Merging data frames with different number of rows and different columns
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
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
I tried cbindbut it gives me an error
Error in data.frame(..., check.names = FALSE) : arguments imply differing number of rows: 216, 220
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
How is it possible to do this in R?
Answer
If A and B are the two input data frames, here are some solutions:
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]
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] .
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"))
then:
merge(data.frame(A, row.names=NULL), data.frame(B, row.names=NULL),
by = 0, all = TRUE)[-1]
gives:
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) An equivalent variation is:
do.call("merge", c(lapply(list(A, B), data.frame, row.names=NULL),
by = 0, all = TRUE))[-1]
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)))