If you look closely at your weekly graph, the curve does not go to zero.
Instead, it's missing. That's the effect of the null values.

Same with monthly, but more obvious.

>From what I'm seeing, your results reflect how SQL handles averages.


On Sat, Jun 3, 2023 at 7:11 PM 'Peter Fletcher' via weewx-user <
[email protected]> wrote:

> I would not expect the standard SQL behavior (ignoring nulls and averaging
> the rest of the values) to result in what I am seeing in the graphs, but
> you are probably right that I am going to have to define a specialty
> aggregation.
>
> On Saturday, June 3, 2023 at 8:10:26 PM UTC-4 Tom Keffer wrote:
>
>> WeeWX uses a SQL statement to calculate the averages. SQL ignores any
>> nulls in an aggregate interval. So, if there is nothing but nulls in an
>> interval, the result will be null, not zero.
>>
>> Null values signify unknown values, not zero. I didn't follow the
>> discussion of your service, but if you can't change it to store zero when
>> the value is, well, zero, then you'll have to define your own specialty
>> xtype aggregations, which treats null as a zero, perhaps by using the SQL
>> function IFNULL().
>>
>> Instructions on defining custom xtype aggregations:
>> https://github.com/weewx/weewx/wiki/xtypes#calculating-aggregates
>>
>>
>> On Sat, Jun 3, 2023 at 4:39 PM 'Peter Fletcher' via weewx-user <
>> [email protected]> wrote:
>>
>>> For reasons discussed elsewhere, I have a user service which saves
>>> nulls. rather than zeros to the archive records for UV and solar radiation
>>> values during the night. Daily and weekly graphs continue to look as they
>>> should (with the daytime tracings arising from at or very near to the zero
>>> axis). On the monthly graphs, however, the tracings do not touch the zero
>>> axis at either end of the daytime peak, I am guessing that, in calculating
>>> averaged data points for the longer term graphs, weewx is treating the
>>> average of any group of values that contains a null value as null. There is
>>> some logic to this, but the results are unhelpful in this case. Am I right
>>> about the cause of the problem, and is there a workaround for it?
>>>
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