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Hi, is there a way I can calculate a summary statistics for a columns matrix let say we have this matrix x <- matrix(sample(1:8000),nrow=100) colnames(x)<- paste("Col",1:ncol(x),sep="") if I used summary summary(x) i get the output for each column but I need the output to be in matrix with rownames and all the columns beside it this how I want it

Also, and possibly more constructively, when you get an error like > CI.c = predict(mod2, data.frame( `plant-density` = x), interval = 'c') # fail Error in eval(predvars, data, env) : object 'plant-density' not found you should check your assumptions. Does "newdata" actually contain a columnn called "plant-density": > head(data.frame( `plant-density`

"Thank you Rui. I didn't know about the check.names = FALSE argument. > Another good reminder to always read help, but I'm not sure I understood > what help to read in this case" ?data.frame , of course, which says: "check.names logical. If TRUE then the names of the variables in the data frame are checked to ensure that they are syntactically valid variable names

Dear all, I am pretty new to R only having an introduction course, so please bare with me. I am doing my PhD at The Max Planck Institute of Immunobiology where I am analyzing some calorimetry data from some mice. I have a spreadsheet consisting of measurements of the respiratory exchange rate at different time points measured every 9 minutes over some days. My goal is "bin"/average the