>>>>>>Hello,
>>>>>>
>>>>>>I have a table with 1,500 records and with one column: ID, comprised of numeric data ranging from 1 - 1,591. As the
>>>>>>numbers get higher, the frequency of their appearance increases. But what's important, is not so much any given value
>>>>>>but how many numbers appear within a given range. And yes, I am trying to figure out a cutoff point that will separate
>>>>>>this table into the numbers that appear with the highest frequency (they happen to be larger numbers, in this table)
>>>>>>and numbers that appear less frequently (they happen to be smaller numbers.)
>>>>>>So, I want to know if certain values appear more often than others, kind of like a heat map, except the response would
>>>>>>be in a tabular form rather than in graphic.. Is there a way to use an SQL statement to do this? Can I preselect
>>>>>>the number of ranges and their size, for example: break the table up into 20 ranges. But I can't know
>>>>>>which values each of the 20 ranges will have in advance? I know it's a vague question but I wondered

>>>>>>what you all might say as this kind of question is coming up a lot.
>>>>>>
>>>>>>Thank you,
>>>>>>Steve
>>>>>
>>>>>Hi, Steve,
>>>>>
>>>>>Can you post the table structure (at least for the relevant columns)?
>>>>
>>>>table name: MY_IDS
>>>>field name: ID
>>>>data type: numeric
>>>>range of values in ID: 1 - 1,591
>>>>number of rows: 1,500
>>>>
>>>>(I tried to upload the dbf but the system won't allow it.)
>>>
>>>Try
>>>

>>>;with counts as (select Id, count(Id) as frequency
>>>from My_IDS
>>>group by Id)
>>>
>>>select *, NTILE(5) OVER (order by Frequency)
>>>from counts -- group into 5 different buckets in order of the frequency

>>>
>>>The above is for SQL Server.
>>
>>Naomi, Is the first line missing something, since it begins with:
>>
>>

>>;with counts as (select Id, count(Id) as frequency
>>

>>
>>Thanks, Steve
>
>Am I supposed to start the program with the first line, because I get an error when I do:
>
>;with counts as (select Id, count(Id) as frequency


I am using foxpro and mostly postgreSQL/postGIS