根据R中第一列中的信息替换其他数据中的值

Question

I'm trying to merge informations in two different data frames, but problem begins with uneven dimensions and trying to use not the column index but the information in the column. merge function in R or join's (dplyr) don't work with my data.

I have to dataframes (One is subset of the others with updated info in the last column):

df1=data.frame(Name = print(LETTERS[1:9]), val = seq(1:3), Case = c("NA","1","NA","NA","1","NA","1","NA","NA"))

  Name val Case
1  A   1   NA
2  B   2    1
3  C   3   NA
4  D   1   NA
5  E   2    1
6  F   3   NA
7  G   1    1
8  H   2   NA
9  I   3   NA

Some rows in the Case column in df1 have to be changed with the info in the df2 below:

df2 = data.frame(Name = c("A","D","H"), val = seq(1:3), Case = "1")

    Name val Case
1    A   1    1
2    D   2    1
3    H   3    1

So there's nothing important in the val column, however I added it into the examples since I want to indicate that I have more columns than two and also my real data is way bigger than the examples.

Basically, I want to change specific rows by checking the information in the first columns (in this case, they're unique letters) and in the end I still want to have df1 as a final data frame.

for a better explanation, I want to see something like this:

  Name val Case
1  A   1    1
2  B   2    1
3  C   3   NA
4  D   1    1
5  E   2    1
6  F   3   NA
7  G   1    1
8  H   2    1
9  I   3   NA

Note changed information for A , D and H .

Thanks.

Answer 1

%in% from base-r is there to rescue.

    df1=data.frame(Name = print(LETTERS[1:9]), val = seq(1:3), Case = c("NA","1","NA","NA","1","NA","1","NA","NA"), stringsAsFactors = F)

    df2 = data.frame(Name = c("A","D","H"), val = seq(1:3), Case = "1", stringsAsFactors = F)




    df1$Case <- ifelse(df1$Name %in% df2$Name, df2$Case[df2$Name %in% df1$Name], df1$Case)

df1

Output:

> df1
  Name val Case
1    A   1    1
2    B   2    1
3    C   3   NA
4    D   1    1
5    E   2    1
6    F   3   NA
7    G   1    1
8    H   2    1
9    I   3   NA

Answer 2

Here is what I would do using dplyr :

df1 %>% 
  left_join(df2, by = c("Name")) %>% 
  mutate(val = if_else(is.na(val.y), val.x, val.y), 
         Case = if_else(is.na(Case.y), Case.x, Case.y)) %>% 
 select(Name, val, Case)