factors

Original data frame: v1 = sample(letters[1:3], 10, replace=TRUE) v2 = sample(letters[1:3], 10, replace=TRUE) df = data.frame(v1,v2) df v1 v2 1 b c 2 a a 3 c c 4 b a 5 c c 6 c b 7 a a 8 a b 9 a c 10 a b New data frame: new_df = data.frame(row.names=rownames(df)) for (i in colnames(df)) { for (x in letters[1:3]) { #new_df[x] = as.numeric(df[i] == x) new_df[paste0(i, "_", x)] = as.numeric(df[i] == x) } } v1_a v1_b v1_c v2_a v2_b v2_c 1 0 1 0 0 0 1 2 1 0 0 1 0 0 3 0 0 1 0 0 1 4 0 1 0 1 0 0 5 0 0 1 0 0 1 6 0 0 1 0 1 0 7 1 0 0 1 0 0 8 1 0 0 0 1 0 9 1 0 0 0 0 1 10 1 0 0 0 1 0 For small datasets this

I want to do the opposite of this question , and sort of the opposite of this question , though that's about legends, not the plot itself. The other SO questions seem to be asking about how to keep unused factor levels. I'd actually like mine removed. I have several name variables and several columns (wide format) of variable attributes that I'm using to create numerous bar plots. Here's a reproducible example: library(ggplot2) df <- data.frame(name=c("A","B","C"), var1=c(1,NA,2),var2=c(3,4,5)) ggplot(df, aes(x=name,y=var1)) + geom_bar() I get this: I'd like only the names that have

An example of a non-settable function would be labels . You can only set factor labels when they are created with the factor function. There is no labels<- function. Not that 'labels' and 'levels' in factors make any sense.... > fac <- factor(1:3, labels=c("one", "two", "three")) > fac [1] one two three Levels: one two three > labels(fac) [1] "1" "2" "3" OK, I asked for labels, which one might assume were as set by the factor call, but I get something quite ... what's the word, unintuitive? > levels(fac) [1] "one" "two" "three" So it appears that setting labels is really setting levels. > fac

I want to find all the exact divisors of a number. Currently I have this: { int n; int i=2; scanf("%d",&n); while(i<=n/2) { if(n%i==0) printf("%d,",i); i++; } getch(); } Is there any way to improve it? Rndm First, your code should have the condition of i <= n/2 , otherwise it can miss one of the factors, for example 6 will not be printed if n=12. Run the loop to the square root of the number (ie. i <= sqrt(n) ) and print both i and n/i (both will be multiples of n). { int n; int i=2; scanf("%d",&n); while(i <= sqrt(n)) { if(n%i==0) { printf("%d,",i); if (i != (n / i)) { printf("%d,",n/i); } }

I have the following data.frame and I want to perform some calculations on the 2nd column. > test code age 1 101 15 2 102 25 3 103 16 4 104 u1 5 105 u1 6 106 u2 7 107 27 8 108 27 As you can see, the 2nd column does not include only numbers. I omitted these cases: > new<-subset(test,code<104 | code>106) > new code age 1 101 15 2 102 25 3 103 16 7 107 27 8 108 27 But when I try to do a calculation in a new column this is what I get: > new["MY_NEW_COLUMN"] <- NA > new code age MY_NEW_COLUMN 1 101 15 NA 2 102 25 NA 3 103 16 NA 7 107 27 NA 8 108 27 NA > new$MY_NEW_COLUMN <-new[,2] * 5 Warning

Is there an efficient algorithm to enumerate the factors of a number n , in ascending order, without sorting? By “efficient” I mean: The algorithm avoids a brute-force search for divisors by starting with the prime-power factorization of n . The runtime complexity of the algorithm is O( d log₂ d ) or better, where d is the divisor count of n . The spatial complexity of the algorithm is O( d ). The algorithm avoids a sort operation. That is, the factors are produced in order rather than produced out of order and sorted afterward. Although enumerating using a simple recursive approach and then

Numbers whose only prime factors are 2, 3 or 5 are called ugly numbers. Example: 1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 15, ... 1 can be considered as 2^0. I am working on finding nth ugly number. Note that these numbers are extremely sparsely distributed as n gets large. I wrote a trivial program that computes if a given number is ugly or not. For n > 500 - it became super slow. I tried using memoization - observation: ugly_number * 2, ugly_number * 3, ugly_number * 5 are all ugly. Even with that it is slow. I tried using some properties of log - since that will reduce this problem from