Thanks Stanton,
could you elaborate a bit on that - I'm not sure if I get exactly what
you mean.
if you have a smallish example would be great. the help from 'Igor
Tandetnik' with cast is a good starting point - but on selections with
max or min I still get the incorrect rounded numbers back.
EXAMPLE:column txt
"0.2009"
"10.200899"
"4.0"
"300.2009"
and I do a selection: SELECT max(CAST(txt AS REAL)) FROM test
it returns returns 300.2008999999999999
so the only solution till now seems to make a sub-query like: SELECT txt
FROM test WHERE txt=(SELECT max(CAST(txt AS REAL)) from test)
not sure how messy that might get in complex queries.
anyway for any suggestion I'm more than grateful
regards W.Braun
John Stanton wrote:
Our approach to that problem was to write a library of ASCII decimal
arithmetic functions, store the data as underlying type TEXT but give
them a declared type of DECIMAL(n,m) and have added functions which
understand that declared type. With that addition Sqlite becomes
useful for accounting and other such activities requiring arithmetic
accuracy.
For a simple display interface we use display format, fixed point
decimal numbers, right justified.
Mag. Wilhelm Braun wrote:
Dear all,
I use sqlite to store numerical text strings.
Why do I use text type: because of the float problem of
incorrection. example in numeric Columns: 3.2009 returns as
3.2008999999999999 which is not what I want.
Column Type=TEXT
is there a way to do comparison of text in a numerical way.
EXAMPLE rows:Column txt
"0.200899"
"1.2009"
"113.2008999"
"4.0"
"3.1"
"3.2009"
SELECT max(txt) FROM test
should return "113.2008999" and not "4.0"
ALSO:
SELECT * FROM test WHERE txt>10.0
should just return "113.2008999" and not
"113.2008999"
"4.0"
"3.1"
so my question is there a way to do that correctly?
Thanks for any helpful hints
regards W.Braun
by the way: I use pysqlite.
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