CODEWITHSUNDEEP
rdataframemergerbindcbind
Steviee kann
Steviee kann

Reputation: 35

Merging data frames of different lengths without unique keys

I am trying to merge two data frames of different lengths without using a unique key.

For example: 

Name <- c("Steve","Peter")
Age <- c(10,20)

df1 <- data.frame(Name,Age)

> df1
   Name Age
1 Steve  10
2 Peter  20

Name <-c("Jason","Nelson")
School <-c("xyz","abc")

df2 <- data.frame(Name,School)

> df2
    Name School
1  Jason    xyz
2 Nelson    abc

I want to join these two tables so that I have all columns and have NA cells for rows that didn't have that column originally. It should look something like this:

    Name Age School
1  Steve  10   <NA>
2  Peter  20   <NA>
3  Jason  NA    xyz
4 Nelson  NA    abc

thank you in advance!

Upvotes: 1

Views: 757

Answers (1)

r2evans
r2evans

Reputation: 160447

dplyr::bind_rows(df1,df2)
# Warning in bind_rows_(x, .id) :
#   Unequal factor levels: coercing to character
# Warning in bind_rows_(x, .id) :
#   binding character and factor vector, coercing into character vector
# Warning in bind_rows_(x, .id) :
#   binding character and factor vector, coercing into character vector
#     Name Age School
# 1  Steve  10   <NA>
# 2  Peter  20   <NA>
# 3  Jason  NA    xyz
# 4 Nelson  NA    abc

You can alleviate some of this by pre-assigning unrecognized columns, which also works well with base R:

df2 <- cbind(df2, df1[NA,setdiff(names(df1), names(df2)),drop=FALSE])
df1 <- cbind(df1, df2[NA,setdiff(names(df2), names(df1)),drop=FALSE])
df1
#       Name Age School
# NA   Steve  10   <NA>
# NA.1 Peter  20   <NA>
df2
#        Name School Age
# NA    Jason    xyz  NA
# NA.1 Nelson    abc  NA

# ensure we use the same column order for both frames
nms <- names(df1)
rbind(df1[,nms], df2[,nms])
#         Name Age School
# NA     Steve  10   <NA>
# NA.1   Peter  20   <NA>
# NA1    Jason  NA    xyz
# NA.11 Nelson  NA    abc

Upvotes: 2

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