1

我有一个如下数据集。

dat1 <- read.table(header=TRUE, text="
ID  Pa  Gu  Ta
8645    Rel345  Gel294  Tel452
6228    Rel345  Gel294  Tel467
5830    Rel345  Gel294  Tel467
1844    Rel345  Gel295  Tel467
4461    Rel345  Gel295  Tel467
2119    Rel345  Gel294  Tel452
1821    Rel345  Gel294  Tel467
6851    Rel345  Gel294  Tel467
4214    Rel345  Gel294  Tel452
2589    Rel346  Gel294  Tel467
2116    Rel347  Gel294  Tel452
8523    Rel348  Gel295  Tel468
2603    Rel348  Gel295  Tel468
2801    Rel348  Gel295  Tel452
1485    Rel348  Gel295  Tel468
2116    Rel348  Gel295  Tel452
8753    Rel348  Gel295  Tel452
4277    Rel348  Gel295  Tel468
7053    Rel348  Gel295  Tel468
3320    Rel348  Gel295  Tel452
7974    Rel348  Gel295  Tel468
                   ")
dat1
     ID      Pa       Gu      Ta
1  8645 Rel_123 Gela_134 Tel_111
2  6228 Rel_123 Gela_134 Tel_112
3  5830 Rel_123 Gela_134 Tel_112
4  1844 Rel_123 Gela_135 Tel_112
5  4461 Rel_123 Gela_135 Tel_112
6  2119 Rel_123 Gela_134 Tel_111
7  1821 Rel_123 Gela_134 Tel_112
8  6851 Rel_123 Gela_134 Tel_112
9  4214 Rel_123 Gela_134 Tel_111
10 2589 Rel_124 Gela_134 Tel_112
11 2116 Rel_125 Gela_134 Tel_111
12 8523 Rel_126 Gela_135 Tel_113
13 2603 Rel_126 Gela_135 Tel_113
14 2801 Rel_126 Gela_135 Tel_111
15 1485 Rel_126 Gela_135 Tel_113
16 2116 Rel_126 Gela_135 Tel_111
17 8753 Rel_126 Gela_135 Tel_111
18 4277 Rel_126 Gela_135 Tel_113
19 7053 Rel_126 Gela_135 Tel_113
20 3320 Rel_126 Gela_135 Tel_111
21 7974 Rel_126 Gela_135 Tel_113

右三列的属性重新编码如下：

dat2 <- read.table(header=TRUE, text="
Att New_Att
Rel345  Rel_123
Rel346  Rel_124
Rel347  Rel_125
Rel348  Rel_126
Gel294  Gela_134
Gel295  Gela_135
Tel452  Tel_111
Tel467  Tel_112
Tel468  Tel_113

                   ")
dat2
     Att  New_Att
1 Rel345  Rel_123
2 Rel346  Rel_124
3 Rel347  Rel_125
4 Rel348  Rel_126
5 Gel294 Gela_134
6 Gel295 Gela_135
7 Tel452  Tel_111
8 Tel467  Tel_112
9 Tel468  Tel_113

使用plyr包（通过使用revalue函数），我可以进行如下更改。

library(plyr)
dat1$Pa<- revalue(dat1$Pa, c("Rel345"="Rel_123","Rel346"="Rel_124","Rel347"="Rel_125",
"Rel348"="Rel_126"))
dat1$Gu<- revalue(dat1$Gu, c("Gel294"="Gela_134","Gel295"="Gela_135"))
dat1$Ta<- revalue(dat1$Ta, c("Tel452"="Tel_111","Tel467"="Tel_112","Tel468"="Tel_113" ))

dat1
     ID      Pa       Gu      Ta
1  8645 Rel_123 Gela_134 Tel_111
2  6228 Rel_123 Gela_134 Tel_112
3  5830 Rel_123 Gela_134 Tel_112
4  1844 Rel_123 Gela_135 Tel_112
5  4461 Rel_123 Gela_135 Tel_112
6  2119 Rel_123 Gela_134 Tel_111
7  1821 Rel_123 Gela_134 Tel_112
8  6851 Rel_123 Gela_134 Tel_112
9  4214 Rel_123 Gela_134 Tel_111
10 2589 Rel_124 Gela_134 Tel_112
11 2116 Rel_125 Gela_134 Tel_111
12 8523 Rel_126 Gela_135 Tel_113
13 2603 Rel_126 Gela_135 Tel_113
14 2801 Rel_126 Gela_135 Tel_111
15 1485 Rel_126 Gela_135 Tel_113
16 2116 Rel_126 Gela_135 Tel_111
17 8753 Rel_126 Gela_135 Tel_111
18 4277 Rel_126 Gela_135 Tel_113
19 7053 Rel_126 Gela_135 Tel_113
20 3320 Rel_126 Gela_135 Tel_111
21 7974 Rel_126 Gela_135 Tel_113

我有一个包含 100 万行的数据集，其中一些变量有 200 多个类别。所以我上面的代码不方便。我想attribute name通过阅读dat2.

4

1 回答 1

1

我们遍历'dat1'的列，除了'ID'列，match'df2'中的'Att'，使用数字索引将列元素替换为'New_Att'的相应元素

dat1[-1] <- lapply(dat1[-1], function(x) dat2$New_Att[match(x, dat2$Att)])

或者我们可以match像以前一样将数据集转换为矩阵。

`dim<-`(dat2[,2][match(as.matrix(dat1[-1]), dat2[,1])], dim(dat1[-1]))
于 2015-11-03T18:48:15.663 回答