genMoreInfo {googlePublicData}

Generates a dataframe used to complement a DSPL bundle

Description

Parsing csv, tab or xls(x) files at a specific directory path, genMore info generates a dataframe used to complete a DSPL bundle with a more complete concepts definition including description, url, etc..

Usage

genMoreInfo(path, encoding = getOption("encoding"), sep = ";",
  output = NA, action = "merge", dec = ".")

Arguments

path

String. Path to the folder where the tables are saved.

encoding

The encoding of the files to be parsed.

sep

The separation character of the tables in the 'path' folder. Currently supports introducing the following arguments: “,” or “;” (for .csv files), “\t” (for .tab files) and “xls” or “xlsx” (for Microsoft's excel files).

output

If defined, the place where to save the dataframe as tab file. Otherwise it returns a data frame object.

action

Tells the function what to do if there's a copy of the file. Available actions are “merge” and “replace”.

dec

String. Decimal point.

Details

If there isn't any output defined (NA) the function returns a dataframe containing concepts as observations. Using this, the user may add more descriptive info about concepts. In turn it writes a tab file with the dataframe described above. The user may recycle this file writing “append” in the action argument.

Value

If no output defined, genMoreInfo returns a dataframe with the following columns.

id

XML id of the concept (autogenerated)

label

The label of the concept (autogenerated)

description

A brief description of the concept

topic

The topic of the concept

url

A URL for the concept where, for example, to get more info

totalName

A total name as specified by DSPL language (works for dimensional concepts)

pluralName

A total name as specified by DSPL language (works for dimensional concepts)

Author(s)

George G. Vega Yon

References

Google Public Data Explorer: http://publicdata.google.com

Examples

# Getting the path where all the datasets are
path <- system.file("dspl-tutorial", package="googlePublicData")
info <- genMoreInfo(path) # This is a dataframe

# Setting the 5th concept as topic "Demographics"
info[5, "topic"] <- "Demographics"

# Generating the dspl file
ans <- dspl(path, moreinfo = info)
ans

  ## Not run: 
    # Parsing some xlsx files at "my stats folder" to gen a "moreinfo" dataframe
    INFO <- genMoreInfo(path="my stats folder/", sep="xls")
    
    # Rows 1 to 10 are about "Poverty" and rows 11 to 20 about "Education"
    # So we fill the "topic" column with it.
    INFO$topic[1:10] <- "Poverty"
    INFO$topic[11:20] <- "Education"
    
    # Finally, we build the DSPL ZIP including more info
    dspl(path="my stats folder/", sep="xls", moreinfo=INFO)
    
  
## End(Not run)