "23:15", 
    "23:23", "23:28", "23:30", "23:33", "23:37", "23:38", "23:42", 
    "23:43", "23:45", "23:48", "23:49", "23:56", "24:06", "24:13", 
    "24:17", "24:18", "24:21", "24:33", "24:34", "24:35", "24:41", 
    "24:43", "24:49", "24:50", "24:54", "24:58", "24:59", "25:01", 
    "25:02", "25:05", "25:11", "25:14", "25:16", "25:19", "25:25", 
    "25:29", "25:31", "25:32", "25:34", "25:36", "25:37", "25:38", 
    "25:40", "25:41", "25:46", "25:47", "25:53", "25:55", "25:57", 
    "25:58", "26:00", "26:04", "26:09", "26:10", "26:11", "26:12", 
    "26:13", "26:16", "26:20", "26:27", "26:32", "26:36", "26:37", 
    "26:38", "26:39", "26:40", "26:41", "26:44", "26:46", "26:49", 
    "26:53", "26:56", "26:59", "27:01", "27:04", "27:10", "27:12", 
    "27:13", "27:15", "27:18", "27:20", "27:24", "27:25", "27:26", 
    "27:27", "27:28", "27:30", "27:32", "27:37", "27:40", "27:44", 
    "27:46", "27:47", "27:48", "27:50", "27:51", "27:52", "27:53", 
    "27:55", "27:57", "27:58", "27:59", "28:00", "28:01", "28:03", 
    "28:05", "28:06", "28:07", "28:13", "28:14", "28:16", "28:17", 
    "28:18", "28:19", "28:21", "28:22", "28:24", "28:25", "28:28", 
    "28:29", "28:32", "28:38", "28:40", "28:41", "28:45", "28:47", 
    "28:49", "28:51", "28:53", "28:55", "28:57", "28:58", "28:59", 
    "29:00", "29:02", "29:04", "29:05", "29:07", "29:08", "29:11", 
    "29:13", "29:14", "29:18", "29:19", "29:20", "29:26", "29:27", 
    "29:29", "29:31", "29:32", "29:33", "29:34", "29:36", "29:37", 
    "29:38", "29:41", "29:42", "29:43", "29:49", "29:50", "29:55", 
    "29:56", "29:59", "30:01", "30:04", "30:05", "30:10", "30:11", 
    "30:17", "30:18", "30:19", "30:22", "30:23", "30:24", "30:26", 
    "30:27", "30:28", "30:29", "30:31", "30:33", "30:34", "30:40", 
    "30:41", "30:42", "30:46", "30:47", "30:49", "30:52", "30:53", 
    "30:55", "30:58", "31:00", "31:01", "31:02", "31:03", "31:05", 
    "31:07", "31:09", "31:11", "31:13", "31:15", "31:19", "31:20", 
    "31:22", "31:28", "31:31", "31:32", "31:35", "31:36", "31:38", 
    "31:39", "31:41", "31:42", "31:43", "31:44", "31:46", "31:47", 
    "31:53", "31:54", "31:55", "31:57", "31:59", "32:00", "32:01", 
    "32:02", "32:03", "32:05", "32:07", "32:08", "32:09", "32:10", 
    "32:12", "32:13", "32:14", "32:16", "32:20", "32:23", "32:28", 
    "32:30", "32:32", "32:33", "32:34", "32:35", "32:36", "32:40", 
    "32:42", "32:45", "32:47", "32:48", "32:50", "32:56", "32:59", 
    "33:01", "33:04", "33:07", "33:11", "33:14", "33:16", "33:19", 
    "33:20", "33:21", "33:22", "33:23", "33:24", "33:28", "33:33", 
    "33:40", "33:44", "33:47", "33:48", "33:49", "33:50", "33:51", 
    "33:56", "34:00", "34:02", "34:03", "34:05", "34:07", "34:13", 
    "34:14", "34:19", "34:20", "34:22", "34:23", "34:24", "34:26", 
    "34:28", "34:29", "34:31", "34:35", "34:41", "34:44", "34:46", 
    "34:49", "34:55", "34:58", "34:59", "35:01", "35:02", "35:06", 
    "35:10", "35:11", "35:17", "35:19", "35:25", "35:26", "35:27", 
    "35:39", "35:42", "35:43", "35:47", "35:54", "36:04", "36:11", 
    "36:12", "36:15", "36:17", "36:18", "36:22", "36:23", "36:27", 
    "36:30", "36:32", "36:37", "36:45", "36:48", "36:50", "36:51", 
    "37:01", "37:05", "37:07", "37:21", "37:22", "37:26", "37:27", 
    "37:29", "37:30", "37:35", "37:42", "37:44", "37:48", "37:52", 
    "37:57", "38:08", "38:15", "38:16", "38:23", "38:25", "38:32", 
    "38:34", "38:44", "38:52", "38:57", "39:12", "39:34", "39:48", 
    "39:49", "40:04", "40:29", "41:33", "41:45", "45:15"), class = "factor"), 
    PuntAvgOff = c(36.3, 37.9, 45, 38.3, 48.2, 46.6), Opponent = structure(c(32L, 
    21L, 27L, 11L, 7L, 28L), .Label = c("Arizona Cardinals", 
    "Atlanta Falcons", "Baltimore Ravens", "Buffalo Bills", "Carolina Panthers", 
    "Chicago Bears", "Cincinnati Bengals", "Cleveland Browns", 
    "Dallas Cowboys", "Denver Broncos", "Detroit Lions", "Green Bay Packers", 
    "Houston Texans", "Indianapolis Colts", "Jacksonville Jaguars", 
    "Kansas City Chiefs", "Miami Dolphins", "Minnesota Vikings", 
    "New England Patriots", "New Orleans Saints", "New York Giants", 
    "New York Jets", "Oakland Raiders", "Philadelphia Eagles", 
    "Pittsburgh Steelers", "San Diego Chargers", "San Francisco 49ers", 
    "Seattle Seahawks", "St Louis Rams", "Tampa Bay Buccaneers", 
    "Tennessee Titans", "Washington Redskins"), class = "factor"), 
    ScoreDef = c(7L, 16L, 13L, 21L, 10L, 10L), FirstDownDef = c(11L, 
    21L, 13L, 21L, 8L, 16L), ThirdDownPctDef = structure(c(14L, 
    34L, 25L, 13L, 7L, 10L), .Label = c("0%", "10%", "11%", "12%", 
    "13%", "14%", "15%", "17%", "18%", "19%", "20%", "21%", "22%", 
    "23%", "24%", "25%", "27%", "29%", "30%", "31%", "33%", "35%", 
    "36%", "37%", "38%", "40%", "41%", "42%", "43%", "44%", "45%", 
    "46%", "47%", "50%", "53%", "54%", "55%", "56%", "57%", "58%", 
    "59%", "60%", "61%", "62%", "63%", "64%", "65%", "67%", "69%", 
    "73%", "77%", "8%", "80%", "9%", "92%"), class = "factor"), 
    RushAttDef = c(24L, 32L, 20L, 21L, 23L, 21L), RushYdsDef = c(84L, 
    154L, 108L, 62L, 65L, 85L), PassAttDef = c(27L, 35L, 20L, 
    33L, 25L, 41L), PassCompDef = c(15L, 19L, 14L, 24L, 10L, 
    17L), PassYdsDef = c(133L, 216L, 195L, 262L, 99L, 190L), 
    PassIntDef = c(0L, 1L, 1L, 1L, 1L, 1L), FumblesDef = c(0L, 
    0L, 4L, 0L, 1L, 1L), SackYdsDef = c(8L, 16L, 12L, 16L, 10L, 
    23L), PenYdsDef = c(35L, 70L, 20L, 30L, 40L, 30L), TimePossDef = structure(c(52L, 
    348L, 32L, 225L, 46L, 161L), .Label = c("14:45", "18:15", 
    "18:27", "19:31", "19:56", "20:11", "20:12", "20:26", "20:48", 
    "21:03", "21:08", "21:16", "21:26", "21:28", "21:35", "21:44", 
    "21:45", "21:52", "21:54", "22:03", "22:08", "22:12", "22:16", 
    "22:25", "22:30", "22:31", "22:33", "22:34", "22:38", "22:39", 
    "22:53", "22:55", "22:59", "23:09", "23:10", "23:12", "23:15", 
    "23:23", "23:28", "23:30", "23:33", "23:37", "23:38", "23:42", 
    "23:43", "23:45", "23:48", "23:49", "23:56", "24:06", "24:13", 
    "24:17", "24:18", "24:21", "24:33", "24:34", "24:35", "24:41", 
    "24:43", "24:49", "24:50", "24:54", "24:58", "24:59", "25:01", 
    "25:02", "25:05", "25:11", "25:14", "25:16", "25:19", "25:25", 
    "25:29", "25:31", "25:32", "25:34", "25:36", "25:37", "25:38", 
    "25:40", "25:41", "25:46", "25:47", "25:53", "25:55", "25:57", 
    "25:58", "26:00", "26:04", "26:09", "26:10", "26:11", "26:12", 
    "26:13", "26:16", "26:20", "26:27", "26:32", "26:36", "26:37", 
    "26:38", "26:39", "26:40", "26:41", "26:44", "26:46", "26:49", 
    "26:53", "26:56", "26:59", "27:01", "27:04", "27:10", "27:12", 
    "27:13", "27:15", "27:18", "27:20", "27:24", "27:25", "27:26", 
    "27:27", "27:28", "27:30", "27:32", "27:37", "27:40", "27:44", 
    "27:46", "27:47", "27:48", "27:50", "27:51", "27:52", "27:53", 
    "27:55", "27:57", "27:58", "27:59", "28:00", "28:01", "28:03", 
    "28:05", "28:06", "28:07", "28:13", "28:14", "28:16", "28:17", 
    "28:18", "28:19", "28:21", "28:22", "28:24", "28:25", "28:28", 
    "28:29", "28:32", "28:38", "28:40", "28:41", "28:45", "28:47", 
    "28:49", "28:51", "28:53", "28:55", "28:57", "28:58", "28:59", 
    "29:00", "29:02", "29:05", "29:07", "29:08", "29:11", "29:13", 
    "29:14", "29:18", "29:19", "29:20", "29:26", "29:27", "29:29", 
    "29:31", "29:32", "29:33", "29:34", "29:36", "29:37", "29:38", 
    "29:41", "29:42", "29:43", "29:49", "29:50", "29:55", "29:56", 
    "29:59", "30:01", "30:04", "30:05", "30:10", "30:11", "30:17", 
    "30:18", "30:19", "30:22", "30:23", "30:24", "30:26", "30:27", 
    "30:28", "30:29", "30:31", "30:33", "30:34", "30:40", "30:41", 
    "30:42", "30:46", "30:47", "30:49", "30:52", "30:53", "30:55", 
    "30:56", "30:58", "31:00", "31:01", "31:02", "31:03", "31:05", 
    "31:07", "31:09", "31:11", "31:13", "31:15", "31:19", "31:20", 
    "31:22", "31:28", "31:31", "31:32", "31:35", "31:36", "31:38", 
    "31:39", "31:41", "31:42", "31:43", "31:44", "31:46", "31:47", 
    "31:53", "31:54", "31:55", "31:57", "31:59", "32:00", "32:01", 
    "32:02", "32:03", "32:05", "32:07", "32:08", "32:09", "32:10", 
    "32:12", "32:13", "32:14", "32:16", "32:20", "32:23", "32:28", 
    "32:30", "32:32", "32:33", "32:34", "32:35", "32:36", "32:40", 
    "32:42", "32:45", "32:47", "32:48", "32:50", "32:56", "32:59", 
    "33:01", "33:04", "33:07", "33:11", "33:14", "33:16", "33:19", 
    "33:20", "33:21", "33:22", "33:23", "33:24", "33:28", "33:33", 
    "33:40", "33:44", "33:47", "33:48", "33:49", "33:50", "33:51", 
    "33:56", "34:00", "34:02", "34:03", "34:05", "34:07", "34:13", 
    "34:14", "34:19", "34:20", "34:22", "34:23", "34:24", "34:26", 
    "34:28", "34:29", "34:31", "34:35", "34:41", "34:44", "34:46", 
    "34:49", "34:55", "34:58", "34:59", "35:01", "35:02", "35:06", 
    "35:10", "35:11", "35:17", "35:19", "35:25", "35:26", "35:27", 
    "35:39", "35:42", "35:43", "35:47", "35:54", "36:04", "36:11", 
    "36:12", "36:15", "36:17", "36:18", "36:22", "36:23", "36:27", 
    "36:30", "36:32", "36:37", "36:45", "36:48", "36:50", "36:51", 
    "37:01", "37:05", "37:07", "37:21", "37:22", "37:26", "37:27", 
    "37:29", "37:30", "37:35", "37:42", "37:44", "37:48", "37:52", 
    "37:57", "38:08", "38:15", "38:16", "38:23", "38:25", "38:32", 
    "38:34", "38:44", "38:52", "38:57", "39:12", "39:34", "39:48", 
    "39:49", "40:04", "40:29", "41:33", "41:45", "45:15"), class = "factor"), 
    Site = structure(c(1L, 3L, 3L, 1L, 1L, 1L), .Label = c("H", 
    "N", "V"), class = "factor"), Line = c(4.5, -4.5, 2.5, -3, 
    -2, 1), Totalline = c(41.5, 41.5, 42, 41, 37.5, 38.5), TotalYdsOff = c(370L, 
    217L, 306L, 479L, 358L, 340L), TotalYdsDef = c(217L, 370L, 
    303L, 324L, 164L, 275L), ActualLine = c(-9L, 9L, -10L, -13L, 
    -7L, -24L)), .Names = c("Date", "TeamName", "ScoreOff", "FirstDownOff", 
"ThirdDownPctOff", "RushAttOff", "RushYdsOff", "PassAttOff", 
"PassCompOff", "PassYdsOff", "PassIntOff", "FumblesOff", "SackYdsOff", 
"PenYdsOff", "TimePossOff", "PuntAvgOff", "Opponent", "ScoreDef", 
"FirstDownDef", "ThirdDownPctDef", "RushAttDef", "RushYdsDef", 
"PassAttDef", "PassCompDef", "PassYdsDef", "PassIntDef", "FumblesDef", 
"SackYdsDef", "PenYdsDef", "TimePossDef", "Site", "Line", "Totalline", 
"TotalYdsOff", "TotalYdsDef", "ActualLine"), row.names = c(NA, 
6L), class = "data.frame")

TotalYds [Off | Def]列を追加したのは、簡単なことでした。移動平均を適切に計算するのに最も近いのは、zooライブラリとplyrライブラリ、および次のコマンドを使用した場合です。

ddply(df2, .(TeamName), summarise, rollmean(TotalYdsOff, k=4, fill=0, align="right"))

これは、平均して今週の情報を使用することを除いて、私が望むこと をほぼ実行します。

対戦相手のマッチング情報を取得する限り、「TeamName」と「Date」の両方が現在の行の「Opponent」と「Date」と一致する行から同じデータを引き出す方法があると思いました。 「」これは、データベースに特定のゲームに2つのエントリがあり、1つはホームチーム用、もう1つはアウェイ用であるためです（*Offと*Defが交換されます）。サンプルデータの1行目と2行目、具体的にはDate、TeamName、Opponentを見ると、私が何を言おうとしているのかがわかります。

ここに何かガイダンスはありますか？これは、Rをいじくり回している数日以上の人にとっては比較的些細なことだと思います。この人は、これを行う関数やライブラリを知っているでしょう。しかし、私はまだ数日しか経っていないため、問題が発生しています。

4

2 に答える 2

2

質問1に対処する簡単な方法はddply、説明した呼び出しを使用することですが、今週のすべてのゲームを削除したデータフレームを渡します。

require(plyr)
dfRedacted <- ddply(df2, .(TeamName), function(x) subset(x, Date!=max(Date)))
meanStats <- ddply(dfRedacted, .(TeamName), summarise, rollmean(TotalYdsOff, k=4, fill=0, align="right"))
于 2012-10-17T21:11:09.027 に答える
0

今のところ、特定のゲームまでのシーズン平均を計算する関数を作成し、その結果を別のベクトルに入れてから、cbind（）を使用してデータフレームに追加することになりました。

foo <- vector()
for(each in levels(df$TeamName)) {
  foo <- c(foo, calc_avg_yds(df, each))
}

df <-cbind（df [order（df $ TeamName）、]、AvgTotalYdsOff = foo）

ご覧のとおり、dfをチーム名（セカンダリは日付で、すでに注文されています）で並べ替えて、一致することを確認しました。

対応する行（ゲーム内の他のチームの行）から情報を取得するために、ループを実行してすべてをベクトルに入れ、次に別のcbind（）を配置しました。

for(i in nrow(df)) {
   foo <- c(foo, subset(df, TeamName==df[i,]$Opponent & Date==df[i,]$Date)$AvgTotalYdsOff)
}
df <- cbind(df, AvgTotalYdsDef = foo)

結局、私はより良い代替案を知らなかったので、単純で粗雑なルートを選びました。これが将来、同様の問題を抱えている人に役立つことを願っています。

于 2012-10-18T16:41:25.257 に答える