Ideal merge for different number of columns and rows in dataframe

Question

Some example data of stucture:

df1 = data.frame(x=c('a', 'b', 'c', 'd', 'e'))
df2 = data.frame(x=c('f', 'g', 'h'),y = c(0,1,0))
df3 = data.frame(x=c('i', 'j','k','l'), y = c(1,7,5,2,6), z = c(75,3,25,2,1))

I have 3 different dataframes.

df1 has 22201 object and 121 variables df2 has 8403 object and 68 variables df3 has 50476 object and 157 variables

I try to merge them using merge and I receive this error:

Error in fix.by(by.x, x) : 
  'by' must specify one or more columns as numbers, names or logical

using cbind and I received this error:

Error in data.frame(..., check.names = FALSE) : 
  arguments imply differing number of rows: 22201, 8403, 50476

and rbind and I receive this error:

Error in rbind(deparse.level, ...) : 
  numbers of columns of arguments do not match

How can I merge dataframes with different number of rows and columns? I have to refer that columns have the same names in dataframes so in the merge I expect the number of columns be the highest numbers of columns of the dataframe which contains the most.

Can you show us your code and a reproducible example of your dataframes? — Barbara
– Barbara, Commented Nov 14, 2017 at 14:37

Santosh M. · Accepted Answer · 2017-11-14 14:44:33Z

3

In this case, use rbind.fill from the library plyr

library(plyr)
rbind.fill(df1, df2, df3)

This will merge all your 3 data frames with different number of columns.

answered Nov 14, 2017 at 14:44

Santosh M.

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quartin · Accepted Answer · 2017-11-14 14:58:43Z

2

dplyr is an evolution from plyr, so I'd use it instead. bind_rows will achieve what you want:

library(dplyr)
bind_rows(df1, df2, df3, ...)

One example:

tbl1 <- data_frame(var1 = c('a', 'b', 'c'),
                   var2 = c('x', 'y', 'z'))

tbl2 <- data_frame(var1 = c('e', 'd', 'g', 'h'))

tbl3 <- data_frame(var6 = 1, 
                   var10 = 14)

> bind_rows(tbl1, tbl2, tbl3)
# A tibble: 8 x 4
   var1  var2  var6 var10
  <chr> <chr> <dbl> <dbl>
1     a     x    NA    NA
2     b     y    NA    NA
3     c     z    NA    NA
4     e  <NA>    NA    NA
5     d  <NA>    NA    NA
6     g  <NA>    NA    NA
7     h  <NA>    NA    NA
8  <NA>  <NA>     1    14

edited Nov 14, 2017 at 14:58

answered Nov 14, 2017 at 14:50

quartin

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