Row-wise sum for columns with certain names

Question

I have a sample data:

SampleID  a      b     d     f       ca      k     l    cb
1         0.1    2     1     2       7       1     4    3
2         0.2    3     2     3       4       2     5    5
3         0.5    4     3     6       1       3     9    2

I need to find row-wise sum of columns which have something common in names, e.g. row-wise sum(a, ca) or row-wise sum(b,cb). The problem is that i have large data.frame and ideally i would be able to write what is common in column header, so that code would pick only those columns to sum

Thank you beforehand for any assistance.

akrun · Accepted Answer · 2016-02-29 07:20:19Z

2

We can select the columns that have 'a' with grep, subset the columns and do rowSums and the same with 'b' columns.

 rowSums(df1[grep('a', names(df1)[-1])+1])
 rowSums(df1[grep('b', names(df1)[-1])+1])

answered Feb 29, 2016 at 7:20

akrun

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15 Comments

Try Over a year ago

Could it be modified so that it returns matrix, data.frame and position of columns is not +1 all the time. So, could be the code a bit more general.

Try Over a year ago

I clicked! Thank you! But i don't have much reputation yet, it to be appeared. But i really did!

Try Over a year ago

Thank you. But could you please explain me a bit more.How can i modify your code to sum rows of columns which are for example 7 columns away from each other?

akrun Over a year ago

@OlgaAnufrieva The grep gives the column index of the columns that have the same pattern in the column name. I added 1 to the grep output because I was grepping on the subset of dataset that doesn't include the first column. So, if I understand your comment, it should work.

Try Over a year ago

Thanks a lot for the help!

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Peter K · Accepted Answer · 2016-02-29 10:23:18Z

If you want the output as a data frame, try using dplyr

# Recreating your sample data
df <- data.frame(SampleID = c(1, 2, 3),
             a = c(0.1, 0.2, 0.5),
             b = c(2, 3, 4),
             d = c(1, 2, 3),
             f = c(2, 3, 6),
             ca = c(7, 4, 1),
             k = c(1, 2, 3),
             l = c(4, 5, 9),
             cb = c(3, 5, 2))

Process the data

# load dplyr
library(dplyr)

# Sum across columns 'a' and 'ca' (sum(a, ca))
df2 <- df %>%
    select(contains('a'), -SampleID) %>% # 'select' function to choose the columns you want 
    mutate(row_sum = rowSums(.)) # 'mutate' function to create a new column 'row_sum' with the sum of the selected columns. You can drop the selected columns by using 'transmute' instead.

df2 # have a look

    a ca row_sum
1 0.1  7     7.1
2 0.2  4     4.2
3 0.5  1     1.5

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