# Merge Two Dataframes In R By Column

`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.

R Combine Data Frames – Merge based on a common column (s) merge function is used to merge data frames. The syntax of merge function is: merge(x, y, by, by.x, by.y, sort = TRUE). Example 1: Combine Data by Two ID Columns Using merge Function In Example 1, I’ll illustrate how to apply the merge function to combine data frames based on multiple ID columns. For this, we have to specify the by argument of the merge function to be equal to a vector of ID column. How to Use the merge Function with Data Sets in R. In this article. By Andrie de Vries, Joris Meys. In R you use the merge function to combine data frames. This powerful function tries to identify columns or rows that are common between the two different data frames. The second data frame also contains five rows and four columns, including the two ID columns ID1 and ID2. Example 1: Combine Data by Two ID Columns Using merge Function. In Example 1, I’ll illustrate how to apply the merge function to combine data frames based on multiple ID columns. For this, we have to specify the by argument of the merge function to be equal to a vector of ID column names (i.e. By = c(“ID1”, “ID2”)).

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`

.

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.

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.

## Merge Two Dataframes In R By Column

## Join Two Dataframes In R By Column

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.

## R Sort Dataframe By Column

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

## Merge Two Dataframes In R By Column In Excel

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.