, an array if appropriate, by applying simplify2array(). Step 4: Combine the files using the bind_rows function from the dplyr library and the lapply and fread functions. Assign the result to names and years, respectively. We need to write our own function for lapply() to use. Arguments are recycled if necessary. The hardest part of using lapply() is writing the function that is to be applied to each piece. R matrix function tutorial covers matrix functions in R; apply function and sapply function with uses and examples to understand the concept thoroughly. To apply a function to multiple parameters, you can pass an extra variable while using any apply function.. The problem is that I often want to calculate several diffrent statistics of the data. Apply a function to multiple list or vector arguments Description. mapply is a multivariate version of sapply. This is the first cut at parallelizing R scripts. sapply is a user-friendly version and is a wrapper of lapply. Standard lapply or sapply functions work very nice for this but operate only on single function. In our case, the variables of interest are stored in columns 3 through 8 of our data frame. By default, sapply returns a vector, matrix or an array. The Apply family comprises: apply, lapply , sapply, vapply, mapply, rapply, and tapply. mapply applies FUN to the first elements of each ... argument, the second elements, the third elements, and so on. For example assume that we want to calculate minimum, maximum and mean value of each variable in data frame. But once, they were created I could use the lapply and sapply functions to ‘apply’ each function: > largeplans=c(61,63,65) lapply returns a list of the same length as X , each element of which is the result of applying FUN to the corresponding element of X . combined_files <- bind_rows(lapply(files, fread)) Here, I’m using the bind_rows function from the tidyverse libraries. 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