As advised, I used some code samples in another forum but it could not improve the problem. My question is the “ error in plot.window(…) : need finite ‘xlim’ values ” in r- how to solve it? Command line is:
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In the process of completing my work, I encountered the following problem: Error in grid.Call(L_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : Polygon edge not found In addition: Warning messages: 1: In grid.Call(L_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : ...
I am tired of fixing the problem: error in file(file, “rt”) : invalid ‘description’ argument in the r; even if I get the reference from another forum, it still returns an error: Error in file(file, "rt") : ...
As advised, I used some code samples in another forum but it could not improve the problem. My question is the “ error in eval(family$initialize) : y values must be 0 <= y <= 1 ” in r- how to ...
I am new to r and searching the “error in colmeans(x, na.rm = true) : ‘x’ must be numeric” to understand it better. It seems it doesn’t work as expected when I used some suggestions before. This is the command ...
I get the error message: Error in confusionMatrix.default(pred, testing$Final) : the data and reference factors must have the same number of levels Has anyone ever faced this problem? How to troubleshoot the “ error: `data` and `reference` should ...
How to check – error in xy.coords(x, y, xlabel, ylabel, log) : ‘x’ and ‘y’ lengths differ? I have the sample detail: var1 = c(10, 12, 8, 8, 7) var2 = c(30, 21, 50, 4, 9, 54, ...
I am tired of fixing the problem: error in chartodate(x) : character string is not in a standard unambiguous format in the r; even if I get the reference from another forum, it still returns an error:
I get an error [1] NA Warning message: In mean.default(results) : argument is not numeric or logical: returning NA` when trying to calculate mean (a data frame with two columns). How to fix the argument is not numeric ...
I get the error message: Error in eval(predvars, data, env) : numeric 'envir' arg not of length one > predict(model, df$Total, interval="confidence") Error in eval(predvars, data, env) : numeric 'envir' ...