我有一个看起来像这样的data.frame：
gvs order labels color
1 -2.3321916 1 Adygei 1
13 -0.8519079 2 Basque 1
46 -0.9298674 3 French 1
47 -2.8859587 4 Italian 1
2 -1.4996229 5 Orcadian 1
9 -1.5597359 6 Russian 1
48 -1.4494841 7 Sardinian 1
14 -2.4279528 8 Tuscan 1
15 -3.1717421 9 Bedouin 2
22 -0.5058627 10 Druze 2
39 -2.6491331 11 Mozabite 2
23 -0.7819299 12 Palestinian 2
24 -1.4095947 13 Balochi 3
10 -1.2534511 14 Brahui 3
3 1.7958170 15 Burusho 3
25 2.2810477 16 Hazara 3
16 -0.9258497 17 Kalash 3
26 -0.9007551 18 Makrani 3
4 2.5543214 19 Pathan 3
27 2.6614486 20 Sindhi 3
17 -1.2207974 21 Uygurf 3
40 2.3706977 22 Cambodian 4
28 -0.9441980 23 Dai 4
18 -1.0325107 24 Daur 4
49 -0.7381369 25 Han 4
41 -2.7590587 26 Hezhen 4
50 -0.5644325 27 Japanese 4
44 -0.8449225 28 Lahu 4
29 -0.7237586 29 Miao 4
30 -0.9452944 30 Mongola 4
11 -0.1625003 31 Naxi 4
31 -1.2035258 32 Oroqen 4
5 -2.7758460 33 She 4
32 -0.7703779 34 Tu 4
12 -1.0265275 35 Tujia 4
45 -1.1163019 36 Xibo 4
19 -3.2102686 37 Yakut 4
42 -0.9614190 38 Yi 4
6 -1.9659984 39 Colombian 5
51 -0.9195156 40 Karitiana 5
7 2.1239768 41 Maya 5
33 -3.0895998 42 Pima 5
20 -0.9377928 43 Surui 5
43 -1.6961014 44 Melanesian 6
34 -0.7037952 45 Papuan 6
35 -1.9311354 46 BantuKenya 7
8 -1.8515908 47 BantuSouthAfrica 7
21 -1.7657017 48 BiakaPygmy 7
36 -0.5423822 49 Mandenka 7
37 -1.6244801 50 MbutiPygmy 7
38 -0.9049735 51 San 7
52 2.0949378 52 Yoruba 7
我有另一个data.frame2，如下所示：
labels pvals
Adygei Adygei 0.914
Balochi Balochi 0.158
BantuKenya BantuKenya 0.484
BantuSouthAfrica BantuSouthAfrica 0.016
Basque Basque 0.218
Bedouin Bedouin 0.914
BiakaPygmy BiakaPygmy 0.538
Brahui Brahui 0.162
Burusho Burusho 0.414
Cambodian Cambodian 0.118
Colombian Colombian 0.166
Dai Dai 0.686
Daur Daur 0.932
Druze Druze 0.220
French French 0.000
Han Han 0.794
Hazara Hazara 0.152
Hezhen Hezhen 0.182
Italian Italian 0.024
Japanese Japanese 0.366
Kalash Kalash 0.974
Karitiana Karitiana 0.660
Lahu Lahu 0.560
Makrani Makrani 0.226
Mandenka Mandenka 0.076
Maya Maya 0.818
MbutiPygmy MbutiPygmy 0.054
Melanesian Melanesian 0.414
Miao Miao 0.194
Mongola Mongola 0.768
Mozabite Mozabite 0.200
Naxi Naxi 0.554
Orcadian Orcadian 0.148
Oroqen Oroqen 0.782
Palestinian Palestinian 0.552
Papuan Papuan 0.386
Pathan Pathan 0.112
Pima Pima 0.818
Russian Russian 0.626
San San 0.478
Sardinian Sardinian 0.516
She She 0.912
Sindhi Sindhi 0.338
Surui Surui 0.536
Tu Tu 0.254
Tujia Tujia 0.912
Tuscan Tuscan 0.420
Uygur Uygur 0.652
Xibo Xibo 0.292
Yakut Yakut 0.030
Yi Yi 0.838
Yoruba Yoruba 0.904
我想在原始data.frame中添加pvals列，添加与正确填充对应的pval，而不更改输出的顺序。 IE，我希望我的输出仍然有标签顺序：Adygei，巴斯克语，法语，意大利语......等等。有谁知道怎么做？我已经尝试了merge()，但它似乎按字母顺序重新组织了labels。
答案 0 :(得分：1)
另一种方式（使用plyr包的连接）
col s5 m5 l5答案 1 :(得分：0)
您可以直接使用match
df1$pvals <- df2$pvals[match(df1$labels, df2$labels)]