Optimize code to read text-file with digits
Simplest version that I can think of:
x <- scan("~/Downloads/digits.txt")
x <- x[-seq(1,220000,11)]
length(x) # 200000
hist(x)
Now, because it's Friday:
How does one work out the theoretical distribution of the following table?
table(table(factor(x,levels=0:99999)))
0 1 2 3 4 5 6 7 8 9 10 11
13497 27113 27010 18116 9122 3466 1186 366 99 22 1 1
12
1
(I.e., out of 200000 random 5 digit numbers, 13497 numbers never occurred, 27113 numbers exactly once, and ... and 1 number occurred 12 times.)
-pd
On 8 Sep 2017, at 10:48 , Martin M?ller Skarbiniks Pedersen <traxplayer at gmail.com> wrote: Hi, Every day I try to write some small R programs to improve my R-skills. Yesterday I wrote a small program to read the digits from "A Million Random Digits" from RAND. My code works but it is very slow and I guess the code is not optimal. The digits.txt file downloaded from https://www.rand.org/pubs/monograph_reports/MR1418.html contains 20000 lines which looks like this: 00000 10097 32533 76520 13586 34673 54876 80959 09117 39292 74945 00001 37542 04805 64894 74296 24805 24037 20636 10402 00822 91665 00002 08422 68953 19645 09303 23209 02560 15953 34764 35080 33606 00003 99019 02529 09376 70715 38311 31165 88676 74397 04436 27659 00004 12807 99970 80157 36147 64032 36653 98951 16877 12171 76833 My program which is slow looks like this: filename <- "digits.txt" lines <- readLines(filename) numbers <- vector('numeric') for (i in 1:length(lines)) { # remove first column lines[i] <- sub("[^ ]+ +","",lines[i]) # remove spaces lines[i] <- gsub(" ","",lines[i]) # split the characters and convert them into numbers numbers <- c(numbers,as.numeric(unlist(strsplit(lines[i],"")))) } Thanks for any advice how this program can be improved. Regards Martin M. S. Pedersen [[alternative HTML version deleted]]
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Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com