I don't know if anything like this is planned, but I wrote a hack to make 
it work: http://jsfiddle.net/asgallant/WaUu2/ 

On Thursday, June 21, 2012 2:02:26 AM UTC-4, Peetzer wrote:
>
> Thanks! I thought it would be like this. But actually this is adding a new 
> column, I solved this already in java but good to know this in javascript 
> too.
> I gives possibilities :)
>  
> Regards Peter
>  
> Ps, is also support planned for filtering on column (show only column 
> 'bananas' or 'tomatos') ? Like catergory filter but not only filter on 
> values.
> On Thu, Jun 21, 2012 at 5:24 AM, asgallant <[email protected]>wrote:
>
>> This is not explicitly supported, but you can hack around it using a 
>> DataView with calculated columns: 
>>
>> ​var view = new google.visualization.DataView(data);
>> view.setColumns([0, {
>>     label: 'bananas',
>>     type: 'number',
>>     calc: function (dt, row) {
>>         // if type = bananas, return this value, otherwise return null
>>         if (dt.getValue(row, 2) == 'bananas') {
>>             return dt.getValue(row, 1);
>>         }
>>         else {
>>             return null;
>>         }
>>     }
>> }, {
>>     label: 'tomatos',
>>     type: 'number',
>>     calc: function (dt, row) {
>>         // if type = tomatos, return this value, otherwise return null
>>         if (dt.getValue(row, 2) == 'tomatos') {
>>             return dt.getValue(row, 1);
>>         }
>>         else {
>>             return null;
>>         }
>>     }
>>     
>> }]);​ 
>>
>> Draw the chart using this view. 
>>
>>
>> On Wednesday, June 20, 2012 9:54:28 AM UTC-4, Peetzer wrote: 
>>>
>>> Is it possible to use column date (date), value (number) and group on 
>>> type (string) and show both types (legends) in graph ? 
>>>
>>> Column value contains all the values which belong to different types.
>>>
>>>
>>> Date                            value                type
>>> 20-06-2012 09:00          10                   'bananas'
>>> 20-06-2012 09:30          2                     'tomatos' 
>>> 20-06-2012 10:00          5                     'tomatos' 
>>> 20-06-2012 10:00          1                     'bananas' 
>>>
>>> Or is it only possible to use a column for each type?
>>>
>>>  Date                            value (label 'bananas')              
>>>  value2 (label 'tomatos')
>>> 20-06-2012 09:00          10                  
>>> 20-06-2012 09:30                                                       
>>>  2                      
>>> 20-06-2012 10:00                                                       
>>>  5 
>>> 20-06-2012 10:00          1
>>>
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>
>

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