R: Adding values from a selected column to a large number of other columns

Question

I am relatively new to R and have a data frame that looks like this:

df <- structure(list(row.names = 1:5, date = c("01-01-2017", "10-01-2017", 
"10-04-2017", "11-04-2017", "12-04-2017"), fixed_factor = c(NA, 
3L, 2L, 5L, 10L), line_1_rec_1_mean = c(0.5, 0.1, 0.05, 0.05, 
0.1), line_1_rec_2_mean = c(6, 5, 3, 2, 0.9), line_1_rec_3_mean = c(88L, 
3L, 4L, 3L, 7L), line_1_rec_5_mean = c(6, 0.2, 0.7, 0.6, 3), 
    line_1_rec_6_mean = c(50L, 1L, 5L, 8L, 2L)), row.names = c(NA, 
-5L), class = "data.frame")

  row.names       date fixed_factor line_1_rec_1_mean line_1_rec_2_mean line_1_rec_3_mean line_1_rec_5_mean line_1_rec_6_mean
1         1 01-01-2017           NA               0.5                 6                88                 6                50
2         2 10-01-2017            3               0.1                 5                 3               0.2                 1
3         3 10-04-2017            2              0.05                 3                 4               0.7                 5
4         4 11-04-2017            5              0.05                 2                 3               0.6                 8
5         5 12-04-2017           10               0.1               0.9                 7                 3                 2

The real dataframe contains over 1,500 columns and 365 rows.

What I am trying to do is to add the "fixed_factor" for each row to all "line_1_rec*" columns. Which is all columns except the first three and save the resulting data set as a new data frame which would look sth like this:

 row.names       date fixed_factor line_1_rec_1_mean line_1_rec_2_mean line_1_rec_3_mean line_1_rec_5_mean line_1_rec_6_mean
1         1 01-01-2017           NA              0.50               6.0                88               6.0                50
2         2 10-01-2017            3              3.10               8.0                 6               3.2                 4
3         3 10-04-2017            2              2.05               5.0                 6               2.7                 7
4         4 11-04-2017            5              5.05               7.0                 8               5.6                13
5         5 12-04-2017           10             10.10              10.9                17              13.0                12

I have done alot of reading but have not managed to find a solution. Any help would be greatly appreciated.

Answer 1

You can use dplyr . There is a way to change (or mutate ) multiple columns at once. You can specify the relvant columns using across . Note that I replace NA with 0 in fixed_factor using coalesce .

library(dplyr)

df %>% 
  mutate(across(matches("line_1_rec"), ~.x + coalesce(fixed_factor, 0)))

Answer 2

Try

tmp=grep("line_1_rec",colnames(df))
df[,tmp]=replace(df[,"fixed_factor"],is.na(df[,"fixed_factor"]),0)+df[,tmp]

  row.names     date.x fixed_factor line_1_rec_1_mean line_1_rec_2_mean line_1_rec_3_mean
1         1 01-01-2017           NA              0.50               6.0                88
2         2 10-01-2017            3              3.10               8.0                 6
3         3 10-04-2017            2              2.05               5.0                 6
4         4 11-04-2017            5              5.05               7.0                 8
5         5 12-04-2017           10             10.10              10.9                17
  line_1_rec_4_mean line_1_rec_5_mean
1               6.0                50
2               3.2                 4
3               2.7                 7
4               5.6                13
5              13.0                12

Answer 3

There is a simple way :

df$fixed_factor[is.na(df$fixed_factor)] <- 0   #replace NA values in fixed factor by 0;
df_res <- df[,c(4:ncol(df)] + df$fixed_factor  #Add the fixed factor

It's, I think, the most simple way to understand how works dataframe in R at the beginning.

Answer 4

# Store a vector of column names of line cols:
#line1_cnames => character vector
line1_cnames <- grep("line_1_rec.*", names(df), value = TRUE)

# Don't replace NA values:
# Add the fixed factor to each line1_rec vector: res => data.frame
res <- setNames(
   df$fixed_factor + df[,line1_cnames],
   paste(
      "fixed_factor_plus",
      line1_cnames,
      sep = "_"
   )
)

# replace NA values:
# Add the fixed factor to each line1_rec vector: res => data.frame
res <- setNames(
   with(
      replace(df, is.na(df), 0),
      fixed_factor + replace(df, is.na(df), 0)[,line1_cnames]
   ),
   paste(
      "fixed_factor_plus",
      line1_cnames,
      sep = "_"
   )
)