合并具有不同行数和不同列的数据帧 [英] Merging data frames with different number of rows and different columns
问题描述
我有两个具有不同列数和行数的数据框.我想将它们组合成一个数据帧.
I have two data frames with different number of columns and rows. I want to combine them into one data frame.
> month.saf
Name NCDC Year Month Day HrMn Temp Q
244 AP 99999 2014 2 1 0 12 1
245 AP 99999 2014 2 1 300 12.2 1
246 AP 99999 2014 2 1 600 14.4 1
247 AP 99999 2014 2 1 900 18.6 1
248 AP 99999 2014 2 1 1200 18 1
249 AP 99999 2014 2 1 1500 13.6 1
250 AP 99999 2014 2 1 1800 11.8 1
251 AP 99999 2014 2 1 2100 10.8 1
252 AP 99999 2014 2 2 0 8.4 1
253 AP 99999 2014 2 2 300 8.6 1
254 AP 99999 2014 2 2 600 19.8 2
255 AP 99999 2014 2 2 900 22.8 1
256 AP 99999 2014 2 2 1200 20.8 1
257 AP 99999 2014 2 2 1500 16.4 1
258 AP 99999 2014 2 2 1800 13.4 1
259 AP 99999 2014 2 2 2100 12.4 1
> T2Mdf
V1 V2
0 293.494262695312 291.642639160156
300 294.003479003906 292.375091552734
600 296.809997558594 295.207885742188
900 298.287811279297 297.181549072266
1200 298.317565917969 297.725708007813
1500 298.134002685547 296.226165771484
1800 296.006805419922 293.354248046875
2100 293.785491943359 293.547210693359
0.1 294.638732910156 293.019866943359
300.1 292.179992675781 291.256958007812
我想要的输出是这样的:
The output that I want is like this:
Name NCDC Year Month Day HrMn Temp Q V1 V2
244 AP 99999 2014 2 1 0 12 1 293.4942627 291.6426392
245 AP 99999 2014 2 1 300 12.2 1 294.003479 292.3750916
246 AP 99999 2014 2 1 600 14.4 1 296.8099976 295.2078857
247 AP 99999 2014 2 1 900 18.6 1 298.2878113 297.1815491
248 AP 99999 2014 2 1 1200 18 1 298.3175659 297.725708
249 AP 99999 2014 2 1 1500 13.6 1 298.1340027 296.2261658
250 AP 99999 2014 2 1 1800 11.8 1 296.0068054 293.354248
251 AP 99999 2014 2 1 2100 10.8 1 293.7854919 293.5472107
252 AP 99999 2014 2 2 0 8.4 1 294.6387329 293.0198669
253 AP 99999 2014 2 2 300 8.6 1 292.1799927 291.256958
254 AP 99999 2014 2 2 600 19.8 2 292.2477417 291.3471069
255 AP 99999 2014 2 2 900 22.8 1 294.2276306 294.2766418
256 AP 99999 2014 2 2 1200 20.8 1 NA NA
257 AP 99999 2014 2 2 1500 16.4 1 NA NA
258 AP 99999 2014 2 2 1800 13.4 1 NA NA
259 AP 99999 2014 2 2 2100 12.4 1 NA NA
我尝试了cbind，但它给了我一个错误
I tried cbindbut it gives me an error
data.frame(...，check.names = FALSE)中的错误:参数隐含 不同的行数:216、220
Error in data.frame(..., check.names = FALSE) : arguments imply differing number of rows: 216, 220
并使用rbind.fill()，但它给了我类似的东西
And using rbind.fill() but it gives me something like
V1 V2 Name USAF NCDC Year Month Day HrMn I Type QCP Temp Q
1 293.494262695312 291.642639160156 <NA> NA NA NA NA NA NA NA <NA> NA <NA> NA
2 294.003479003906 292.375091552734 <NA> NA NA NA NA NA NA NA <NA> NA <NA> NA
3 296.809997558594 295.207885742188 <NA> NA NA NA NA NA NA NA <NA> NA <NA> NA
4 298.287811279297 297.181549072266 <NA> NA NA NA NA NA NA NA <NA> NA <NA> NA
5 298.317565917969 297.725708007813 <NA> NA NA NA NA NA NA NA <NA> NA <NA> NA
6 <NA> <NA> AP 421820 99999 2014 2 1 0 4 FM-12 NA 12 1
7 <NA> <NA> AP 421820 99999 2014 2 1 300 4 FM-12 NA 12.2 1
8 <NA> <NA> AP 421820 99999 2014 2 1 600 4 FM-12 NA 14.4 1
9 <NA> <NA> AP 421820 99999 2014 2 1 900 4 FM-12 NA 18.6 1
10 <NA> <NA> AP 421820 99999 2014 2 1 1200 4 FM-12 NA 18 1
如何在R中做到这一点?
How is it possible to do this in R?
推荐答案
如果A和B是两个输入数据帧，则有一些解决方案:
If A and B are the two input data frames, here are some solutions:
1)合并，无论A或B是否有更多行，此解决方案都有效.
1) merge This solutions works regardless of whether A or B has more rows.
merge(data.frame(A, row.names=NULL), data.frame(B, row.names=NULL), by = 0, all = TRUE)[-1]
如果A和B具有默认行名(即1、2，...)或具有一致的行名，则前两个参数可以分别仅用A和B替换.即merge(A, B, by = 0, all = TRUE)[-1].
The first two arguments could be replaced with just A and B respectively if A and B have default rownames, i.e. 1, 2, ..., or if they have consistent rownames. That is, merge(A, B, by = 0, all = TRUE)[-1] .
例如，如果我们输入以下内容:
For example, if we have this input:
# test inputs
A <- data.frame(BOD, row.names = letters[1:6])
B <- setNames(2 * BOD[1:2, ], c("X", "Y"))
然后:
merge(data.frame(A, row.names=NULL), data.frame(B, row.names=NULL), by = 0, all = TRUE)[-1]
给予:
Time demand X Y
1 1 8.3 2 16.6
2 2 10.3 4 20.6
3 3 19.0 NA NA
4 4 16.0 NA NA
5 5 15.6 NA NA
6 7 19.8 NA NA
1a):
do.call("merge", c(lapply(list(A, B), data.frame, row.names=NULL), by = 0, all = TRUE))[-1]
2)cbind.zoo 此解决方案假定A具有更多行，并且B的条目都是同一类型，例如所有数字. A不受限制.这些条件包含在问题的数据中.
2) cbind.zoo This solution assumes that A has more rows and that B's entries are all of the same type, e.g. all numeric. A is not restricted. These conditions hold in the data of the question.
library(zoo)
data.frame(A, cbind(zoo(, 1:nrow(A)), as.zoo(B)))
注意:例如，如果
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