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有人要求我更清楚地说明不同的问题，因此它们位于顶部:
原文如下:
我正在学习 R 来对运动进行一些纸上谈兵的分析。现在，我遇到了一个问题，我有一份 NFL 赛季每场比赛的 list ，我正在尝试计算这场比赛前几周的 AvgTotalYds 进攻情况。最终，我希望能够计算本赛季至今的平均值，以及过去 X 个时期的移动平均值。
更复杂的是，我还想获得有关一周前对手的相同信息。我搜索了很多类似的问题，但找不到任何解决方案。
以下是数据示例。给我的数据库有一些不幸的列名。 ScoreOff 实际上是指球队在 TeamName 字段中的总得分，无论是进攻、防守还是特殊球队的比赛。 *Def 同样指的是对手。代码示例使用标记为“df2”的数据框。
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")
我添加了 TotalYds[Off|Def] 列，因为这样做很简单。最接近正确计算移动平均线的事情是通过 zoo 和 plyr 库以及以下命令完成的:
ddply(df2, .(TeamName), summarise, rollmean(TotalYdsOff, k=4, fill=0, align="right"))
几乎 做我想做的，只是它会平均使用当前一周的信息。
就获取对手的匹配信息而言，我认为有一种方法可以从“TeamName”和“Date”都与当前行的“Opponent”匹配的行中提取相同的数据“日期。”这是因为数据库在给定的比赛中有两个条目，一个是主队，一个是客队(*Off 和 *Def 被交换了)。查看示例数据中的第 1 行和第 2 行，特别是 Date、TeamName 和 Opponent，您就会明白我想说的是什么。
这里有什么指导吗？我想这对于在 R 中修修补补了几天的人来说是相对微不足道的，他们会知道执行此操作的某些函数或库。然而，我才来几天，因此遇到了一些麻烦。
最佳答案
解决问题 1 的一个简单方法是使用您描述的 ddply 调用，但向它传递一个数据框，其中删除了本周的所有游戏:
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"))
关于r - 尝试计算 R 中的运行队统计数据 - 计算本场比赛前的平均进攻码数以及对手的码数，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/12938867/
25
4
0
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我正在尝试在 MySQL 中添加列并动态填充其他列。 例如我有一张表“数字”并具有第 1 列、第 2 列、第 3 列，这些总数应填充在第 4 列中 最佳答案 除非我误解了你的问题，否则你不只是在寻找:
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如何在 Excel 中将公式放入自定义数字格式？例如(出于说明目的随机示例)， 假设我有以下数据: 输入 输出 在不编辑单元格中的实际数据的情况下，我想显示单元格中的值除以 2，并保留两位小数: 有没
每次我在 Flutter 应用程序中调用计算()时，我都会看到内存泄漏，据我所知，这基本上只是一种生成隔离的便捷方法。我的应用程序内存占用增加并且在 GC 之后永远不会减少。 我已将我的代码简化为仅调
我有数字特征观察 V1通过 V12用于目标变量 Wavelength .我想计算 Vx 之间的 RMSE列。数据格式如下。 每个变量“Vx”以 5 分钟的间隔进行测量。我想计算所有 Vx 变量的观测值
我正在寻找一种使用 C 语言计算文件中未知字符数的简单方法。谢谢你的帮助 最佳答案 POSIX 方式(可能是您想要的方式): off_t get_file_length( FILE *file ) {
我正在使用 Postgres，并且我正试图围绕如何在连续日期跨度中得出第一个开始日期的问题进行思考。例如 :- ID | Start Date | End Date =================
我有一个订单表格，我在其中使用 jQuery 计算插件来汇总总数。 此求和工作正常，但生成的“总和”存在问题。总之，我希望用逗号替换任何点。 代码的基础是； function ($this) {
我在使用 double 变量计算简单算术方程时遇到问题。 我有一个具有 double 属性 Value 的组件，我将此属性设置为 100。 然后我做一个简单的减法来检查这个值是否真的是 100: va
我在这里看到了一些关于 CRC 32 计算的其他问题。但没有一个让我满意，因此是这样。 openssl 库是否有任何用于计算 CRC32 的 api 支持？我已经在为 SHA1 使用 openssl，
当我在PHP日期计算中遇到问题时，我感到惊讶。 $add = '- 30 days'; echo date('Y-m-01', strtotime($add)); // result is 2017-
我正在使用 javascript 进行练习，我编写了这个脚本来计算 2 个变量的总和，然后在第三个方程中使用这个总和!关于如何完成这项工作的任何想法都将非常有用! First Number:
我有一个来自EAC的提示单和一个包含完整专辑的FLAC文件。 我正在尝试制作一些python脚本来播放文件，因为我需要能够设置在flac文件中开始的位置。 如何从CueSheet格式MM:SS:FF转
这个问题已经有答案了: Adding two numbers concatenates them instead of calculating the sum (24 个回答) 已关闭去年。 我有一个
4000 我需要上面字段 name="quantity" 和 id="price" 中的值，并使用 javascript 函数进行计算，并将其显示在字段 id= 中仅当我单击计算按钮时才显示“总
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