Merging data frames with different number of rows and different columns

Question

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            


        

Answer 1

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)))