ds.dataFrame {dsBaseClient}

R Documentation

Generates a data frame object in the server-side

Description

Creates a data frame from its elemental components: pre-existing data frames, single variables or matrices.

Usage

ds.dataFrame(
  x = NULL,
  row.names = NULL,
  check.rows = FALSE,
  check.names = TRUE,
  stringsAsFactors = TRUE,
  completeCases = FALSE,
  DataSHIELD.checks = FALSE,
  newobj = NULL,
  datasources = NULL,
  notify.of.progress = FALSE
)

Arguments

x	a character string that provides the name of the objects to be combined.
row.names	NULL, integer or character string that provides the row names of the output data frame.
check.rows	logical. If TRUE then the rows are checked for consistency of length and names. Default is FALSE.
check.names	logical. If TRUE the column names in the data frame are checked to ensure that is unique. Default is TRUE.
stringsAsFactors	logical. If true the character vectors are converted to factors. Default TRUE.
completeCases	logical. If TRUE rows with one or more missing values will be deleted from the output data frame. Default is FALSE.
DataSHIELD.checks	logical. Default FALSE. If TRUE undertakes all DataSHIELD checks (time-consuming) which are: 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 of the data frames or matrices and the length of all component variables are the same
newobj	a character string that provides the name for the output data frame that is stored on the data servers. Default dataframe.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.
notify.of.progress	specifies if console output should be produced to indicate progress. Default is FALSE.

Details

It creates a data frame by combining pre-existing data frames, matrices or variables.

The length of all component variables and the number of rows of the data frames or matrices must be the same. The output data frame will have the same number of rows.

Server functions called: classDS, colnamesDS, dataFrameDS

Value

ds.dataFrame returns the object specified by the newobj argument which is written to the serverside. Also, two validity messages are returned to the client-side indicating the name of the newobj that has been created in each data source and if it is in a valid form.

Author(s)

DataSHIELD Development Team

Examples

## Not run: 

  ## 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") 
  
  # Create a new data frame
  ds.dataFrame(x = c("D$LAB_TSC","D$GENDER","D$PM_BMI_CATEGORICAL"),
               row.names = NULL,
               check.rows = FALSE,
               check.names = TRUE,
               stringsAsFactors = TRUE, #character variables are converted to a factor 
               completeCases = TRUE, #only rows with not missing values are selected
               DataSHIELD.checks = FALSE,
               newobj = "df1",
               datasources = connections[1], #only the first Opal server is used ("study1")
               notify.of.progress = FALSE)


  # Clear the Datashield R sessions and logout
  datashield.logout(connections) 

## End(Not run)

---