datareader is a pure Go (Golang) package that can read binary SAS format (SAS7BDAT) and Stata format (dta) data files into native Go data structures. For non-Go users, there are command line utilities that convert SAS and Stata files into text/csv and parquet files.

The Stata reader is based on the Stata documentation for the dta file format and supports dta versions 115, 117, and 118.

There is no official documentation for SAS binary format files. The code here is translated from the Python sas7bdat package, which in turn is based on an R package. Also see here for more information about the SAS7BDAT file structure.

This package also provides a simple column-oriented data container called a Series. Both the SAS reader and Stata reader return the data as an array of Series objects, corresponding to the columns of the data file. These can in turn be converted to other formats as needed.

Both the Stata and SAS reader support streaming access to the data (i.e. reading the file by chunks of consecutive records).

Here is an example of how the SAS reader can be used in a Go program (error handling omitted for brevity):

import (
        "datareader"
        "os"
)

// Create a SAS7BDAT object
f, _ := os.Open("filename.sas7bdat")
sas, _ := datareader.NewSAS7BDATReader(f)

// Read the first 10000 records (rows)
ds, _ := sas.Read(10000)

// If column 0 contains numeric data
// x is a []float64 containing the dta
// m is a []bool containing missingness indicators
x, m, _ := ds[0].AsFloat64Slice()

// If column 1 contains text data
// x is a []string containing the dta
// m is a []bool containing missingness indicators
x, m, _ := ds[1].AsStringSlice()

Here is an example of how the Stata reader can be used in a Go program (again with no error handling):

import (
        "datareader"
        "os"
)

// Create a StataReader object
f,_ := os.Open("filename.dta")
stata, _ := datareader.NewStataReader(f)

// Read the first 10000 records (rows)
ds, _ := stata.Read(10000)

The package includes a CSV reader with type inference for the column data types.

import (
        "datareader"
)

f, _ := os.Open("filename.csv")
rt := datareader.NewCSVReader(f)
rt.HasHeader = true
dt, _ := rt.Read(-1)
// obtain data from dt as in the SAS example above

We provide two command-line utilities allowing conversion of SAS and Stata datasets to other formats without using Go directly. Executables for several OS's and architectures are contained in the bin directory. The script used to cross-compile these binaries is build.sh. To build and install the commands for your local architecture only, run the Makefile (the executables will be copied into your GOBIN directory).

The stattocsv command converts a SAS7BDAT or Stata dta file to a csv file, it can be used as follows:

> stattocsv file.sas7bdat > file.csv
> stattocsv file.dta > file.csv

The columnize command takes the data from either a SAS7BDAT or a Stata dta file, and writes the data from each column into a separate file. Numeric data can be stored in either binary (native 8 byte floats) or text format (binary is considerably faster).

> columnize -in=file.sas7bdat -out=cols -mode=binary
> columnize -in=file.dta -out=cols -mode=text

We provide a simple and efficient way to convert a SAS7BDAT file to parquet format, using the parquet-go package. To convert a SAS file called 'mydata.sas7bdat' to Parquet format, begin by running sas_to_parquet as follows:

sas_to_parquet -sasfile=mydata.sas7bdat -outdir=. -structname=MyStruct -pkgname=mypackage

If you want the Parquet file for use outside of Go, you can specify any values for structname and pkgname. The sas_to_parquet command generates a Go program called 'convert_data.go' that you can use to perform the data conversion.

The parquet file will be written to the specified destination directory, which in the above example is the current working directory. The parquet file name will be based on the SAS file name, e.g. in the above example it will be 'mydata.parquet'.

To facilitate reading the Parquet file into Go using the parquet-go package, a Go struct definition will be written to the directory specified by 'mypackage' above. See the sas_to_parquet_check.go script to see how to read the file into Go using these struct definitions.

Automated testing is implemented against the Stata files used to test the pandas Stata reader (for versions 115+):

https://github.com/pydata/pandas/tree/master/pandas/io/tests/data

A CSV data file for testing is generated by the gendat.go script. There are scripts make.sas and make.stata in the test directory that generate SAS and Stata files for testing. SAS and Stata software are required to run these scripts. The generated files are provided in the test_files/data directory, so go test can be run without having access to SAS or Stata.

The columnize_test.go and stattocsv_test.go scripts test the commands against stored output.

Please file an issue if you encounter a file that is not properly handled. If possible, share the file that causes the problem.