dhis2-users team mailing list archive

[Jason Pickering <jason.p.pickering@xxxxxxxxx>]

Hi Eric,

Nice to see someone else looking to use R and DHIS2. :)

Another way of getting the orgunit Hierarchy is with something like this.

https://play.dhis2.org/demo/api/organisationUnits?fields=uid,parent[id],name,level,path

Once you have the parent ID you can then generate the entire tree structure
. The "path" also provides the full hierarchy of the position of a given
orgunit within the hierarchy. Once you have either of these, it would be
possible to generate the hierarchical structure pretty easily in R I think
(although I have not written the code to do it!).

I think your approach will work, but in general, the API can aggregate the
data for you (depending on how you would like to aggregate it). Otherwise,
if you make a lot of loops on the server, it could be a lot of data, and
could potentially put the server under stress (depending on the level of
usage of course). In general, I think it would make sense to try and only
ask for what you need, if that is possible, and supported by the API. This
will run a lot quicker (on the server and in R). This of course, all
depends on the scale of what you are asking for and if you need to perform
some type of filtering (such as outliers, bad data, etc) prior to
aggregation, which the server may not perform.


Also, be aware, that when getting indicators from DHIS2, you do not get the
data values which compose the indicators. Thus, any aggregation which you
would perform would likely be significantly different than DHIS2, because
when DHIS2 aggregates the data, it does so with a weighted average, as
opposed to an un-weighted average (which would be the only possibility
since you are getting the  percentages here rather than both the numerator
and denominator).

I hacked your example a bit to make it a bit quicker. You can test the
output on RFiddle here <http://www.r-fiddle.org/#/fiddle?id=QLAOB1hp>.

Hope this helps to get you started.

Regards,
Jason





On Mon, Nov 23, 2015 at 3:46 PM, Alex Tumwesigye <atumwesigye@xxxxxxxxx>
wrote:

> Dear Eric,
>
> Something like this  should assist to generate the metadata
>
> http://YOUR_URLl/api/organisationUnits.json?paging=false&fields=id,name,parent[id,name,parent[id,name,parent[id,name]]]&filter=level:EQ:5
>
>
> The above will generate the orgunit hierachy at level 5 (lowest level) up
> to level 2. Note how I use the parent[id,name]
>
> Alex
>
> On Mon, Nov 23, 2015 at 5:35 PM, Eric Green <epgreen@xxxxxxxxx> wrote:
>
>> I had a side conversation with Jason Pickering about using R to access
>> the web API, and I’m moving the conversation to the mailing list to
>> document it for others.
>>
>> I asked Jason for guidance on modifying the API url to import data into
>> R. Prior to contacting Jason, I reviewed this documentation
>> <https://www.dhis2.org/doc/snapshot/en/developer/html/apas07.html> and his
>> presentation <https://github.com/jason-p-pickering/dhis2RIntegration> on
>> R/DHIS2 integration (great stuff!). Jason was nice enough to create this
>> example <http://www.r-fiddle.org/#/fiddle?id=wHglXleC&version=1> that
>> showed me how to use the pivot table app, copy the API url using
>> Firefox/Chrome developer tools, and use the pre-filled URL in R as a
>> template.
>>
>> I wanted to do more with organization units, so I modified Jason’s
>> example here: https://gist.github.com/ericpgreen/bb7fcb55efd8c93d3451.
>>
>> I might not be approaching the problem the right way, but my general
>> approach is to define a set of periods (monthly) and organizational units
>> and then loop over a set of indicators to create a data frame for each
>> indicator that has values by unit (row) and period (column). Then in R (not
>> shown), I will transform each data frame from wide to long and then combine
>> the data frames for each indicator into a larger data frame for analysis.
>>
>> I would like to have the data at the lowest level possible so I can later
>> aggregate at higher organization unit levels (e.g., counties) and periods
>> (e.g., years) as needed. I know I could just request these aggregations via
>> the API, but I am accustomed to working with datasets at the lowest level
>> and doing manipulations in my code so I can follow the process more closely
>> (I’m new to APIs).
>>
>> *My current question is how to obtain the metadata that indicates the
>> organizational hierarchy of units.* When I define urlD in my code, I’d
>> like to automatically grab all facility OU’s where county==2, for instance.
>> I know I could do this if I had something like the following table. Right
>> now I specify each OU manually. Having this table would allow me to build
>> the API url programmatically.
>>
>> Also, in the data frame that is created, I only know that an observation
>> is linked to facility 5, for instance, but I don’t have the metadata to
>> show that facility 5 is in sub county 3 which is in county 2 of country 1.
>> So having this table would let me aggregate on my end later.
>>
>> Of course suggestions on improving my general approach are also welcome!!
>>
>>
>>
>>
>>
>>
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>>
>
>
> --
> Alex Tumwesigye
>
> Technical Advisor - DHIS2 (Consultant),
> Ministry of Health/AFENET
> Kampala
> Uganda
>
> IT Consultant - BarefootPower Uganda Ltd, SmartSolar, Kenya
>
> IT Specialist (Servers, Networks and Security, Health Information Systems
> - DHIS2 ) & Solar Consultant
>
> +256 774149 775, + 256 759 800161
>
> "I don't want to be anything other than what I have been - one tree hill "
>
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>


-- 
Jason P. Pickering
email: jason.p.pickering@xxxxxxxxx
tel:+46764147049