我有 4 个具有以下结构的数据框:
数据1:
1.8064 2.2016 2.4506 2.1828 2.1171 1.9308 2.1707 2.1885
2.2310 2.2400 1.9115 2.1527 2.0934 1.7989 2.2144 2.0091
1.9248 2.2038 1.9676 1.9224 1.9502 1.7990 2.0824 2.1300
2.0095 2.0341 1.8433 1.8361 1.9958 1.8243 2.0397 2.0482
2.1143 2.2627 1.7620 1.7561 1.9490 1.9803 1.9336 2.2511
2.2377 2.5414 1.7867 1.6618 2.5090 1.8325 2.0212 2.1616
2.3476 2.1878 2.0469 1.7508 2.2969 1.7939 2.0291 2.0721
2.3534 2.0932 2.3502 1.9960 2.0710 1.9923 1.7787 1.9772
2.2607 2.1504 2.3685 2.1148 2.1961 1.7738 1.8405 2.0135
2.2411 1.9916 2.4726 2.0347 2.0751 1.7570 1.8874 1.9385
数据2:
2.1913 1.8981 2.2441 2.3068 2.1198 2.1484 1.8056 1.7747
2.0842 1.8750 2.3023 2.1204 1.8972 2.1534 1.8028 1.9401
2.2105 1.9618 2.2472 1.9656 2.3098 1.9771 1.9520 1.8627
2.2863 1.9959 2.1781 1.9544 1.9281 1.9286 1.9699 2.0330
2.1987 2.0583 2.0953 2.0206 2.1148 2.3789 1.7052 1.9145
2.0513 2.0850 1.9810 2.4943 1.9120 2.2209 1.9461 2.0882
2.0049 2.0416 1.9303 2.3681 1.8974 2.0054 1.9261 1.9097
1.6882 2.1196 1.8641 2.3600 2.0931 1.7641 2.1131 1.7748
1.8840 1.7604 1.7664 2.2000 2.0055 1.8229 1.9871 1.9168
1.7340 1.9656 1.8480 2.0523 1.9950 1.8716 1.9206 1.7786
1.9604 1.9804 1.9601 2.0599 1.8969 1.8087 2.1845 1.8598
数据3:
1.8064 2.2016 2.4506 2.1828 2.1171 1.9308 2.1707 2.1885
2.2310 2.2400 1.9115 2.1527 2.0934 1.7989 2.2144 2.0091
1.9248 2.2038 1.9676 1.9224 1.9502 1.7990 2.0824 2.1300
2.0095 2.0341 1.8433 1.8361 1.9958 1.8243 2.0397 2.0482
2.1143 2.2627 1.7620 1.7561 1.9490 1.9803 1.9336 2.2511
2.2377 2.5414 1.7867 1.6618 2.5090 1.8325 2.0212 2.1616
2.3476 2.1878 2.0469 1.7508 2.2969 1.7939 2.0291 2.0721
2.3534 2.0932 2.3502 1.9960 2.0710 1.9923 1.7787 1.9772
2.2607 2.1504 2.3685 2.1148 2.1961 1.7738 1.8405 2.0135
2.2411 1.9916 2.4726 2.0347 2.0751 1.7570 1.8874 1.9385
数据4:
2.1913 1.8981 2.2441 2.3068 2.1198 2.1484 1.8056 1.7747
2.0842 1.8750 2.3023 2.1204 1.8972 2.1534 1.8028 1.9401
2.2105 1.9618 2.2472 1.9656 2.3098 1.9771 1.9520 1.8627
2.2863 1.9959 2.1781 1.9544 1.9281 1.9286 1.9699 2.0330
2.1987 2.0583 2.0953 2.0206 2.1148 2.3789 1.7052 1.9145
2.0513 2.0850 1.9810 2.4943 1.9120 2.2209 1.9461 2.0882
2.0049 2.0416 1.9303 2.3681 1.8974 2.0054 1.9261 1.9097
1.6882 2.1196 1.8641 2.3600 2.0931 1.7641 2.1131 1.7748
1.8840 1.7604 1.7664 2.2000 2.0055 1.8229 1.9871 1.9168
1.7340 1.9656 1.8480 2.0523 1.9950 1.8716 1.9206 1.7786
1.9604 1.9804 1.9601 2.0599 1.8969 1.8087 2.1845 1.8598
我需要从 data1 获取第 1 列,从 data2 获取第 1 列,从 data3 获取第 1 列,从 data4 获取第 1 列,并将它们并排组合成一个数据框,并对其他列执行相同的操作。
我正在使用这个方法,但它有点简陋
dat1 <- data.frame(data1$V1)
dat2 <- data.frame(data2$V1)
dat3 <- data.frame(data3$V1)
dat4 <- data.frame(data4$V1)
final_data1 <- cbind(dat1,dat2,dat3,dat4)
.
.
.
dat1 <- data.frame(data1$V8)
dat2 <- data.frame(data2$V8)
dat3 <- data.frame(data3$V8)
dat4 <- data.frame(data4$V8)
final_data8 <- cbind(dat1,dat2,dat3,dat4)
有没有办法用循环来做到这一点?
最佳答案
我们可以循环遍历列,绑定(bind)它们,并将生成的 8 个数据帧保存在列表中:
res <- lapply(1:8, function(i){ cbind(data1[i], data2[i], data3[i], data4[i]) })
关于r - 循环多个数据帧,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/38891864/