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Hello Avi, while something like d$something <- ... may seem like you're directly modifying the data it does not actually do so. Most R objects try to be immutable, that is, the object may not change after creation. This guarantees that if you have a binding for same object the object won't change sneakily. There is a data structure that is in fact mutable which are environments. For

On 4/6/23 03:49, Steven Yen wrote: > The RStudio list generally does not respond to free version users. I was hoping someone one this (R) list would be kind enough to help me. I don't think that is true. It is perhaps true that you cannot get personalized help from employed staff, but you can certainly submit to the Q&A forum. -- David > > Steven from iPhone > >>

I may be missing something but using the plain old c() combine function seems to work fine: df <- data.frame(left = 1:5, right = 6:10) df.combined <- data.frame(comb = c(df$left, df$right)) df left right 1 1 6 2 2 7 3 3 8 4 4 9 5 5 10 df.combined comb 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 -----Original

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It's still hard to figure out what you want. If you have two vectors you can compute their (2x2) covariance matrix using cov(cbind(x,y)). If you want to compute all pairwise squared differences between elements of x and y you could use outer(x, y, "-")^2. Can you explain a little bit more about (1) the context for your question and (2) why you want/need to use apply() ? On

Hi, I have a table of x rows and y columns. The table is huge and so i'd like to create a subset of the data containing rows where any of the y values are below a threshold, say 1e-4. Is there a simple way of doing this in R? thanks Rich