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 Møller Skarbiniks Pedersen
> <traxpla...@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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> and provide commented, minimal, self-contained, reproducible code.
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd....@cbs.dk Priv: pda...@gmail.com
______________________________________________
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