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I'm trying to teach myself basics of R and I couldn't find the answer:

Say, I have a csv file and I want to calculate weighted mean for each subject such that I have a mean mu = 0.015*1030+0.16*26930+0.24*0+0.87*250+0.29*310+0.77*6240+0.98*3730+0.98*0+0.08*1400 for Subject A, for example.

How would I accomplish it in R or Excel?

Also, if I need to multiply each pair by corresponding value from the same row from the column salary:

0.015*1030*111+0.16*26930*222+0.24*0*333+0.87*250*444+0.29*310*555+0.77*6240*666+0.98*3730*777+0.98*0*888+0.08*1400*999

Thanks

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UPDATE:

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Given your data is in DataFrame called df, you can simply do this: 

mu = sum(df$Probability * df$SubjectA * df$salary)
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  • $\begingroup$ Thank you! A stupid noob question: how do I create a new row containing mu for all subjects in the existing csv or at least generate a new csv with that data? Thanks! $\endgroup$
    – InfiniteLoop
    Dec 28, 2018 at 10:38
  • $\begingroup$ Assuming you mean a new column containing mu: df$mu = rep(sum(df$Probability * df$SubjectA * df$salary),nrow(df)) $\endgroup$
    – bradS
    Dec 28, 2018 at 11:16
  • $\begingroup$ I've updated the question with the actual dataset. It contains columns of states and rows of professions. There is also a column denoting how likely this occupation is to disappear due to automation. I want to calculate total job attrition for each state. Perhaps, it's be better to generate a new data frame with a list of states and total attrition (mu) for each one. How would I do it? Thanks $\endgroup$
    – InfiniteLoop
    Dec 28, 2018 at 12:36

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