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I have a problem which i'm finding tricky to solve . I have a data frame that looks like this :
Date	treatment	AVG("one.Other.Other.Other.Other.Other")	avg("k__Bacteria.p__Actinobacteria.c__Actinobacteria.o__Actinomycetales.f__Actinomycetaceae.g__Actinomyces")	avg("k__Bacteria.p__Actinobacteria.c__Actinobacteria.o__Bifidobacteriales.f__Bifidobacteriaceae.g__Bifidobacterium")
25.7.2021	Original Sample	0	5.28E-05	0.08379538
29.7.2021	Treatment 1	0	0	0.38547496
29.7.2021	Treatment 10	0	0	0.589164539
29.7.2021	Treatment 2	0	0	0.282869579
29.7.2021	Treatment 3	0	0	0.251450878
29.7.2021	Treatment 4	0	0	0.736359499
29.7.2021	Treatment 5	0	0	0.305756115
29.7.2021	Treatment 6	0	0	0.281702441
29.7.2021	Treatment 7	0	0	0.491254245
29.7.2021	Treatment 8	0	0	0.325992622
29.7.2021	Treatment 9	0	0	0.434048894

It has 89 columns. What I wish to do is create a new data frame which will contain all the columns and the observation values will be for any column : (treatment 1 of column x/original sample of column x) (treatment 2 of column x/original sample of column x) and so on for all the 10 treatments and doing this calculations for all columns

I thought about doing nested for loops but is doesn't seem to work.

What I have tried:

data_slope=for(i in 3:ncol(data_work_final)) {       
  for(j in length(data_work_final[i]) {
    data_slope$data_work_final[i[j]]=data_work_final[i[j]]/data_work_final[data_work_final[i[1]]
    
  }
}
Posted
Updated 28-Nov-21 22:16pm
v2

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