CODEWITHSUNDEEP
rmergerowsum
Eric González
Eric González

Reputation: 485

Merge two columns maintaning missing values

I am trying to add two columns. My dataframe is like this one:

data <- data.frame(a = c(0,1,NA,0,NA,NA),
                   x = c(NA,NA,NA,NA,1,0),
                   t = c(NA,2,NA,NA,2,0))

I want to add some of the columns like this:

yep  <- cbind.data.frame( data$a, data$x, rowSums(data[,c(1, 2)], na.rm = TRUE))

However the output looks like this:

> yep

      data$a  data$x   rowSums(data[,c(1, 2)], na.rm = TRUE)
  1        0      NA                                      0
  2        1      NA                                      1
  3       NA      NA                                      0
  4        0      NA                                      0
  5       NA       1                                      1
  6       NA       0                                      0

And I would like an oputput like this:

> yep

      data$a  data$x   rowSums(data[,c(1, 2)], na.rm = TRUE)
  1        0      NA                                      0
  2        1      NA                                      1
  3       NA      NA                                      NA
  4        0      NA                                      0
  5       NA       1                                      1
  6       NA       0                                      0

If the columns contain only NA values I want to leave the NA values.

How I could achive this?

Upvotes: 4

Views: 90

Answers (5)

Ronak Shah
Ronak Shah

Reputation: 389265

Another base R approach.

If all the values in the rows are NA then return NA or else return sum of the row ignoring NA's.

#Select only the columns which we need
sub_df <- data[c("a", "x")]

sub_df$answer <- ifelse(rowSums(is.na(sub_df)) == ncol(sub_df), NA, 
                    rowSums(sub_df, na.rm = TRUE))

sub_df
#   a  x answer
#1  0 NA      0
#2  1 NA      1
#3 NA NA     NA
#4  0 NA      0
#5 NA  1      1
#6 NA  0      0

Upvotes: 0

Saurabh Chauhan
Saurabh Chauhan

Reputation: 3221

Base R (ifelse):

cbind(data$a,data$x,ifelse(is.na(data$a) & is.na(data$x),NA,rowSums(data[,1:2],na.rm = TRUE)))

If you are looking for the column name then replace cbind with cbind.data.frame

Output:

      [,1] [,2] [,3]
[1,]    0   NA    0
[2,]    1   NA    1
[3,]   NA   NA   NA
[4,]    0   NA    0
[5,]   NA    1    1
[6,]   NA    0    0

Upvotes: 3

rahul
rahul

Reputation: 591

base r ifelse

  data[['rowsum']]<-ifelse(is.na(data$a) & is.na(data$x),NA,ifelse(is.na(data$a),0,data$a)+ifelse(is.na(data$x),0,data$x))

     a  x  t rowsum
 1:  0 NA NA      0
 2:  1 NA  2      1
 3: NA NA NA     NA
 4:  0 NA NA      0
 5: NA  1  2      1
 6: NA  0  0      0

Upvotes: 0

r.user.05apr
r.user.05apr

Reputation: 5456

Base R:

data <- data.frame("a" = c(0,1,NA,0,NA,NA),
                   "x" = c(NA,NA,NA,NA,1,0),
                   "t" = c(NA,2,NA,NA,2,0)
)

yep <- cbind.data.frame( data$a, data$x, rs = rowSums(data[,c(1, 2)], na.rm = TRUE))
yep$rs[is.na(data$a) & is.na(data$x)] <- NA
yep

Upvotes: 4

markus
markus

Reputation: 26373

You might try dplyr::coalesce

cbind.data.frame( data$a, data$x, dplyr::coalesce(data$a, data$x))
#  data$a data$x dplyr::coalesce(data$a, data$x)
#1      0     NA                               0
#2      1     NA                               1
#3     NA     NA                              NA
#4      0     NA                               0
#5     NA      1                               1
#6     NA      0                               0

Upvotes: 3

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