I have df1:

df1 <- data.frame(X1 = c(2,5,1,5,4,6),
              X2 = c(1,4,2,5,2,9),
              X3 = c(8,4,2,6,3,8))
rownames(df1) <- rownames(df1) <- c("a","b","c","d","e","f")

  X1 X2 X3
a  2  1  8
b  5  4  4
c  1  2  2
d  5  5  6
e  4  2  3
f  6  9  8

and df2:

df2 <- data.frame(X1 = c(9,8,0),
              X2 = c(4,6,2),
              X3 = c(7,0,2)
rownames(df2) <- c("b","c","f")

  X1 X2 X3
b  9  4  7
c  8  6  0
f  0  2  2

my goal is to update only the values in df1 with values of df2 where their rownames are identical:

  X1 X2 X3
a  2  1  8
b  9  4  7
c  8  6  0
d  5  5  6
e  4  2  3
f  0  2  2

I feel this should be rather simple but I could not find an answer in the forum nor figure this out by myself.

Note: all rows of df2 are present in df1

CodePudding user response：

Try

df1[na.omit(match(rownames(df1), rownames(df2))),] <- df2

  X1 X2 X3
a  9  4  7
b  8  6  0
c  0  2  2
d  5  5  6
e  4  2  3
f  6  9  8

CodePudding user response：

Another dplyr option with rows_update:

df1 <- data.frame(X1 = c(2,5,1,5,4,6),
                  X2 = c(1,4,2,5,2,9),
                  X3 = c(8,4,2,6,3,8))
rownames(df1) <- rownames(df1) <- c("a","b","c","d","e","f")

df2 <- data.frame(X1 = c(9,8,0),
                  X2 = c(4,6,2),
                  X3 = c(7,0,2))
rownames(df2) <- c("b","c","f")

library(dplyr)
library(tibble)
df1 %>%
  rownames_to_column() %>%
  rows_update(df2 %>% rownames_to_column(), by = "rowname") %>%
  column_to_rownames()
#>   X1 X2 X3
#> a  2  1  8
#> b  9  4  7
#> c  8  6  0
#> d  5  5  6
#> e  4  2  3
#> f  0  2  2

^{Created on 2022-07-19 by the reprex package (v2.0.1)}

CodePudding user response：

Another possible solution:

library(tidyverse)
             
bind_rows(df1 %>% rownames_to_column(), df2 %>% rownames_to_column()) %>% 
  group_by(rowname) %>% 
  slice_tail(n = 1) %>% 
  column_to_rownames

#>   X1 X2 X3
#> a  2  1  8
#> b  9  4  7
#> c  8  6  0
#> d  5  5  6
#> e  4  2  3
#> f  0  2  2