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Anonymous
Not applicable

Qlik Sense filter a table without aggregation

Hi all,

I am trying to filter a table to only display rows with an InputType of 'Error'. This is really easy to do by simply clicking the table and filtering that column by error. But I would like to permanently apply that filter to that table.

If I did it through set analysis it would aggregate the data which is what I don't want. Example data looks like:


Header 1Header 2Header 3Header 4Header 4
DateVersionSiteErrorInputType
2017-12-092.5AAAThings brokeError
2017-12-092.3SSS0.74Stat
2017-12-072.3BBB0.65Stat
2017-11-312.1AAASomething went wrongError

I would only like to show all the individual rows with InputType = 'Error'.


Any help would be much appreciated.

Thanks

1 Solution

Accepted Solutions
devarasu07
Master II
Master II

Hi,

Method 1:Using back end script where clasue method

Fact:

LOAD * INLINE [

    Date, Version, Site, Error, InputType

    2017-12-09, 2.5, AAA, Things broke, Error

    2017-12-09, 2.3, SSS, 0.74, Stat

    2017-12-07, 2.3, BBB, 0.65, Stat

    2017-11-31, 2.1, AAA, Something went wrong, Error

] where InputType like '*Error*';


method 2: if it's only one chart object then u can create calculated dimension like below

=pick(wildmatch(InputType,'*Error*'),InputType)

make sure to suppress null value for this Cal.Dimension

Thanks,

Deva

View solution in original post

2 Replies
devarasu07
Master II
Master II

Hi,

Method 1:Using back end script where clasue method

Fact:

LOAD * INLINE [

    Date, Version, Site, Error, InputType

    2017-12-09, 2.5, AAA, Things broke, Error

    2017-12-09, 2.3, SSS, 0.74, Stat

    2017-12-07, 2.3, BBB, 0.65, Stat

    2017-11-31, 2.1, AAA, Something went wrong, Error

] where InputType like '*Error*';


method 2: if it's only one chart object then u can create calculated dimension like below

=pick(wildmatch(InputType,'*Error*'),InputType)

make sure to suppress null value for this Cal.Dimension

Thanks,

Deva

Anonymous
Not applicable
Author

Awesome, method 2 worked perfectly. Thank you.