Skip to main content

Stata Format

Description​

Stata is a statistical software package, and .dta files are Stata's native data file format. This implementation supports reading Stata files and converting them to Python dictionaries.

File Extensions​

  • .dta - Stata data files
  • .stata - Stata files (alias)

Implementation Details​

Reading​

The Stata implementation:

  • Uses pyreadstat library for reading
  • Reads Stata files and converts to pandas DataFrame, then to dictionaries
  • Supports metadata extraction (variable labels, value labels)
  • Requires file path (not stream)

Writing​

Writing is not currently supported for Stata format.

Key Features​

  • Statistical format: Designed for statistical analysis
  • Metadata support: Can extract variable labels and value labels
  • Totals support: Can count total rows
  • Type preservation: Maintains data types from Stata

Usage​

from iterable import open_iterable

# Basic reading
with open_iterable('data.dta') as source:
    for row in source:
        print(row)

Parameters​

No specific parameters required.

Limitations​

  1. Read-only: Stata format does not support writing
  2. pyreadstat dependency: Requires pyreadstat package
  3. File path required: Requires filename, not stream
  4. Flat data only: Only supports tabular data
  5. Memory usage: Entire file is loaded into memory

Compression Support​

Stata files can be compressed with all supported codecs:

  • GZip (.dta.gz)
  • BZip2 (.dta.bz2)
  • LZMA (.dta.xz)
  • LZ4 (.dta.lz4)
  • ZIP (.dta.zip)
  • Brotli (.dta.br)
  • ZStandard (.dta.zst)

Use Cases​

  • Statistical analysis: Working with Stata data files
  • Data migration: Converting Stata data to other formats
  • Research data: Processing research datasets in Stata format
  • Academic research: Common in academic research

Error Handling​

  • Missing dependency: optional libraries raise ImportError with an install hint (pip install 'iterabledata[<extra>]' when an extra exists).
  • Read-only: opening with mode="w" raises WriteNotSupportedError or ValueError.
  • Bad or unsupported input: may raise ValueError, OSError, or library-specific errors.
  • See Troubleshooting for decoding, detection, and engine issues.
  • SAS - SAS statistical format
  • SPSS - SPSS statistical format
  • CSV - Simple text format for conversion