• SFrame and SArray methods for conversion to NumPy arrays
• Added __pow__, __abs__, __neg__, __pos__ ops for SArray.
• Added more cumulative aggregates: Avg, Min, Max, Std, Var.
• Added rolling mean for SArray.
• Improved python lambda stability.
• Improved SSL certificate verification for S3 bucket access.
• Bug fixes.

Scalable tabular (SFrame, SArray) and graph (SGraph) data-structures built for out-of-core data analysis.

The SFrame package provides the complete implementation of:

• SFrame
• SArray
• SGraph
• The C++ SDK surface area (gl_sframe, gl_sarray, gl_sgraph)

Some of the key features of this package are.

• A scalable column compressed disk-backed dataframe optimized for machine learning and data science needs.
• Designed for both tabular (SFrame, SArray) as well as graph data (SGraph)
• Support for strictly typed columns (int, float, str, datetime), weakly typed columns (schema free lists, dictionaries) as well as specialized types such as Image.
• Uniform support for missing data.
• Query optimization and Lazy evaluation.
• A C++ API (gl_sarray, gl_sframe, gl_sgraph) with direct native access via the C++ SDK.
• A Python API (SArray, SFrame, SGraph) with an indirect access via an interprocess layer.