How to merge multiple frames into one

To illustrate, I will create 3 different data.frames of example, one with the variable x , another with variable y and another with the variable z for the same individuals id :

### exemplos ####
set.seed(1)
df1 <- data.frame(id=1:10, y = rnorm(10))
df2 <- data.frame(id=1:10, z = rnorm(10))
df3 <- data.frame(id=1:10, x = rnorm(10))

With the base functions of R, one way to merge directly from the three is to combine the Reduce function with the merge :

resultado <- Reduce(function(x,y) {merge(x,y)}, list(df1, df2, df3))
resultado
   id          y           z           x
1   1 -0.6264538  1.51178117  0.91897737
2   2  0.1836433  0.38984324  0.78213630
3   3 -0.8356286 -0.62124058  0.07456498
4   4  1.5952808 -2.21469989 -1.98935170
5   5  0.3295078  1.12493092  0.61982575
6   6 -0.8204684 -0.04493361 -0.05612874
7   7  0.4874291 -0.01619026 -0.15579551
8   8  0.7383247  0.94383621 -1.47075238
9   9  0.5757814  0.82122120 -0.47815006
10 10 -0.3053884  0.59390132  0.41794156

In the plyr package, there is the join_all function, which basically does the even though it was done above, but with a simpler syntax:

library(plyr) ### se você ainda não tem o pacote, você tem que instalar antes

resultados <- join_all(list(df1,df2,df3)) 
resultados

   id          y           z           x
1   1 -0.6264538  1.51178117  0.91897737
2   2  0.1836433  0.38984324  0.78213630
3   3 -0.8356286 -0.62124058  0.07456498
4   4  1.5952808 -2.21469989 -1.98935170
5   5  0.3295078  1.12493092  0.61982575
6   6 -0.8204684 -0.04493361 -0.05612874
7   7  0.4874291 -0.01619026 -0.15579551
8   8  0.7383247  0.94383621 -1.47075238
9   9  0.5757814  0.82122120 -0.47815006
10 10 -0.3053884  0.59390132  0.41794156

Or if you just want to type in a cleaner way, you can use the magrittr package % that has a forward pipe operator for R. With this package, the merge of the 3 data.frames can also be done in a row only by chaining the arguments with the %>% operator:

 library(magrittr) ### se você ainda não tem o pacote, você tem que instalar antes

 resultado <- df1%>%merge(df2)%>%merge(df3)
 resultado

   id          y           z           x
1   1 -0.6264538  1.51178117  0.91897737
2   2  0.1836433  0.38984324  0.78213630
3   3 -0.8356286 -0.62124058  0.07456498
4   4  1.5952808 -2.21469989 -1.98935170
5   5  0.3295078  1.12493092  0.61982575
6   6 -0.8204684 -0.04493361 -0.05612874
7   7  0.4874291 -0.01619026 -0.15579551
8   8  0.7383247  0.94383621 -1.47075238
9   9  0.5757814  0.82122120 -0.47815006
10 10 -0.3053884  0.59390132  0.41794156

Remembering that it's always good to specify the identifier columns of merge (option by of function), otherwise you might end up with something different than expected. In the above case this is not necessary because we only have one column in common.

For those who want a "new" alternative.

It has the functions:

bind_rows(..., .id = NULL)

bind_cols(...)

combine(...)

They are in the dplyr package that is worth studying.

With dplyr you can use join functions chained to the piper operator %>% ( inner_join , full_join , left_join , right_join etc, depending on your purpose). >

Example with full_join chained:

library(dplyr)

set.seed(1)
df1 <- data.frame(id=1:10, y = rnorm(10))
df2 <- data.frame(id=1:10, z = rnorm(10))
df3 <- data.frame(id=1:10, x = rnorm(10))

df1 %>% full_join(df2) %>% full_join(df3)

  id          y           z           x
1   1 -0.6264538  1.51178117  0.91897737
2   2  0.1836433  0.38984324  0.78213630
3   3 -0.8356286 -0.62124058  0.07456498
4   4  1.5952808 -2.21469989 -1.98935170
5   5  0.3295078  1.12493092  0.61982575
6   6 -0.8204684 -0.04493361 -0.05612874
7   7  0.4874291 -0.01619026 -0.15579551
8   8  0.7383247  0.94383621 -1.47075238
9   9  0.5757814  0.82122120 -0.47815006
10 10 -0.3053884  0.59390132  0.41794156