How to join dataframes without losing rows

Question

I have the following dataframes. I cannot find a satisfying way to merge them all. I tried the following:

a=data.frame('name'=c('a','b','c','d'),'value'=c(23,45,23,56))
b=data.frame('name'=c('a','b','f','e'),'value'=c(23,45,23,56))
d=data.frame('name'=c('g','b','f','e'),'value'=c(23,45,23,56))
testlist=list(a,b,d)
c=join_all(testlist,by='name',type='left',match='all')

But this return me the following table:

  name value value value
1    a    23    23    NA
2    b    45    45    45
3    c    23    NA    NA
4    d    56    NA    NA

while instead, I would like a table with all the possible names in the first column ('a','b','c','d','e','f','g') and all the other values in the corresponding rows in 3 different columns (1 per dataframe). How can I do it? Does not matter if all the blanck values are NA, I will change then later with 0

Thanks!!!!!!

Related to https://stackoverflow.com/questions/14096814/merging-a-lot-of-data-frames — akrun, Jan 07 '19 at 16:05

Maurits Evers · Accepted Answer · 2019-01-07T16:07:58.300

A base R option is to use Reduce with merge(..., all = TRUE)

Reduce(function(x, y) merge(x, y, by = "name", all = T), testlist)
#  name value.x value.y value
#1    a      23      23    NA
#2    b      45      45    45
#3    c      23      NA    NA
#4    d      56      NA    NA
#5    e      NA      56    56
#6    f      NA      23    23
#7    g      NA      NA    23

Or similarly using dplyr::full_join and purrr::reduce

library(dplyr)
library(purrr)
reduce(testlist, full_join, by = "name")

How to join dataframes without losing rows

1 Answers1