ds.reShape {dsBaseClient}

R Documentation

Reshapes server-side grouped data

Description

Reshapes a data frame containing longitudinal or otherwise grouped data from 'wide' to 'long' format or vice-versa.

Usage

ds.reShape(
  data.name = NULL,
  varying = NULL,
  v.names = NULL,
  timevar.name = "time",
  idvar.name = "id",
  drop = NULL,
  direction = NULL,
  sep = ".",
  newobj = "newObject",
  datasources = NULL
)

Arguments

data.name	a character string specifying the name of the data frame to be reshaped.
varying	names of sets of variables in the wide format that correspond to single variables in 'long' format.
v.names	the names of variables in the 'long' format that correspond to multiple variables in the 'wide' format.
timevar.name	the variable in 'long' format that differentiates multiple records from the same group or individual. If more than one record matches, the first will be taken.
idvar.name	names of one or more variables in 'long' format that identify multiple records from the same group/individual. These variables may also be present in 'wide' format.
drop	a vector of names of variables to drop before reshaping. This can simplify the resultant output.
direction	a character string that partially matched to either 'wide' to reshape from 'long' to 'wide' format, or 'long' to reshape from 'wide' to 'long' format.
sep	a character vector of length 1, indicating a separating character in the variable names in the 'wide' format. This is used for creating good v.names and times arguments based on the names in the varying argument. This is also used to create variable names when reshaping to 'wide' format.
newobj	a character string that provides the name for the output object that is stored on the data servers. Default reshape.newobj.
datasources	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.

Details

This function is based on the native R function reshape. It reshapes a data frame containing longitudinal or otherwise grouped data between 'wide' format with repeated measurements in separate columns of the same record and 'long' format with the repeated measurements in separate records. The reshaping can be in either direction. Server function called: reShapeDS

Value

ds.reShape returns to the server-side a reshaped data frame converted from 'long' to 'wide' format or from 'wide' to long' format. Also, two validity messages are returned to the client-side indicating whether the new object has been created in each data source and if so whether it is in a valid form.

Author(s)

DataSHIELD Development Team

Examples

## Not run: 

 ## Version 6, for version 5 see Wiki
  # Connecting to the Opal servers
  
  require('DSI')
  require('DSOpal')
  require('dsBaseClient')
  
  builder <- DSI::newDSLoginBuilder()
  builder$append(server = "study1", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "SURVIVAL.EXPAND_NO_MISSING1", driver = "OpalDriver")
  builder$append(server = "study2", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "SURVIVAL.EXPAND_NO_MISSING2", driver = "OpalDriver")
  builder$append(server = "study3",
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "SURVIVAL.EXPAND_NO_MISSING3", driver = "OpalDriver")
  logindata <- builder$build()
  
  # Log onto the remote Opal training servers
  connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D") 
  
  #Reshape server-side grouped data
  
  ds.reShape(data.name = "D", 
             v.names = "age.60", 
             timevar.name = "time.id",
             idvar.name = "id",
             direction = "wide",
             newobj = "reshape1_obj",
             datasources = connections)
  
  # Clear the Datashield R sessions and logout
  datashield.logout(connections) 

## End(Not run)

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