ds.cbind.RdTakes a sequence of vector, matrix or data-frame arguments and combines them by column to produce a data-frame.
ds.cbind(
x = NULL,
DataSHIELD.checks = FALSE,
force.colnames = NULL,
newobj = NULL,
datasources = NULL,
notify.of.progress = FALSE
)a character vector with the name of the objects to be combined.
logical. if TRUE does four checks:
1. the input object(s) is(are) defined in all the studies.
2. the input object(s) is(are) of the same legal class in all the studies.
3. if there are any duplicated column names in the input objects in each study.
4. the number of rows is the same in all components to be cbind.
Default FALSE.
can be NULL (recommended) or a vector of characters that specifies column names of the output object. If it is not NULL the user should take some caution. For more information see Details.
a character string that provides the name for the output variable
that is stored on the data servers. Defaults cbind.newobj.
a list of DSConnection-class objects obtained after login.
If the datasources argument is not specified
the default set of connections will be used: see datashield.connections_default.
specifies if console output should be produced to indicate progress. Default FALSE.
ds.cbind returns a data frame combining the columns of the R
objects specified in the function which is written to the server-side.
It also returns to the client-side two messages with the name of newobj
that has been created in each data source and DataSHIELD.checks result.
A sequence of vector, matrix or data-frame arguments is combined column by column to produce a data-frame that is written to the server-side.
This function is similar to the native R function cbind.
In DataSHIELD.checks the checks are relatively slow.
Default DataSHIELD.checks value is FALSE.
If force.colnames is NULL (which is recommended), the column names are inferred
from the names or column names of the first object specified in the x argument.
If this argument is not NULL, then the column names of the assigned data.frame have the
same order as the characters specified by the user in this argument. Therefore, the
vector of force.colnames must have the same number of elements as the columns in
the output object. In a multi-site DataSHIELD setting to use this argument, the user should
make sure that each study has the same number of names and column names of the input elements
specified in the x argument and in the same order in all the studies.
Server function called: cbindDS
if (FALSE) { # \dontrun{
## Version 6, for version 5 see the Wiki
# Connecting to the Opal servers
require('DSI')
require('DSOpal')
require('dsBaseClient')
builder <- DSI::newDSLoginBuilder()
builder$append(server = "study1",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM1", driver = "OpalDriver")
builder$append(server = "study2",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM2", driver = "OpalDriver")
builder$append(server = "study3",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM3", driver = "OpalDriver")
logindata <- builder$build()
# Log onto the remote Opal training servers
connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
# Example 1: Assign the exponent of a numeric variable at each server and cbind it
# to the data frame D
ds.exp(x = "D$LAB_HDL",
newobj = "LAB_HDL.exp",
datasources = connections)
ds.cbind(x = c("D", "LAB_HDL.exp"),
DataSHIELD.checks = FALSE,
newobj = "D.cbind.1",
datasources = connections)
# Example 2: If there are duplicated column names in the input objects the function adds
# a suffix '.k' to the kth replicate". If also the argument DataSHIELD.checks is set to TRUE
# the function returns a warning message notifying the user for the existence of any duplicated
# column names in each study
ds.cbind(x = c("LAB_HDL.exp", "LAB_HDL.exp"),
DataSHIELD.checks = TRUE,
newobj = "D.cbind.2",
datasources = connections)
ds.colnames(x = "D.cbind.2",
datasources = connections)
# Example 3: Generate a random normally distributed variable of length 100 at each study,
# and cbind it to the data frame D. This example fails and returns an error as the length
# of the generated variable "norm.var" is not the same as the number of rows in the data frame D
ds.rNorm(samp.size = 100,
newobj = "norm.var",
datasources = connections)
ds.cbind(x = c("D", "norm.var"),
DataSHIELD.checks = FALSE,
newobj = "D.cbind.3",
datasources = connections)
# Clear the Datashield R sessions and logout
datashield.logout(connections)
} # }