r - 使用来自数据帧的数据在矩阵中创建一个向量，该数据以 R 中矩阵中的变量值为条件

Question

这在书面上有点难以解释，我会尽力而为。（这也是我在这里的第一篇文章）。所以，我有这样的数据框“ x ”：

+---+----+----+-----+
|   | A  | B  | C   |
| 1 | 50 | 40 | 30  |
| 2 | 60 | 80 | 40  |
| 3 | 70 | 30 | 20  |
| 4 | 10 | 40 | 100 |
| 5 | 35 | 50 | 20  |
| 6 | 20 | 50 | 30  |
+---+----+----+-----+

还有一个像这样的矩阵“ Y ”：

+---+---+---+---+---+---+
| A | C | C | B | A | A |
| 1 | 5 | 5 | 4 | 3 | 6 |
+---+---+---+---+---+---+

（假设字母是数字，我用字母只是为了更清楚地解释）。现在我希望“R”在“ Y ”矩阵中创建一个新行，根据矩阵第一行和第二行的值从“ X ”数据帧中提取数据。因此，例如，对于矩阵“ Y ”中的第三列，从数据帧中提取的值将是 20。由于第一行的值为“C”，第二行的值为“5”，而在数据框“C”和“5”相交的值为20。所以，基本上我需要'R'" 包含该列的相应值。使用示例表，第三行应如下所示：

+----+----+----+----+----+----+
| A  | C  | C  | B  | A  | A  |
| 1  | 5  | 5  | 4  | 3  | 6  |
| 50 | 20 | 20 | 40 | 70 | 20 |
+----+----+----+----+----+----+

我希望它足够清楚，我认为执行此操作的功能是“子集”，但我真的不知道如何获得所需的结果。感谢您提供的任何帮助。

编辑：以下数据是数据框“ X ”

structure(list(X = structure(c(52L, 1L, 2L, 3L, 4L, 25L, 26L, 
38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 
51L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
18L, 19L, 20L, 21L, 22L, 23L, 24L, 27L, 28L, 29L, 30L, 31L, 32L, 
33L, 34L, 35L, 36L, 37L), .Label = c("0", "0.5", "1", "1.5", 
"10", "10.5", "11", "11.5", "12", "12.5", "13", "13.5", "14", 
"14.5", "15", "15.5", "16", "16.5", "17", "17.5", "18", "18.5", 
"19", "19.5", "2", "2.5", "20", "20.5", "21", "21.5", "22", "22.5", 
"23", "23.5", "24", "24.5", "25", "3", "3.5", "4", "4.5", "5", 
"5.5", "6", "6.5", "7", "7.5", "8", "8.5", "9", "9.5", "v"
), class = "factor"), AD = c(0.9, 0, 0, 0, 0, 0, 0, 
1, 15, 50, 94, 147, 209, 280, 361, 455, 564, 689, 830, 978, 1130, 
1281, 1431, 1579, 1728, 1872, 2011, 2144, 2263, 2353, 2418, 2462, 
2489, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500), X.1 = c(0.925, 
0, 0, 0, 0, 0, 0, 1, 16, 52, 97, 151, 215, 288, 372, 469, 581, 
710, 854, 1006, 1161, 1315, 1467, 1619, 1770, 1915, 2055, 2189, 
2300, 2381, 2439, 2477, 2496, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500), X.2 = c(0.95, 0, 0, 0, 0, 0, 0, 1, 17, 54, 100, 
156, 222, 297, 383, 483, 599, 731, 879, 1034, 1192, 1348, 1503, 
1657, 1810, 1956, 2096, 2230, 2331, 2405, 2455, 2488, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500), X.3 = c(0.975, 0, 
0, 0, 0, 0, 0, 1, 18, 56, 104, 161, 228, 305, 394, 497, 616, 
752, 903, 1061, 1222, 1381, 1539, 1696, 1849, 1996, 2135, 2260, 
2354, 2421, 2465, 2491, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500), X.4 = c(1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 19L, 58L, 
107L, 165L, 234L, 314L, 405L, 511L, 634L, 773L, 929L, 1097L, 
1274L, 1459L, 1649L, 1840L, 2030L, 2199L, 2327L, 2415L, 2470L, 
2495L, 2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 
2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 2500L, 
2500L, 2500L, 2500L, 2500L, 2500L), X.5 = c(1.025, 0, 0, 0, 0, 
0, 0, 1, 20, 60, 110, 170, 241, 322, 416, 525, 651, 795, 953, 
1125, 1307, 1497, 1692, 1889, 2084, 2245, 2362, 2440, 2485, 2499, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500
), X.6 = c(1.05, 0, 0, 0, 0, 0, 0, 1, 21, 62, 113, 175, 247, 
331, 427, 539, 668, 816, 978, 1154, 1340, 1535, 1735, 1937, 2132, 
2284, 2391, 2459, 2494, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500), X.7 = c(1.075, 0, 0, 0, 0, 0, 
0, 1, 22, 64, 116, 179, 254, 339, 438, 553, 685, 836, 1002, 1182, 
1373, 1572, 1778, 1986, 2175, 2316, 2414, 2473, 2497, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500), 
    X.8 = c(1.1, 0, 0, 0, 0, 0, 0, 1, 24, 66, 120, 184, 260, 
    348, 449, 566, 702, 856, 1026, 1211, 1406, 1610, 1821, 2035, 
    2217, 2349, 2437, 2486, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500), X.9 = c(1.125, 
    0, 0, 0, 0, 0, 0, 1, 25, 68, 123, 189, 267, 356, 460, 580, 
    719, 877, 1051, 1239, 1439, 1648, 1864, 2080, 2254, 2377, 
    2455, 2495, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500), X.10 = c(1.15, 0, 0, 
    0, 0, 0, 0, 1, 26, 70, 126, 193, 273, 365, 471, 594, 736, 
    897, 1075, 1267, 1472, 1686, 1908, 2119, 2284, 2397, 2467, 
    2496, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500), X.11 = c(1.175, 0, 0, 0, 0, 
    0, 0, 1, 27, 72, 129, 198, 279, 373, 482, 608, 753, 917, 
    1099, 1295, 1505, 1724, 1952, 2158, 2313, 2418, 2478, 2498, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500), X.12 = c(1.2, 0, 0, 0, 0, 0, 0, 
    1, 28, 74, 132, 203, 286, 382, 493, 622, 770, 937, 1123, 
    1324, 1537, 1761, 1995, 2197, 2343, 2439, 2489, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500), X.13 = c(1.225, 0, 0, 0, 0, 0, 0, 1, 29, 
    76, 136, 207, 292, 390, 504, 635, 787, 958, 1147, 1352, 1570, 
    1799, 2036, 2231, 2368, 2454, 2496, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500), X.14 = c(1.25, 0, 0, 0, 0, 0, 0, 1, 30, 78, 139, 212, 
    298, 399, 515, 649, 803, 978, 1171, 1380, 1603, 1838, 2071, 
    2257, 2386, 2464, 2497, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500), X.15 = c(1.275, 
    0, 0, 0, 0, 0, 0, 1, 31, 80, 142, 217, 305, 407, 525, 662, 
    820, 998, 1195, 1408, 1636, 1877, 2107, 2284, 2404, 2473, 
    2498, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500), X.16 = c(1.3, 0, 0, 
    0, 0, 0, 0, 1, 32, 82, 145, 221, 311, 415, 536, 676, 836, 
    1018, 1219, 1437, 1668, 1915, 2142, 2310, 2423, 2483, 2499, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500, 
    2500, 2500, 2500, 2500, 2500)), .Names = c("X", "AD", 
"X.1", "X.2", "X.3", "X.4", "X.5", "X.6", "X.7", "X.8", "X.9", 
"X.10", "X.11", "X.12", "X.13", "X.14", "X.15", "X.16"), class = "data.frame", row.names = c(NA, 
-52L))

我无法粘贴矩阵“ Y ”中的所有数据，因为它太大了，它是一个 3x1644 矩阵。
这是矩阵“ Y ”的前几列。

structure(list(V1 = structure(1:3, .Label = c("", "AD", "WS"), class = "factor"), 
    V2 = structure(c(3L, 1L, 2L), .Label = c("1.2", "3.5", "V1"
    ), class = "factor"), V3 = structure(c(3L, 1L, 2L), .Label = c("1.2", 
    "4", "V2"), class = "factor"), V4 = structure(c(3L, 1L, 2L
    ), .Label = c("1.2", "3.5", "V3"), class = "factor")), .Names = c("V1", 
"V2", "V3", "V4"), class = "matrix", row.names = c(NA, -3L
))

请注意，当我提取第一列并在此处发布它们时，矩阵变成了一个数据框，但它仍然是我数据中的一个矩阵。

Answer 1

尝试这样的事情：

rbind(Y, sapply(seq_along(Y), 
                function(z) 
                  X[Y[1, z], names(Y)[z]]))
#    A  C  C  B  A  A
# 1  1  5  5  4  3  6
# 2 50 20 20 40 70 20

在这里，我基本上是使用子集[来匹配您正在寻找的值。

---

为了方便其他人，这里是X和Y：

X <- structure(list(A = c(50, 60, 70, 10, 35, 20), 
                    B = c(40, 80, 30, 40, 50, 50), 
                    C = c(30, 40, 20, 100, 20, 30)), 
               .Names = c("A", "B", "C"), 
               row.names = c(NA, -6L), 
               class = "data.frame")
Y <- structure(list(A = 1, C = 5, C = 5, B = 4, A = 3, A = 6), 
               .Names = c("A", "C", "C", "B", "A", "A"), 
               row.names = c(NA, -1L), class = "data.frame")