R识别数据框中的第一个值，并通过从新列的数据框中的所有值中添加/减去该值来创建新变量

Question

I know this question may have been already answered elsewhere and apologies for repeating it if so but I haven't found a workable answer as yet.

I have 17 subjects each with two variables as below:

Time (s)    OD
130        41.48
130.5      41.41
131        39.6
131.5      39.18
132        39.41
132.5      37.91
133        37.95
133.5      37.15
134        35.5
134.5      36.01
135        35.01

I would like R to identify the first value in column 2 (OD) of my dataframe and create a new column (OD_adjusted) by adding or subtracting (depending if the first value is +ive or -ive) from all values in column 2 so it would look like this:

    Time (s)    OD      OD_adjusted 
130            41.48     0
130.5          41.41    -0.07
131            39.6     -1.88
131.5          39.18    -2.3
132            39.41    -2.07
132.5          37.91    -3.57
133            37.95    -3.53
133.5          37.15    -4.33
134            35.5     -5.98
134.5          36.01    -5.47
135            35.01    -6.47

First value in column 2 is 41.48 therefore I want to subtract this value from all datapoints in column 2 to create a new third column (OD_adjusted).

I can use OD_adjusted <- ((df$OD) - 41.48) however, I would like to automate the process using a function and this is where I am stuck:

AUC_OD <- function(df){

return_value_1 = df %>%
  arrange(OD) %>%
  filter(OD [1,2) %>%
  slice_(1)
colnames(return_value_1)[3] <- "OD_adjusted"


if (nrow(return_value_1) > 0 ) { subtract 
   (return_value_1 [1,2] #into new row

     else add
     (return_value_1 [1,2] #into new row

}

Answer 1

We get the first element of 'OD' and subtract from the column

library(dplyr)
df1 %>%
   mutate(OD_adjusted = OD- OD[1])

---

Or using base R

df1$OD_adjusted <- with(df1, OD - OD[1])