I have this vector (10x fold dilutions in replicates)
amount<-rep(c(0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001, 0.0000001), each = 3)
and want to adjust it based on the length of each column in the df, e.g. if CT_1 has 15 values, then the amount should be
amount<-rep(c(0.1, 0.01, 0.001, 0.0001, 0.00001), each = 3)
if CT3 HAS 20 values, then the amount should be
amount<-rep(c(0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001, 0.0000001), each = 3)
Since there is only 2 replicates for the amount 0.0000001 in CT_3, would it be a problem that each = 3 in amount?
but is there a way to control the size of rep for every different case (=the varying number of rows of any of the columns)?
CT_1 CT_2 CT_3 amount
<dbl> <dbl> <dbl> <dbl>
1 14.2 12.4 12.0 1
2 14.2 12.4 11.9 1
3 14.3 12.8 11.8 1
4 17.4 16.5 15.9 0.1
5 17.3 16.5 15.9 0.1
6 17.4 16.6 15.6 0.1
7 21.2 19.9 19.3 0.01
8 21.3 20.0 19.6 0.01
9 21.1 20.0 19.3 0.01
10 24.6 23.2 20.4 0.001
11 24.6 23.5 22.0 0.001
12 24.8 23.4 22.8 0.001
13 27.6 26.4 26.1 0.0001
14 27.8 26.5 26.1 0.0001
15 27.8 26.5 26.1 0.0001
16 NA 30.0 29.3 0.00001
17 NA 30.2 29.5 0.00001
18 NA 30.4 NA 0.00001
You can just simply get only n elements from the rep
# or check if number of not NA in your data
for (current_col in names(data)) {
col_data <- data[[current_col]]
col_data <- col_data[!is.na(col_data)]
# get number of row in your data
n_max <- length(col_data)
# Use length.out for control the size of rep
amount <- rep(c(0.1, 0.01, 0.001, 0.0001, 0.00001, 0.000001, 0.0000001),
each = 3, length.out = n_max)
# Your regression analysis code here
# ...
}