Subtract one row from another row in df

Question

I have DF which looks like

DF
Nrow  a   b    c   d
1     0.1 0.2 0.3 0.4 
2      2   3   4   5
3      7   8   9   10

I want to subtract row 1 from row 2 and row 3.

How can i do it ? Thank you for any tips.

Updates

I saw this code: within-group differences from group member, and tried it as well.

Edited my data:

newdf <- df[!is.na(S[,1]),] ## df had NA values which was interfering with analysis, so I removed them.

df <- data.frame(treatment = rep(c('','baseline', 'treatment 1', 'treatment 2'), times=372),S[c(1:258)])

A <- df %>% mutate_each(funs(. - .[treatment=="baseline"]), -treatment) %>% filter(treatment!="baseline") ##have multiple columns for which I would like to calculate row-wise change

View(A)

However, now I thought to get correct results (or absolute change, i.e. row 2 - row 1), but the values are different from what I can calculate manually. Any thoughts?

Thanks!

Answers 11.03.2016

2-y Axes Plot with calculated absolute & relative Change in R

http://stackoverflow.com/questions/35781173/within-group-differences-from-group-member — rawr, Mar 09 '16 at 12:54

score 2 · Answer 1 · answered Mar 09 '16 at 12:53

2

If we need to subtract a single row from multiple rows, we can rep the the single row to make the dimension as that of the subset of dataset with multiple rows and then do the subtraction.

DF[2:3, -1]- DF[rep(1,2),-1]
#   a   b   c   d
#2 1.9 2.8 3.7 4.6
#3 6.9 7.8 8.7 9.6

data

DF <- structure(list(Nrow = 1:3, a = c(0.1, 2, 7), b = c(0.2, 3, 8), 
c = c(0.3, 4, 9), d = c(0.4, 5, 10)), .Names = c("Nrow", 
"a", "b", "c", "d"), class = "data.frame",
 row.names = c(NA, -3L))

answered Mar 09 '16 at 12:53

akrun

874,273
37
540
662

Thank you for your time. What if some of those values are NA? How can I omit them to calculate difference? Also, I am getting a `warning messages: In Ops.factor(left, right) : ‘-’ not meaningful for factors` – Aby Mar 09 '16 at 13:18
@Dr.AmitBansal When you post a dataset with numeric values and the question is to subtract between rows, we expect it to be `numeric` class. For some reason, your columns are `factor`. You can convert it to numeric as mentioned by cory in the comments. If there are NA values, you can replace those with 0 (if that makes sense) i.e. `DF1 <- replace(DF1, is.na(DF1), 0)` (after converting the columns to `numeric`). – akrun Mar 09 '16 at 16:49

score 0 · Answer 2 · answered Mar 09 '16 at 12:55

0

Use indexes to look at rows...

df <- read.table(textConnection("Nrow  a   b    c   d
1     0.1 0.2 0.3 0.4 
2      2   3   4   5
3      7   8   9   10"), stringsAsFactors=FALSE, header=TRUE)

df[1, ] - df[2, ]
# or assign the result to a new row...
df <- rbind(df, df[1, ] - df[2, ])

answered Mar 09 '16 at 12:55

cory

6,529
3
21
41

Thank you, @cory! What if some of those values are NA? How can I omit them to calculate difference? Also, I am getting a `warning messages: In Ops.factor(left, right) : ‘-’ not meaningful for factors` – Aby Mar 09 '16 at 13:22
Some of your columns are factors. If these are supposed to be numeric values, then you'll need to do a `as.numeric(as.character(your factor var))` – cory Mar 09 '16 at 13:36

score 0 · Answer 3 · answered Mar 09 '16 at 22:45

The following commands would perform the subtraction of 1st row from all the rows below, and will print the result of subtraction of 1st row from rows below.

 data = data.frame(x=c(1,5,7,10),y=c(3,2,4,1.1),z=1:4)
 data
 #    x    y  z
 # 1  1  3.0  1
 # 2  5  2.0  2
 # 3  7  4.0  3
 # 4 10  1.1  4

 for(i in 2:nrow(data)){
 result = data[i,] - data[1,]
 print (result)
 }

 #     x   y  z    
 # 2   4  -1  1     <--- 2nd row minus 1st row

 #     x   y  z
 # 3   6   1  2     <--- 3rd row minus 1st row

 #     x   y  z
 # 4   9 -1.9 3     <--- 4th row minus 1st row

Hope this helped. You can use the same commands for any number of rows in your data.

score 0 · Accepted Answer · answered Mar 22 '16 at 06:58

Answer 11.03.2016 #thought it might help others

This is how I finally did it:

library(dplyr) dft1= filter(df, df$time==1) dft2= filter(df, df$time==2) dft3= filter(df, df$time==3)

You might need to rename data frame or columns in accordance to your data set.

To calculate absolute change from second to first time point & third to first time point: abs1=dft2[33:290] - dft1[33:290]

abs2=dft3[33:290] - dft1[33:290]

To calculate relative change from second to first time point & third to first time point: rel1=abs1/dft1[33:290]*100

rel2=abs2/dft1[33:290]*100

Subtract one row from another row in df

4 Answers4

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