I'd also argue that it's a nice shortcut but you should ALWAYS select only
what's needed. A select fetching 20 columns just to display the data from
one column only will ALWAYS perform worse than a select fetching that only
column.
On Wednesday, May 28, 2014 1:35:03 PM UTC+2, Anthony wrote:
>
> Note, in trunk there is now a new .column method for the Rows object,
> which allows you to extract a single column as a list of values
> (internally, it just does a list comprehension, as in my original answer).
> So, in this case you could do:
>
> nums3 = db(db.Measures).select(orderby=db.Measures.measure_date_time).
> column('measure_value')
>
> You can also pass a field object to .column:
>
> nums3 = db(db.Measures).select(orderby=db.Measures.measure_date_time).
> column(db.Measures.measure_value)
>
> Also, if you don't pass any argument to .column, it will return the first
> column, which is convenient if your database select returns only a single
> column:
>
> nums3 = db().select(db.Measures.measure_value, orderby=db.Measures.
> measure_date_time).column()
>
> Anthony
>
> On Monday, May 26, 2014 1:21:15 PM UTC-4, Anthony wrote:
>>
>> You can do:
>>
>> nums3 = [r.measure_value for r in db().select(db.Measures.measure_value)]
>>
>> The .select() returns a Rows object, which acts like a list of Row
>> objects -- if you want to extract just a single value from each Row object,
>> you have to iterate through the Rows object and pull each value out.
>>
>> Note, depending on what you are doing, you can instead operate on the
>> Rows object itself (rather than generating a list and then operating on the
>> list). For example, to randomize the order:
>>
>> import random
>> random_rows = db(db.Measures).select().sort(lambda r: random.random())
>>
>> Anthony
>>
>> On Monday, May 26, 2014 6:20:07 AM UTC-4, Syd Stewart wrote:
>>>
>>> Hi
>>>
>>> What is the simplest way please to select a column of figures (floats
>>> and int) into a list, so I can manipulate the list e.g randomise the order
>>>
>>> nums3 = db(db.Measures).select( db.Measures.measure_value,
>>> orderby=db.Measures.measure_date_time)
>>>
>>> meannums= sum(nums3)/float(len(nums3))
>>>
>>> This calculation of the mean keeps giving me an error
>>>
>>> File "/home/sydstewart/web2py/applications/SydOwn/controllers/test.py"
>>> <https://sydstewart.pythonanywhere.com/admin/default/edit/SydOwn/controllers/test.py>,
>>> line 92, in cusum
>>> qnum[i][k] = (nums3[k]) - (meannums)
>>> TypeError: unsupported operand type(s) for -: 'Row' and 'int'
>>>
>>>
>>> Thanks
>>>
>>>
>>>
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