XPT.jl

Read SAS® software transport files and convert datasets to DataFrames in julia.
Popularity
1 Star
Updated Last
3 Years Ago
Started In
February 2014

XPT

Build Status

NOTE Requires the master version of DataFrames. Get that with Pkg.checkout("DataFrames"). I don't know how to specify that in the REQUIRE file.

About

The XPT package reads SAS® software transport files and converts SAS software datasets to DataFrames. Transport files are assumed to follow the specifications described in the technical note tiled "THE RECORD LAYOUT OF A DATA SET IN SAS TRANSPORT (XPORT) FORMAT" available here (pdf).

Datasets are tagged with member type SASDATA in transport files. No other member types are referenced in the tech note, so I am assuming they cannot exist (in a transport file). If this is not the case, you'll get an error. Please file an issue and send me a an example of an offending transport file, if possible.

Character variables in a dataset are converted to {ASCIIString}s. Missing character variables in SAS datasets are just empty strings, and are treated as such here.

SAS software numeric variables are not standard IEEE Float64s and can be shorter than 8 bytes and can have missing values. (Twenty-eight kinds in fact: ._, ., .a, ..., .z.) All numeric variables are converted to Float64s unless they are missing. All missing values are treated as DataArrays.NA.

NOTE Currently, only the first dataset found in a transport file is read and converted to a dataframe, even if the transport file has more than one dataset. If you need to access a dataset after the first in a transport file and I haven't gotten around to adding support for that yet, please file an issue.

Usage

Open a transport file (and process the header information):

xpt = XPTFile("path/to/xpt")

or

f = open("path/to/xpt")
xpt = XPTFile(f)

Convert the first SAS dataset in an xpt file to a dataframe:

df = readdf(xpt)

Future work

  • Convert all datasets in a transport file after the first to julia DataFrames
  • Or only a selection, indexing by name or number.
  • Add some useful tests.
  • Make it go faster. I assume my implementation is slow but I haven't benchmarked it.
  • Subset observations in a dataset by index before converting to DataFrame.
  • Maybe interface with DataStreams to read datasets sequentially.