Why make completely random numbers? For bank numbers and ssn, often a mechanism
is used to minimize the risk of typos. That is, typos often yield a non-existent
code. Below is a little program to generate numbers that are "modulus 11 proof"
http://docs.hp.com/en/32209-90024/apds02.html. There are various ways to do
this ( I used a 'control digit' method). Check the code because I just cobbled
def isValidSsn(ssnNum, nDigits = 9):
ssn = str(ssnNum).zfill(nDigits)
sigma = 0
for n, digit in enumerate(ssn[:-1]):
sigma += (len(ssn) - n) * int(digit)
check = int(ssn[-1])
if sigma % 11 == check:
def makeSsns(outfile = "c:/temp/ssn.txt", n = 20, offset = 10000):
with open(outfile, "wb") as f:
nSsn = 0
ssn = 0 + offset
ssn += 1
sigma = 0
nSsn += 1
f.write(str(ssn).zfill(9) + os.linesep)
if nSsn == n:
makeSsns(n = 20)
All right, but apart from the sanitation, the medicine, education, wine, public
order, irrigation, roads, a fresh water system, and public health, what have the
Romans ever done for us?
From: Justin Carroll <firstname.lastname@example.org>
Sent: Mon, September 27, 2010 8:19:33 PM
Subject: Re: [SPSSX-L] generating random (not consecutive) identification
I'll respond with some Python (and maybe pure sytanx ways) a bit later today
(assuming I remember!!), but I often direct my students to use Random.org. This
website uses "atmospheric static" to generate seemingly random numbers (it uses
static in addition to some choice algorithms which plays on the age-old argument
if true-randomization even exists). As such, there are some options via this
website (random.org) which allow you create upwards to millions of cases (or so
I think I remember seeing) of consecutive random numbers (aka non repeating
numbers). You can also specific the range so if you a 6 digit random non
repeating ID, you can select 100,000-999,999, and it'll give a list of random
non-repeating numbers. Furthermore, I believe there is an export option (if not
copy and paste often works well enough for smaller generations).
This is quick, dirty, and I think just as good as using any randomization
techniques that SPSS or Python can derive.
In writing this, I can see a process in which you generate the $casenum, as
you've done in the past, and use a random algorithm in SPSS (pure syntax) to
select from the available cases you already generated (thus picking from the set
of numbers at random, and reordering them based on their ordinal selection: aka
the first case selected might be 642,324 which goes at the top of the column).
Interesting thought! I'll play around with it tonight/tomorrow (hopefully!) and
get back to you if one of the listers doesn't respond with a more cogent
Check out random.orgthough (specifically http://www.random.org/sequences/), I
don't see why this couldn't work in your situation as a quick solution
(specifics of your situation notwithstanding).
J. R. Carroll
Grad. Student in Pre-Doc Psychology at CSUS
Research Assistant for Just About Everyone.
Email: email@example.com -or- firstname.lastname@example.org
Phone: (916) 628-4204
On Mon, Sep 27, 2010 at 11:04 AM, Debbie Hahs-Vaughn <email@example.com> wrote:
I have used COMPUTE ID=$CASENUM to generate consecutive identification
>numbers. However how can I generate identification numbers that are not
>consecutive but just purely random? I am trying to avoid having numbers
>that are only one digit difference in the ID so that there is less room for
>error in what we are trying to do. Thanks!
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