On Thu, May 27, 2010 at 11:45 AM, Bob Jolliffe <bobjolli...@gmail.com> wrote:
> We've talked before about integrating scripting engine (such as R)
> into dhis : http://www.rforge.net/rscript/
>
> But my guess is that most R users are going to be of a level of
> sophistication that they would be most comfortable doing the kind of
> thing you describe - conecting directly to db with r client and doing
> their stuff.
>
> OTOH if there were sufficiently useful "canned" dhis R scripts which
> could take some number crunching load off the jvm and produce canned
> useful analysis then that would be different.
In fact Ola and I earlier had discussions with someone who had
integrated R scripts in his own Access based system, but would have
been delighted to switch to DHIS2 as the platform if we could
accommodate the scripts.
And it would be a way to quite quickly enhance the analytical
capabilities, if DHIS2 came with a set of good scripts - perhaps after
being refined and generalized through the more ad hoc process Jason
describes. And one could imagine most of the "plumbing tasks" could
have been taken care of, leaving a simpler and more efficient
interface for a wider audience.
Knut
> Sadly I don't know sufficient about R to know. But I sense it ...
>
> Regards
> Bob
>
> On 27 May 2010 10:08, Jason Pickering <jason.p.picker...@gmail.com> wrote:
>> Hi everyone. I have had a recent question from a user about how DHIS2
>> can be used with R. I am including a trivial example here about how to
>> use R as as a client to access data and produce a graph in DHIS2.
>>
>> Just get a copy of R and install the DBI and RPostregSQL packages with
>>
>>>install.packages()
>>
>>
>> After that, just connect to the DB, retrieve your data (in this case
>> from a report table) and produce a graph.
>>
>>>library(DBI)
>>
>>>library(RPostgreSQL)
>>
>>>drv <- dbDriver("PostgreSQL")
>>
>>>con <- dbConnect(drv, dbname="dhis2_zm_prod2", user="postgres",
>>>password="postgres")
>>
>>>rs <- dbSendQuery(con, "SELECT * FROM _report_malaria_indicators_district
>>>where
>> organisationunitid = 3904")
>>
>>>data <- fetch(rs,n=-1)
>>
>>>barplot(data$malaria_confirm_incidence,
>>>names.arg=as.character(data$periodname),
>>>main=as.character(data$organisationunitname[1]),las=2)
>>
>>>dev.print(png, file="/home/jason/test.png")
>>
>> Regards,
>> Jason
>>
>> ---
>> Jason P. Pickering
>> email: jason.p.picker...@gmail.com
>> tel:+260968395190
>>
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>
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--
Cheers,
Knut Staring
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