WebFeb 17, 2015 · These answers are all vectors, whereas the title of the post says "list". To check if a list of logicals evaluates to TRUE, simply unlist () before checking. > x <- list (rep (TRUE, 5), FALSE) > y <- list (rep (TRUE, 6)) > all (x) Error: 'list' object cannot be coerced to type 'logical' In addition: Warning message: In all (x) : coercing ... WebApr 10, 2024 · How can I use an if-statement for an object when creating a list (for creating an interaction variable using mutate in dplyr)? Please see the example data below. # Example data set.seed (1) x <- sample (1:2, 10, replace = T) y <- sample (1:2, 10, replace = T) z <- sample (1:2, 10, replace = T) df <- data.frame (x, y, z) condition <- list ...
Filtering rows where all columns contain the same data in R
WebFeb 21, 2024 · Note: You can find the complete documentation for the filter function in dplyr here. Additional Resources. The following tutorials explain how to perform other common … WebFeb 8, 2024 · 6. This questions must have been answered before but I cannot find it any where. I need to filter/subset a dataframe using values in two columns to remove them. In the examples I want to keep all the rows that are not equal (!=) to both replicate "1" and treatment "a". However, either subset and filter functions remove all replicate 1 and all ... shipps fire
R check if a list of TRUE/FALSE values evaluate to TRUE
WebAug 10, 2024 · The solution should yield the following data frame: x ID Hour 1 A 0 2 A 2 3 A 5 4 A 6 5 A 9 6 B 0 7 B 2 8 B 5 9 B 6. All values of ID C were dropped because it was missing Hour 5. Note that I want to keep all values of Hour for ID s that match testVector. A dplyr solution would be ideal, but any solution is welcome. WebThey are required to remove 99.97 percent of all tiny particles in the United States with a diameter of fewer than 0.3 microns. Even though HEPA filters are not graded on the MERV scale, their filtration capacities are far higher than those of MERV 16. So, filtration systems with HEPA filters might be helpful for those who suffer from severe ... WebI prefer following way to check whether rows contain any NAs: row.has.na <- apply (final, 1, function (x) {any (is.na (x))}) This returns logical vector with values denoting whether there is any NA in a row. You can use it to see how many rows you'll have to drop: sum (row.has.na) and eventually drop them. questions to ask at an nhs interview