R，计算最后 3 个平均值
san*_*ins 1 r function moving-average
我在R中有以下数据框。它包含奥运会篮球比赛中每个球员的统计数据样本表
每个游戏都由游戏栏中的数字表示。我想创建一个新列，其中包含最近 3 场比赛的平均值。当遵循类似帖子中的示例时，我最大的失败是使用游戏数字而不是其他方法似乎所需的实际日期。
任何帮助将不胜感激。谢谢
编辑：根据一些解决方案和建议进一步澄清一点。对于每一行，我希望新列显示最近 3 场比赛的平均分钟数或得分。到目前为止，建议让每一行显示第 3、4 和 5 场比赛的平均值。
例如。玩家 A，游戏 = 3 平均分 = 平均值（游戏 1 分，游戏 2 分，游戏 3 分）
玩家 B，游戏 = 4 平均分 = 平均值（游戏 2 分，游戏 3 分，游戏 4 分）
我希望这能解决问题。谢谢
数据：
我对此很陌生。我希望这是共享数据的合适方法。
structure(list(Player = structure(c(1L, 2L, 6L, 8L, 17L, 21L,
23L, 24L, 24L, 24L, 24L, 25L, 26L, 15L, 20L, 20L, 12L, 15L, 11L,
5L, 15L, 16L, 14L, 9L, 20L, 11L, 18L, 4L, 12L, 9L, 4L, 9L, 20L,
12L, 5L, 13L, 22L, 7L, 11L, 20L, 4L, 5L, 10L, 11L, 14L, 19L,
3L, 7L, 14L, 5L), .Label = c("Adas Juskevicius", "Alex Abrines",
"Andrew Bogut", "Bojan Bogdanovic", "Boris Diaw", "Brock Motum",
"Dario Saric", "Dwight Lewis", "Facundo Campazzo", "Ike Diogu",
"Jianlian Yi", "Jonas Maciulis", "Kevin Durant", "Luis Scola",
"Mantas Kalnietis", "Matt Dellavedova", "Miguel Marriaga", "Milos Teodosic",
"Nikola Mirotic", "Pau Gasol", "Rafa Luz", "Ricky Rubio", "Roberto Acuna",
"Vaidas Kariniauskas", "Windi Graterol", "Zeljko Sakic"), class = "factor"),
Team = structure(c(8L, 6L, 2L, 12L, 12L, 3L, 1L, 8L, 8L,
8L, 8L, 12L, 5L, 8L, 6L, 6L, 8L, 8L, 4L, 7L, 8L, 2L, 1L,
1L, 6L, 4L, 10L, 5L, 8L, 1L, 5L, 1L, 6L, 8L, 7L, 11L, 6L,
5L, 4L, 6L, 5L, 7L, 9L, 4L, 1L, 6L, 2L, 5L, 1L, 7L), .Label = c("ARG",
"AUS", "BRZ", "CHN", "CRO", "ESP", "FRA", "LTU", "NGR", "SRB",
"USA", "VEN"), class = "factor"), Pos = structure(c(3L, 4L,
2L, 5L, 2L, 5L, 1L, 2L, 2L, 2L, 2L, 1L, 4L, 3L, 1L, 1L, 4L,
5L, 2L, 2L, 5L, 3L, 2L, 3L, 1L, 4L, 5L, 2L, 2L, 3L, 2L, 3L,
1L, 2L, 2L, 4L, 3L, 4L, 4L, 1L, 2L, 2L, 2L, 4L, 1L, 2L, 1L,
4L, 1L, 2L), .Label = c("C", "PF", "PG", "SF", "SG"), class = "factor"),
game = c(4L, 5L, 4L, 5L, 3L, 4L, 3L, 1L, 2L, 3L, 4L, 5L,
5L, 3L, 2L, 3L, 3L, 4L, 3L, 3L, 2L, 4L, 3L, 3L, 5L, 5L, 5L,
4L, 2L, 2L, 2L, 5L, 4L, 4L, 2L, 2L, 1L, 4L, 4L, 1L, 5L, 4L,
3L, 2L, 4L, 2L, 2L, 3L, 2L, 1L), Status = c(0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), Drafted = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 85,
82, 80, 78, 77, 74, 68, 68, 68, 65, 64, 63, 62, 62, 61, 61,
60, 59, 59, 59, 58, 57, 57, 57, 56, 56, 56, 55, 55, 55, 55,
54, 54, 53, 53, 52, 51), Min = c(11.04, 1.44, 16.56, 2.88,
4.8, 1.92, 13.68, 3.84, 9.36, 2.64, 21.12, 17.04, 0.24, 36.48,
32.16, 23.28, 26.88, 17.28, 33.6, 28.56, 30.48, 19.92, 30.24,
25.92, 27.84, 34.8, 15.12, 36, 28.8, 29.04, 29.28, 21.36,
23.04, 18.72, 21.12, 25.2, 12.24, 27.12, 32.88, 31.92, 34.08,
18.24, 27.6, 32.64, 33.6, 32.88, 24.72, 34.8, 35.76, 31.44
), FIC = c(3.8, 1.5, 10.2, 1, 0, -1, 0.2, 0.5, -3.2, -1,
0.6, 4.5, -0.5, 15.6, 9.5, 11.1, 0.5, 7.8, 17, 16.8, 25.2,
10.5, 10, 6, 14.4, 6, 7.5, 15.5, 14.8, 6.2, 7.9, 3, 26.9,
0.8, 11.4, 16, -1, 4.9, 14.1, 18.5, 5.9, 6.5, 10, 10, 10,
8, 19, 9, 12.1, 7.5), FP = c(8, 4, 21.75, 2, 2.75, -0.5,
4.75, 1.5, 2.5, 1.25, 8.5, 13, 0, 35.25, 37, 32.25, 17, 18.5,
39.5, 34.25, 49, 19.25, 28.75, 20.25, 41.25, 27.5, 16.5,
39.25, 33.5, 29, 30.75, 13.25, 47.25, 9, 24.5, 28.5, 6.25,
19.5, 38.25, 40.25, 27.5, 17, 21.75, 37.5, 29, 21, 38.5,
30.75, 37.75, 25.75), FPM = c(0.72463768115942, 2.77777777777778,
1.31340579710145, 0.694444444444444, 0.572916666666667, -0.260416666666667,
0.347222222222222, 0.390625, 0.267094017094017, 0.473484848484848,
0.402462121212121, 0.762910798122066, 0, 0.966282894736842,
1.15049751243781, 1.38530927835052, 0.632440476190476, 1.07060185185185,
1.17559523809524, 1.19922969187675, 1.60761154855643, 0.96636546184739,
0.950727513227513, 0.78125, 1.48168103448276, 0.790229885057471,
1.09126984126984, 1.09027777777778, 1.16319444444444, 0.99862258953168,
1.05020491803279, 0.620318352059925, 2.05078125, 0.480769230769231,
1.16003787878788, 1.13095238095238, 0.51062091503268, 0.719026548672566,
1.16332116788321, 1.2609649122807, 0.806924882629108, 0.932017543859649,
0.78804347826087, 1.14889705882353, 0.863095238095238, 0.638686131386861,
1.55744336569579, 0.883620689655172, 1.05564876957494, 0.819020356234097
), PTS = c(5L, 2L, 15L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 6L, 9L,
0L, 17L, 13L, 16L, 10L, 16L, 18L, 11L, 21L, 6L, 12L, 10L,
19L, 20L, 7L, 28L, 21L, 10L, 18L, 10L, 23L, 4L, 7L, 16L,
0L, 7L, 20L, 26L, 22L, 10L, 7L, 19L, 14L, 6L, 9L, 15L, 23L,
9L), TPM = c(1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 2L, 0L, 0L, 2L, 2L, 0L, 0L, 1L, 0L, 1L, 2L, 1L, 0L,
1L, 3L, 3L, 1L, 1L, 1L, 5L, 0L, 1L, 2L, 0L, 1L, 2L, 3L, 4L,
0L, 0L, 3L, 2L, 0L, 1L, 3L, 3L, 1L), Ast = c(2L, 0L, 2L,
0L, 1L, 0L, 0L, 1L, 2L, 0L, 1L, 1L, 0L, 7L, 1L, 3L, 1L, 2L,
1L, 9L, 12L, 8L, 4L, 1L, 1L, 2L, 5L, 2L, 2L, 8L, 2L, 1L,
5L, 2L, 5L, 5L, 1L, 0L, 2L, 1L, 1L, 0L, 3L, 0L, 1L, 2L, 6L,
3L, 0L, 2L), Reb = c(0L, 0L, 3L, 0L, 1L, 0L, 1L, 0L, 0L,
1L, 2L, 2L, 0L, 5L, 10L, 7L, 6L, 0L, 10L, 9L, 4L, 1L, 7L,
3L, 13L, 2L, 0L, 3L, 4L, 4L, 7L, 1L, 5L, 0L, 4L, 2L, 1L,
6L, 9L, 9L, 2L, 4L, 7L, 6L, 10L, 8L, 12L, 7L, 9L, 5L), BLK = c(0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 2L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 2L, 2L, 0L, 0L, 1L, 0L, 1L,
0L, 2L, 0L, 3L, 1L, 0L, 1L, 2L, 0L, 0L, 0L, 1L, 1L, 0L, 1L,
3L, 1L, 1L, 2L), STL = c(0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 3L, 0L, 1L, 0L, 1L,
2L, 0L, 0L, 1L, 2L, 1L, 2L, 0L, 0L, 2L, 1L, 0L, 0L, 2L, 2L,
0L, 0L, 1L, 1L, 0L, 4L, 0L, 0L, 0L, 1L, 1L, 2L), TO = c(1L,
0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 3L, 1L, 0L, 3L, 3L, 2L,
6L, 3L, 0L, 3L, 2L, 0L, 1L, 0L, 3L, 4L, 1L, 2L, 2L, 5L, 3L,
0L, 0L, 0L, 3L, 1L, 1L, 3L, 2L, 0L, 5L, 0L, 1L, 1L, 3L, 0L,
2L, 6L, 4L, 2L)), .Names = c("Player", "Team", "Pos", "game",
"Status", "Drafted", "Min", "FIC", "FP", "FPM", "PTS", "TPM",
"Ast", "Reb", "BLK", "STL", "TO"), row.names = c(NA, 50L), class = "data.frame")
将 dplyr 与 mtcars 示例数据结合使用：
\n\nlibrary(dplyr)\n\nmtcars %>% \n group_by(cyl) %>% \n mutate(last3mean = mean(tail(mpg, 3))) \n在您的情况下，请使用Player和列来聚合，而不是cyl和mpg 。
\n\n使用 data.table（由@akrun建议）：
\n\ndata.table as.data.table(mtcar\xe2\x80\x8c\xe2\x80\x8bs)[, .(last3mean = mean(tail(mpg,3))), by = cyl]\n