=== modified file 'src/docbkx/en/dhis2_r.xml'
--- src/docbkx/en/dhis2_r.xml 2012-05-23 14:54:01 +0000
+++ src/docbkx/en/dhis2_r.xml 2012-06-01 06:01:20 +0000
@@ -446,9 +446,18 @@
require(RCurl)
require(XML)
#Just a URL with some data
-url<-"https://apps.dhis2.org/dev/api/reportTables/data.csv?de=fbfJHSPpUQD&de=cYeuwXTCPkU&in=Uvn6LCg7dVU&ou=O6uvpzGd5pu&last12Months=true"
+
+url<-"https://apps.dhis2.org/dev/api/reportTables/data.csv?
+de=fbfJHSPpUQD
+&de=cYeuwXTCPkU
+&in=Uvn6LCg7dVU
+&ou=O6uvpzGd5pu
+&last12Months=true"
#Lets get the response and we do not need the headers
-response<-getURL(url,userpwd="admin:district",httpauth = 1L, header=FALSE)
+#This site has some issues with its SSL certificate
+#so lets not verify it.
+response<-getURL(url,userpwd="admin:district"
+,httpauth = 1L, header=FALSE,ssl.verifypeer = FALSE)
#Unquote the data
data<-noquote(response)
#here is the data.
@@ -458,10 +467,12 @@
Here, we have shown how to get some aggregate data from the DHIS2 demo database using the DHIS2's Web API.
In the next code example, we will retrieve some metadata, namely a list of data elements and their unique identifiers.
#Get the list of data elements. Turn off paging and links
+#This site has some issues with its SSL certificate
+#so lets not verify it.
url<-"https://apps.dhis2.org/dev/api/dataElements.xml?
paging=false&links=false"
response<-getURL(url,userpwd="admin:district",
-httpauth = 1L, header=FALSE)
+httpauth = 1L, header=FALSE,ssl.verifypeer = FALSE)
#We ned to parse the result
bri<-xmlParse(response)
#And get the root
@@ -474,9 +485,10 @@
#but we need to be careful for missing attribute values
foo<-cbind(de_names,de_id)
#Recast this as a data frame
-data_elements<-as.data.frame(foo,stringsAsFactors=FALSE,row.names=1:nrow(foo))
+data_elements<-as.data.frame(foo,
+stringsAsFactors=FALSE,row.names=1:nrow(foo))
head(data_elements)
- Note that the values which we are interested in are stored as XML attributes and were parsed into two seperate matrices and then combined together into a single data frame.
+ Note that the values which we are interested in are stored as XML attributes and were parsed into two separate matrices and then combined together into a single data frame.