merge - Combine vectors and tables in R -


i encountered problem during simple merging task , i'm looking better solution. i'm creating tables series of surveys (which cannot merge). tables have same values, different dimensions.

the data below.

table x

x <- structure(c(44l, 167l), .dim = 2l, .dimnames = structure(list(     c("similar", "compete")), .names = ""), class = "table")

table y

y <- structure(c(69l, 213l, 154l, 4l, 29l, 32l), .dim = c(3l, 2l), .dimnames = structure(list(     c("other", "compete", "similar"), c("college", "no college"     )), .names = c("", "")), class = "table")

table z

z <- structure(c(13l, 38l, 43l, 46l, 131l, 172l, 37l, 177l, 122l,  8l, 34l, 12l, 16l, 114l, 70l, 20l, 17l, 27l), .dim = c(3l, 6l ), .dimnames = structure(list(c("other", "compete", "similar" ), c("skipped", "democrat", "independent", "libertarian", "republican",  "other")), .names = c("", "")), class = "table")

my solution use cbind , take out disimilar columns so

cbind(y[-1,], x,  z[-1,-1])

then learned in r, row names unreliable , table turns out different if order of cbind mixed up. makes creating table unreliable. i'd able merge 3 or more tables, without having worry order of merge messing data.

what better way of combining tables different dimensions?

i suspect there might great way data.table or dplyr haven't figured out.

thanks , please let me know if can make question more clear.

not sure if i'm missing point here , not sure how "automated" need process be, might helpful:

x <- structure(c(44l, 167l), .dim = 2l, .dimnames = structure(list(   c("similar", "compete")), .names = ""), class = "table")  y <- structure(c(69l, 213l, 154l, 4l, 29l, 32l), .dim = c(3l, 2l), .dimnames = structure(list(   c("other", "compete", "similar"), c("college", "no college"   )), .names = c("", "")), class = "table")  z <- structure(c(13l, 38l, 43l, 46l, 131l, 172l, 37l, 177l, 122l,                   8l, 34l, 12l, 16l, 114l, 70l, 20l, 17l, 27l), .dim = c(3l, 6l                  ), .dimnames = structure(list(c("other", "compete", "similar"                  ), c("skipped", "democrat", "independent", "libertarian", "republican",                        "other")), .names = c("", "")), class = "table")  library(dplyr) library(tidyr)  # create data frames tables x = data.frame(x) names(x) = c("group","x")  y = data.frame(y) %>% spread(var2,freq) names(y)[1] = "group"  z = data.frame(z) %>% spread(var2, freq) names(z)[1] = "group"  # join data frames x %>% inner_join(y, by="group") %>% inner_join(z, by="group")  #     group   x college no college skipped democrat independent libertarian republican other # 1 similar  44     154         32      43      172         122          12         70    27 # 2 compete 167     213         29      38      131         177          34        114    17

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