1. Merge Dataframes By Rownames R
  2. R Merge Multiple Data Frames

merge is a generic function whose principal method is for data frames: the default method coerces its arguments to data frames and calls the 'data.frame' method.

By default the data frames are merged on the columns with names they both have, but separate specifications of the columns can be given by by.x and by.y. The rows in the two data frames that match on the specified columns are extracted, and joined together. If there is more than one match, all possible matches contribute one row each. For the precise meaning of ‘match’, see match.

Merged.df merge(df1,df2,all=T,by='row.names') R merged.df Row.names x y z 1 r1 1 1 NA 2 r2 2 2 NA 3 r3 3 3 NA 4 r5 NA NA 5 5 r6 NA NA 6 6 r7 NA NA 7 but I want the input row names to be the row names in the output dataframe (merged.df). Merge Data Frames by Row Names In the following example, we will combine our two example data frames with the merge function. The merge function provides the by argument, which usually specifies the column name based on which we want to merge.

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Columns to merge on can be specified by name, number or by a logical vector: the name 'row.names' or the number 0 specifies the row names. If specified by name it must correspond uniquely to a named column in the input.

Merge Dataframes By Rownames R

If by or both by.x and by.y are of length 0 (a length zero vector or NULL), the result, r, is the Cartesian product of x and y, i.e., dim(r) = c(nrow(x)*nrow(y), ncol(x) + ncol(y)).

If all.x is true, all the non matching cases of x are appended to the result as well, with NA filled in the corresponding columns of y; analogously for all.y.

If the columns in the data frames not used in merging have any common names, these have suffixes ('.x' and '.y' by default) appended to try to make the names of the result unique. If this is not possible, an error is thrown.

If a by.x column name matches one of y, and if no.dups is true (as by default), the y version gets suffixed as well, avoiding duplicate column names in the result.

The complexity of the algorithm used is proportional to the length of the answer.

In SQL database terminology, the default value of all = FALSE gives a natural join, a special case of an inner join. Specifying all.x = TRUE gives a left (outer) join, all.y = TRUE a right (outer) join, and both (all = TRUE) a (full) outer join. DBMSes do not match NULL records, equivalent to incomparables = NA in R.


R Merge Multiple Data Frames

-----Original Message-----
From: [hidden email] [mailto:[hidden email]] On Behalf Of dms
Sent: Wednesday, March 02, 2011 3:16 PM
To: [hidden email]
Subject: [R] merge( , by='row.names') slowness
I noticed that joining two data.frames in R using the 'merge'
function that using by='row.names' slows things down substantially
when compared to just joining on a common index column.
Using a dataframe size of ~10,000 rows: it's as slow as 10 minutes in
the by='row.names' case versus merely 1 second using an index column.
Beyond the 10^6 range, it's unusably slow.
n <- 5
a <- data.frame(id=as.character(1:10^n), x=rnorm(10^n)); rownames(a)
<- a$id
b <- data.frame(id=as.character(1:10^n + 10^(n-1)), y=rnorm(10^n));
rownames(b) <- b$id
fast <- merge(a, b, all=T)
slow <- merge(a, b, all=T, by='row.names')
Has anybody else noticed this?
Well, first off, they don't give the same answer.. in fact, not even the same dimension.
Even so, from looking at merge.data.frame, it's not immediately obvious what would make a difference of this magnitude.
The answer might be buried in the internal merge.
Here for n=3:
> system.time(print(dim(merge(a,b,all=T))))
[1] 1100 3
user system elapsed
0.01 0.00 0.01
> system.time(print(dim(merge(a,b,all=T,by=1))))
[1] 1100 3
user system elapsed
0.01 0.00 0.02
> system.time(print(dim(merge(a,b,all=T,by=0))))
[1] 1100 5
user system elapsed
3.26 0.00 3.17
> system.time(print(dim(merge(a,b,all=T,by='row.names'))))
[1] 1100 5
user system elapsed
3.17 0.00 3.17
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.