R中分組數據和數據幀之間的數學運算

Question

我在這里放置了與上述問題相對應的 2 個數據框的簡化集，如下所示：

ss <- structure(list(country = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L), .Label = c("a", "b", "c", 
"d", "e", "f", "g", "h", "k", "v"), class = "factor"), year = c(1961L, 
1962L, 1963L, 1961L, 1962L, 1963L, 1961L, 1962L, 1963L, 1961L, 
1962L, 1963L, 1961L, 1962L, 1963L, 1961L, 1962L, 1963L, 1961L, 
1962L, 1963L, 1961L, 1962L, 1963L, 1961L, 1962L, 1963L, 1961L, 
1962L, 1963L), x = c(19L, 4L, 3L, 23L, 24L, 16L, 28L, 9L, 29L, 
20L, 14L, 21L, 30L, 1L, 12L, 17L, 25L, 26L, 13L, 8L, 2L, 7L, 
10L, 11L, 6L, 22L, 27L, 5L, 15L, 18L), y = c(23L, 20L, 28L, 7L, 
4L, 25L, 5L, 8L, 10L, 13L, 9L, 1L, 21L, 11L, 26L, 16L, 27L, 2L, 
29L, 24L, 3L, 15L, 6L, 19L, 14L, 22L, 12L, 18L, 17L, 30L), z = c(22L, 
4L, 23L, 16L, 29L, 14L, 11L, 13L, 27L, 26L, 5L, 12L, 2L, 9L, 
10L, 25L, 7L, 21L, 6L, 20L, 3L, 30L, 18L, 8L, 1L, 24L, 17L, 15L, 
28L, 19L)), class = "data.frame", row.names = c(NA, -30L))

和

zz <- structure(list(country = structure(c(1L, 1L, 1L), .Label = "w", class = "factor"), 
    year = 1961:1963, x = c(2L, 1L, 3L), y = c(3L, 1L, 2L), z = 1:3), class = "data.frame", row.names = c(NA, 
-3L))

數據框ss代表來自 10 個國家/地區 3 年的數據。 並且，數據框zz表示相應年份的世界數據。 是否有任何方法可以應用諸如ss(for each each group as country)/zz類的條件，以便每個國家的值都可以提取為與世界數據的比率。 我的意思是前兩列也應該保留給ss 。

我們可以避免使用dplyr和tidverse來重塑數據，這只能添加更多的編碼行。 謝謝。

Answer 1

使用match 。

cbind(ss[1:2], ss[-(1:2)] / zz[match(ss$year, zz$year), -(1:2)])
#   country year          x         y         z
# 1        a 1961  9.5000000  7.666667 22.000000
# 2        b 1962  4.0000000 20.000000  2.000000
# 3        c 1963  1.0000000 14.000000  7.666667
# 4        d 1961 11.5000000  2.333333 16.000000
# 5        e 1962 24.0000000  4.000000 14.500000
# 6        f 1963  5.3333333 12.500000  4.666667
# 7        g 1961 14.0000000  1.666667 11.000000
# 8        h 1962  9.0000000  8.000000  6.500000
# 9        k 1963  9.6666667  5.000000  9.000000
# 10       v 1961 10.0000000  4.333333 26.000000
# 11       a 1962 14.0000000  9.000000  2.500000
# 12       b 1963  7.0000000  0.500000  4.000000
# 13       c 1961 15.0000000  7.000000  2.000000
# 14       d 1962  1.0000000 11.000000  4.500000
# 15       e 1963  4.0000000 13.000000  3.333333
# 16       f 1961  8.5000000  5.333333 25.000000
# 17       g 1962 25.0000000 27.000000  3.500000
# 18       h 1963  8.6666667  1.000000  7.000000
# 19       k 1961  6.5000000  9.666667  6.000000
# 20       v 1962  8.0000000 24.000000 10.000000
# 21       a 1963  0.6666667  1.500000  1.000000
# 22       b 1961  3.5000000  5.000000 30.000000
# 23       c 1962 10.0000000  6.000000  9.000000
# 24       d 1963  3.6666667  9.500000  2.666667
# 25       e 1961  3.0000000  4.666667  1.000000
# 26       f 1962 22.0000000 22.000000 12.000000
# 27       g 1963  9.0000000  6.000000  5.666667
# 28       h 1961  2.5000000  6.000000 15.000000
# 29       k 1962 15.0000000 17.000000 14.000000
# 30       v 1963  6.0000000 15.000000  6.333333

Answer 2

這也可以使用包含data.table包來完成：

as.data.table(ss)[zz, .(country, year, x = x/i.x, y = y/i.y, z = z/i.z), on = .(year)]
#     country year          x         y         z
#  1:       a 1961  9.5000000  7.666667 22.000000
#  2:       d 1961 11.5000000  2.333333 16.000000
#  3:       g 1961 14.0000000  1.666667 11.000000
#  4:       v 1961 10.0000000  4.333333 26.000000
#  5:       c 1961 15.0000000  7.000000  2.000000
#  6:       f 1961  8.5000000  5.333333 25.000000
#  7:       k 1961  6.5000000  9.666667  6.000000
#  8:       b 1961  3.5000000  5.000000 30.000000
#  9:       e 1961  3.0000000  4.666667  1.000000
# 10:       h 1961  2.5000000  6.000000 15.000000
# 11:       b 1962  4.0000000 20.000000  2.000000
# 12:       e 1962 24.0000000  4.000000 14.500000
# 13:       h 1962  9.0000000  8.000000  6.500000
# 14:       a 1962 14.0000000  9.000000  2.500000
# 15:       d 1962  1.0000000 11.000000  4.500000
# 16:       g 1962 25.0000000 27.000000  3.500000
# 17:       v 1962  8.0000000 24.000000 10.000000
# 18:       c 1962 10.0000000  6.000000  9.000000
# 19:       f 1962 22.0000000 22.000000 12.000000
# 20:       k 1962 15.0000000 17.000000 14.000000
# 21:       c 1963  1.0000000 14.000000  7.666667
# 22:       f 1963  5.3333333 12.500000  4.666667
# 23:       k 1963  9.6666667  5.000000  9.000000
# 24:       b 1963  7.0000000  0.500000  4.000000
# 25:       e 1963  4.0000000 13.000000  3.333333
# 26:       h 1963  8.6666667  1.000000  7.000000
# 27:       a 1963  0.6666667  1.500000  1.000000
# 28:       d 1963  3.6666667  9.500000  2.666667
# 29:       g 1963  9.0000000  6.000000  5.666667
# 30:       v 1963  6.0000000 15.000000  6.333333
#     country year          x         y         z