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The filtering for text is case sensitive and is based on wildcards, using * as the wildcard character. If
By default if you don’t include the wildcard character in the filter field by default it one will be added to the end, so the filtering will only display rows that start with the text entered, but this can be disabled by setting stringFilterWildcard to false in the grid panel config.
If you want to display rows that contain the filter text in the middle then you need to add * to the start and the end. If you want to filter based on the text ending with the filter value then you just add the * at the start. To use an * in the filter, without it being interpreted as a wildcard placeholder, then you should precede it with the \ character. To use a \ in the filter before an * and have it interpreted as a slash followed by a wildcard, as opposed to an asterisk, use a double \.
If you don’t want to use a wildcard at all and search for the exact text entered then you need to can enclose the filter text in double-quotes, this will also disable the evaluation of \ and * characters and treat them and regular characters (and not escape or wildcard markers).
You can also combine two text filter if you want to match multiple values using | (pipe).
The following table shows the values the user enters and what the actual filter value will be, assuming stringFilterWildcard is true, which is the default, and what values the filter would match.
Entered Value | Filter Value | Matches |
|---|---|---|
WATSON CREEK | WATSON CREEK* | Values that start with “WATSON CREEK” |
WATSON CREEK* | WATSON CREEK* | Values that start with “WATSON CREEK” |
*WATSON CREEK | *WATSON CREEK | Values then end with “WATSON CREEK” |
*WATSON CREEK* | *WATSON CREEK* | Values that contain “WATSON CREEK” |
“WATSON CREEK” | “WATSON CREEK” | Values that are “WATSON CREEK” |
WATSON|FIDDLER | WATSON*|FIDDLER* | Values that start with “WATSON” or “FIDDLER” |
“WATSON”|FIDDLER | “WATSON”|FIDDLER | Values that are “WATSON” or start with “FIDDLER” |
*WATSON|”FIDDLER” | *WASTON|”FIDDLER” | Values that end with “WATSON” or are “FIDDLER” |
C\*Productions | C\*Productions* | Values that start with “C*Productions” |
*C\*Prod* | *C\*Prod* | Values that contain “C*Prod” |
“C*Productions” | “C*Productions” | Values that are “C*Productions” |
\* | \** | Values that begin with “*” |
*\** | *\** | Values that contain “*” |
*\* | *\* | Values that end with “*” |
*\\* | *\\* | Values that contain “\” |
\\* | \\* | Values that start with “\” |
\\\* | \\\* | Values that are “\*” |
“*” | “*” | Values that are “*” |
“\*” | “\*” | Values that are “\*” |
“\\\*” | “\\\*” | Values that are “\\\*” |
Numbers
If you’re filtering a column of numbers then just entering a number will filter the rows that match that value, there is no wildcard as for a text field. If you want to include numbers less than, less than or equal, greater than or greater than or equal then you can precede the value with <, <=, > or >=, or use <> for not equal.
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Column Type | Entered Value | Matches |
|---|---|---|
Date | <20191014 | Before 12:00am 14 Oct 2019 |
<201910 | Before 12:00am 1 Oct 2019 | |
<2019 | Before 12:00am 1 Jan 2019 | |
<=20191014 | Before 12:00am 15 Oct 2019 | |
>20191014 | At or after 12:00am 15 Oct 2019 | |
>=20191014 | At or after 12:00am 14 Oct 2019 | |
<>20191014 | Before 12:00am 14 Oct 2019 or at or after 12:00am 15 Oct 2019 | |
20191014 | At or after 12:00am 14 Oct 2019 and before 12:00am 15 Oct 2019 | |
>=20191014 <20191021 | At or after 12:00am 14 Oct 2019 and before 12:00am 21 Oct 2019 | |
<20191014 | >= 20191021 | Before 12:00am 14 Oct 2019 or at or after 12:00am 21 Oct 2019 | |
201902 | 201905 | At or after 12:00am 1 Feb 2019 and before 12:00am 1 March 2019 or at or after 12:00am 1 May 2019 and before 12:00am 1 June 2019 | |
Time | <1430 | Before 2:30pm |
<=1430 | At or before 2:30pm | |
>1430 | At or after 2:31pm | |
>= 1430 | At or after 2:30pm | |
<>1430 | Before 2:30pm or at or after 2:31pm | |
>=14 <16 | At or after 2:00pm and before 4:00pm | |
<14 | >=16 | Before 2:00pm or at or after 4:00pm |
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Time filtering with SQL Server
If when filtering data from a SQL Server database you receive errors about the data types time and datetime being incompatible you can resolve this by setting sendTimeAsDatetime to false as a parameter in the connection URL, e.g.
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