Hello I have 2 dataframe
The first
df1
target Name
SP1.1 Lupus
SP2.2 Canis
SP3.3 Canis
and the second where I have NA values in the Name columns that I need to fill according to df1$Name and df1$target matches between the two df
df2
target Name COLn
SP1.1 <NA> 9
SP2.2 Canis 32
SP3.3 <NA> 78
SP4 Canis 7
The expected result would be
df2
target Name COLn
SP1.1 Lupus 9
SP2.2 Canis 32
SP3.3 Canis 78
SP4 Canis 7
doessomeone have an idea?
You can join df1 and df2 by target and select first non-NA value using coalesce for Name column.
library(dplyr)
df1 %>%
right_join(df2, by = 'target') %>%
mutate(Name = coalesce(Name.x, Name.y)) %>%
select(names(df2))
# target Name COLn
#1 SP1.1 Lupus 9
#2 SP2.2 Canis 32
#3 SP3.3 Canis 78
#4 SP4 Canis 7
In base R, you can do :
transform(merge(df1, df2, all.y = TRUE, by = 'target'),
Name = ifelse(is.na(Name.x), Name.y, Name.x))[names(df2)]
If target uniquely identifies rows, you can use dplyr::rows_patch().
library(dplyr)
df2 %>%
rows_patch(df1, by = "target")
target Name COLn
1 SP1.1 Lupus 9
2 SP2.2 Canis 32
3 SP3.3 Canis 78
4 SP4 Canis 7
