合并后保持数据框列的属性 [英] Maintain attributes of data frame columns after merge

问题描述

似乎 merge 会导致数据框的列丢失其属性:

It seems that merge causes columns of a data frame to lose their attributes:

attr(mtcars$mpg, "units") <- "miles.per.gallon"
new.df <- data.frame(gear=3:5, my.opinion=c("not enough", "just right", "too many"))
merged.df <- merge(new.df, mtcars)

attr(merged.df$mpg, "units") 返回 NULL.

有没有办法让 merge 保留列的属性?

Is there a way to get merge to preserve attributes of columns?

(一种解决方法是在合并前查询每个数据框的每一列的属性，然后在合并后重新分配它们.但这似乎不雅.)

(A workaround would be to query the attributes of each column of each data frame before the merge, and then to re-assign them after the merge. However that seems inelegant.)

推荐答案

如果您不介意使用 dplyr，这个似乎可行.

If you don't mind using dplyr, this one seems to work.

您的数据:

attr(mtcars$mpg, "units") <- "miles.per.gallon"
new.df <- data.frame(gear=3:5, my.opinion=c("not enough", "just right", "too many"))

> attr(mtcars$mpg, "units")
[1] "miles.per.gallon"

来自 dplyr 的函数 inner_join.

Function inner_join from dplyr.

inner.df<-dplyr::inner_join(new.df, mtcars,"gear")

得到的数据框如下:

> inner.df
    gear my.opinion  mpg cyl  disp  hp drat    wt  qsec vs am carb
1     3 not enough 21.4   6 258.0 110 3.08 3.215 19.44  1  0    1
2     3 not enough 18.7   8 360.0 175 3.15 3.440 17.02  0  0    2
3     3 not enough 18.1   6 225.0 105 2.76 3.460 20.22  1  0    1
4     3 not enough 14.3   8 360.0 245 3.21 3.570 15.84  0  0    4
5     3 not enough 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3
6     3 not enough 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3
7     3 not enough 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3
8     3 not enough 10.4   8 472.0 205 2.93 5.250 17.98  0  0    4
9     3 not enough 10.4   8 460.0 215 3.00 5.424 17.82  0  0    4
10    3 not enough 14.7   8 440.0 230 3.23 5.345 17.42  0  0    4
11    3 not enough 21.5   4 120.1  97 3.70 2.465 20.01  1  0    1
12    3 not enough 15.5   8 318.0 150 2.76 3.520 16.87  0  0    2
13    3 not enough 15.2   8 304.0 150 3.15 3.435 17.30  0  0    2
14    3 not enough 13.3   8 350.0 245 3.73 3.840 15.41  0  0    4
15    3 not enough 19.2   8 400.0 175 3.08 3.845 17.05  0  0    2
16    4 just right 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4
17    4 just right 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4
18    4 just right 22.8   4 108.0  93 3.85 2.320 18.61  1  1    1
19    4 just right 24.4   4 146.7  62 3.69 3.190 20.00  1  0    2
20    4 just right 22.8   4 140.8  95 3.92 3.150 22.90  1  0    2
21    4 just right 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4
22    4 just right 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4
23    4 just right 32.4   4  78.7  66 4.08 2.200 19.47  1  1    1
24    4 just right 30.4   4  75.7  52 4.93 1.615 18.52  1  1    2
25    4 just right 33.9   4  71.1  65 4.22 1.835 19.90  1  1    1
26    4 just right 27.3   4  79.0  66 4.08 1.935 18.90  1  1    1
27    4 just right 21.4   4 121.0 109 4.11 2.780 18.60  1  1    2
28    5   too many 26.0   4 120.3  91 4.43 2.140 16.70  0  1    2
29    5   too many 30.4   4  95.1 113 3.77 1.513 16.90  1  1    2
30    5   too many 15.8   8 351.0 264 4.22 3.170 14.50  0  1    4
31    5   too many 19.7   6 145.0 175 3.62 2.770 15.50  0  1    6
32    5   too many 15.0   8 301.0 335 3.54 3.570 14.60  0  1    8

属性的维护位置:

> attr(inner.df$mpg, "units")
[1] "miles.per.gallon"

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