Adding new row to dataframe with values taken from other rows to replace NAs in R

Question

I have a dataframe much like this one

ID     Col2  Col3  Col4  Col5 
ID_1   JDH   43    FJS   f8j
ID_8   ABC   73    *NA*  *NA*
ID_7   AFE   03    *NA*  k32
ID_8  *NA*   *NA*   FDS   z7d

where I have some rows with the same name/ID (ID_8 in this example) that have different values in the following columns. I now want to merge these rows into a new row ID_8_New without NAs. The dataframe should look something like this:

ID         Col2  Col3  Col4  Col5 
ID_1       JDH   43    FJS   f8j
ID_8       ABC   73    *NA*  *NA*
ID_7       AFE   03    *NA*  k32
ID_8      *NA*   *NA*   FDS   z7d
ID_8_New   ABC   73    FDS   z7d

Does anyone have any tips for me how I can accomplish this? My real dataframe has multiple of those rows. Thank you!

EDIT: Here is the dputstructure of a subset of my data

structure(list(Company = c("CompanyA", "CompanyA"), Ticker = c("A", 
"A"), Ticker_Unq = c("A1", 
"A2"), Description = c(NA, 
"Text"
), Type = c("Token", NA)), row.names = c(NA, -2L), class = c("tbl_df", 
"tbl", "data.frame"))

Answer 1

We could filter

library(dplyr)
library(stringr)
library(tidyr)
df1 %>%
   group_by(ID) %>%
    filter(n() > 1) %>%
    summarise(across(everything(), ~ .x[order(is.na(.x))]), .groups = 'drop')%>%
    drop_na() %>%
    mutate(ID = str_c(ID, '_new')) %>%
    bind_rows(df1, .)

-output

       ID Col2 Col3 Col4 Col5
1     ID_1  JDH   43  FJS  f8j
2     ID_8  ABC   73 <NA> <NA>
3     ID_7  AFE    3 <NA>  k32
4     ID_8 <NA>   NA  FDS  z7d
5 ID_8_new  ABC   73  FDS  z7d

-output

df1 <- structure(list(ID = c("ID_1", "ID_8", "ID_7", "ID_8"),
 Col2 = c("JDH", 
"ABC", "AFE", NA), Col3 = c(43L, 73L, 3L, NA), Col4 = c("FJS", 
NA, NA, "FDS"), Col5 = c("f8j", NA, "k32", "z7d")),
 class = "data.frame", row.names = c(NA, 
-4L))

Answer 2

You can return the maximum value per group:

library(dplyr)
dat %>% 
  group_by(ID) %>% 
  summarise(across(everything(), ~ max(.x, na.rm = T)))

output

# A tibble: 3 × 5
  ID    Col2  Col3  Col4  Col5 
  <chr> <chr> <chr> <chr> <chr>
1 ID_1  JDH   43    FJS   f8j  
2 ID_7  AFE   03    NA    k32  
3 ID_8  ABC   73    FDS   z7d