CODEWITHSUNDEEP
rdataframemergena
SylvainC
SylvainC

Reputation: 59

Merge two data.frames (cell wise)

I have 2 data.frames (df1 et df2) with some empty cells (NAs).

df1<-data.frame(code=c("A","B","C","D"),
                x=c(2.3,NA,3.1,2.6),
                y=c(4.1,2,NA,8))

df2<-data.frame(code=c("A","B","C","D"),
                x=c(NA,8.1,NA,NA),
                y=c(NA,NA,0.5,NA))

I want to fill the NA cells in df1 with the corresponding value in df2.

Expected results :

  code   x   y
1    A 2.3 4.1
2    B 8.1 2.0
3    C 3.1 0.5
4    D 2.6 8.0

I managed to do it with for loops (scanning each cell).

It works but I guess there is a more efficient way of doing this... and I love to learn new tricks...

Thanks in advance

Upvotes: 4

Views: 180

Answers (4)

Donald Seinen
Donald Seinen

Reputation: 4419

A base R option

df1[is.na(df1)] = as.numeric(df2[is.na(df1)])
df1

Upvotes: 1

Sweepy Dodo
Sweepy Dodo

Reputation: 1863

For speed

# set as data.table
lapply(list(df1, df2), \(i) setDT(i))

# custom efficient coalesce
coalesce2 <- function(...)
  {
  Reduce(function(x, y) {
    i <- which(is.na(x))
    x[i] <- y[i]
    x},
    list(...))
  }

# join
df3 <- df2[df1, on =.(code)]

# apply coalesce
df3[, `:=` (x = coalesce2(i.x, x)
            , y = coalesce2(i.y, y)
            )
    ][, c('i.x', 'i.y') := NULL
      ]

Upvotes: 1

Ma&#235;l
Ma&#235;l

Reputation: 51914

Using coalesce:

library(dplyr)
do.call(coalesce, list(df1, df2))

  code   x   y
1    A 2.3 4.1
2    B 8.1 2.0
3    C 3.1 0.5
4    D 2.6 8.0

Upvotes: 1

PaulS
PaulS

Reputation: 25323

A possible solution, using purrr::map2_dfc:

library(tidyverse)

map2_dfc(df1, df2, ~ if_else(is.na(.x), .y, .x))

#> # A tibble: 4 × 3
#>   code      x     y
#>   <chr> <dbl> <dbl>
#> 1 A       2.3   4.1
#> 2 B       8.1   2  
#> 3 C       3.1   0.5
#> 4 D       2.6   8

Upvotes: 2

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