Error in plot.window(...) : need finite 'xlim' values

The error "error in plot.window(...) : need finite 'xlim' values" typically occurs when you are trying to create a plot in the R programming language and the xlim parameter (which specifies the range of the x-axis) is set to NA (not available) or contains infinite values.

To fix this error, you will need to make sure that the xlim parameter is set to a pair of finite values. You can do this by specifying the xlim parameter directly in the plot function, or by using the xlim function within the plot function.

For example, if you are using the plot function to create a scatterplot, you can specify the xlim parameter as follows:

Copy codeplot(x, y, xlim = c(0, 100))

This will set the x-axis range to values between 0 and 100.

Alternatively, you can use the xlim function within the plot function to set the x-axis range:

Copy codeplot(x, y) xlim(0, 100)

This will have the same effect as specifying the xlim parameter directly in the plot function.

If you are still encountering the "need finite 'xlim' values" error after specifying the xlim parameter, it is possible that the data you are plotting contains infinite values. In this case, you will need to identify and remove the infinite values from your data before creating the plot. You can use the is.finite function to identify infinite values in your data, and then use the na.omit function to remove them.

For example:

Copy codex[!is.finite(x)] <- NAy[!is.finite(y)] <- NAx <- na.omit(x)y <- na.omit(y)plot(x, y, xlim = c(0, 100))

This code will replace any infinite values in x and y with NA, and then remove the NA values using the na.omit function. This will ensure that the plot function has only finite values to work with, and should allow you to create the plot without encountering the "need finite 'xlim' values" error.

What is R programming and most common question answers according to that?

R is a programming language and software environment for statistical computing and graphics. It is widely used by data scientists, statisticians, and researchers to explore, analyze, and visualize data.

Some common questions and answers about R programming include:

  1. What can I do with R?

R is a powerful tool for a wide range of tasks, including data manipulation, statistical modeling, data visualization, machine learning, and more. It is particularly useful for tasks that involve working with large datasets, as it has a range of functions and packages for efficiently manipulating and analyzing data.

  1. How do I get started with R?

To get started with R, you will need to install the R software on your computer. You can download the latest version of R from the Comprehensive R Archive Network (CRAN) website ( Once you have installed R, you can open the R console and start typing R commands.

  1. How do I learn R?

There are many resources available to help you learn R, including online tutorials, textbooks, and courses. Some popular resources include the R documentation (, the R tutorial on the DataCamp website (, and the R programming course on Coursera (

  1. What are some good packages to use in R?

There are many useful packages available for R, which can be used to extend the capabilities of the base R software. Some popular packages include dplyr for data manipulation, ggplot2 for data visualization, caret for machine learning, and tidyverse for a suite of data manipulation and visualization tools.

  1. How do I get help with R?

If you have a question about R, you can try searching the R documentation or online forums such as Stack Overflow. You can also ask other R users for help by posting a question on an R-specific forum or mailing list.

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