Mean is just sum(col)/count(col)
Mode can be calculated with having, max, count
Median can be computed by sorting, using a cursor, and going to the
middle.
There are more efficient and better (more accurate) ways to do it, but
those have to be implemented at a low level. Of course, since you have
libpq, anything is possible.
If you want to implement these things at a low level to get better
answers, Kahan (or compenstated) summation is a good idea, and do the
summation into a larger type to prevent loss of precision.
Here are some statistical templates I wrote that are free for any
purpose you like:
ftp://cap.connx.com/pub/tournament_software/Kahan.Hpp
ftp://cap.connx.com/pub/tournament_software/STATS.HPP
The Cephes collection by Moshier has good extended precision types, if
you need to carefully avoid any PLOSS.
For median, the QuickSelect algorithm is very good. Here is an
implementation I wrote in C++:
#include <cstdio>
#include <cstdlib>
#include <iostream>
using namespace std;
/*
**
** In the following code, every reference to CLR means:
**
** "Introduction to Algorithms"
** By Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest
** ISBN 0-07-013143-0
*/
/*
** CLR, page 187
*/
template < class Etype >
Etype
RandomSelect(Etype A[], size_t p, size_t r, size_t i)
{
size_t q,
k;
if (p == r)
return A[p];
q = RandomPartition(A, p, r);
k = q - p + 1;
if (i <= k)
return RandomSelect(A, p, q, i);
else
return RandomSelect(A, q + 1, r, i - k);
}
size_t RandRange(size_t a, size_t b)
{
size_t c = (size_t) ((double) rand() / ((double) RAND_MAX +
1) * (b - a));
return c + a;
}
/*
** CLR, page 162
*/
template < class Etype >
size_t
RandomPartition(Etype A[], size_t p, size_t r)
{
size_t i = RandRange(p, r);
Etype Temp;
Temp = A[p];
A[p] = A[i];
A[i] = Temp;
return Partition(A, p, r);
}
/*
** CLR, page 154
*/
template < class Etype >
size_t
Partition(Etype A[], size_t p, size_t r)
{
Etype x,
temp;
size_t i,
j;
x = A[p];
i = p - 1;
j = r + 1;
for (;;) {
do {
j--;
} while (!(A[j] <= x));
do {
i++;
} while (!(A[i] >= x));
if (i < j) {
temp = A[i];
A[i] = A[j];
A[j] = temp;
} else
return j;
}
}
double data[30];
int main(void)
{
size_t i;
size_t size = sizeof(data) / sizeof(data[0]);
for (i = 0; i < size; i++) {
data[i] = rand();
}
for (i = 0; i < size; i++) {
cout << data[i] << endl;
}
cout << "1st item is " << RandomSelect(data, 0, size - 1, 0) <<
endl;
cout << "2nd item is " << RandomSelect(data, 0, size - 1, 1) <<
endl;
cout << "3rd item is " << RandomSelect(data, 0, size - 1, 2) <<
endl;
for (i = 4; i < size; i++)
cout << i << "th item is " << RandomSelect(data, 0, size - 1,
i) << endl;
return 0;
}
-----Original Message-----
From: pgsql-general-owner@postgresql.org
[mailto:pgsql-general-owner@postgresql.org] On Behalf Of Hrishikesh
Deshmukh
Sent: Friday, March 18, 2005 10:37 AM
To: Postgresql-General
Subject: [GENERAL] Statistics with PostgreSQL
Hi All,
Is there a way to simple statistics like mean/median/mode in PostgreSQL.
I have tables like PsetID | IntensityValue. I want to find out mean
(intensityValue) of some PsetID(s)?!
Any urls/pointers/books would be a big help.
Thanks,
Hrishi
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