plyr

This has really challenged my ability to debug R code. I want to use ddply() to apply the same functions to different columns that are sequentially named; eg. a, b, c. To do this I intend to repeatedly pass the column name as a string and use the eval(parse(text=ColName)) to allow the function to reference it. I grabbed this technique from another answer. And this works well, until I put ddply() inside another function. Here is the sample code: # Required packages: library(plyr) myFunction <- function(x, y){ NewColName = "a" z = ddply(x, y, summarize, Ave = mean(eval(parse(text=NewColName)),

This question already has an answer here: Set certain values to NA with dplyr 4 answers I regularly need to change the values of a variable based on the values on a different variable, like this: mtcars$mpg[mtcars$cyl == 4] <- NA I tried doing this with dplyr but failed miserably: mtcars %>% mutate(mpg = mpg == NA[cyl == 4]) %>% as.data.frame() How could I do this with dplyr ? We can use replace to change the values in 'mpg' to NA that corresponds to cyl==4 . mtcars %>% mutate(mpg=replace(mpg, cyl==4, NA)) %>% as.data.frame() 来源： https://stackoverflow.com/questions/28013850/change-value-of

This question already has an answer here: How do I get a contingency table? 6 answers Faster ways to calculate frequencies and cast from long to wide 4 answers A seemingly easy problem is keeping me very busy. I have a data frame: > df1 Name Score 1 Ben 1 2 Ben 2 3 John 1 4 John 2 5 John 3 I would like to create a summary of the table like this: > df2 Name Score_1 Score_2 Score_3 1 Ben 1 1 0 2 John 1 1 1 So df2 must (i) only show unique "Names" and (ii) create columns from the unique factors in "Score" and (iii) count the number of times a person received said score. I have tried: df2 <- ddply