Introduction to Datatable

H2O’s datatable is a Python package for manipulating 2-dimensional tabular data structures (aka, data frames). It is close in spirit to pandas or SFrame; however we put specific emphasis on speed and big data support. As the name suggests, the package is closely related to R’s data.table and attempts to mimic its core algorithms and API.

Currently datatable is in the Alpha stage and is undergoing active development. The API may be unstable; some of the core features are incomplete and/or missing.

Contributing

datatable is an open source project released under the Mozilla Public Licence v2. Open Source projects live by their user and developer communities. We welcome and encourage your contributions of any kind!

No matter what your skill set or level of engagement is with datatable, you can help others by improving the ecosystem of documentation, bug report and feature request tickets, and code.

We invite anyone who is interested to contribute, whether through pull requests, or tests, or GitHub issues, API suggestions, or generic discussion.

Have Questions?

If you have questions about using datatable, post them on Stack Overflow using the [datatable] [python] tags at http://stackoverflow.com/questions/tagged/datatable+python.

Installation

• Installation
  • Requirements
  • Install on Mac OS X
  • Install on Linux
  • Build from Source
  • Troubleshooting

Common Tasks

• Using datatable
  • Create Frame
  • Convert a Frame
  • Parse Text (csv) Files
  • Write the Frame
  • Save a Frame
  • Basic Frame Properties
  • Compute Per-Column Summary Stats
  • Select Subsets of Rows/Columns
  • Delete Rows/Columns
  • Filter Rows
  • Compute Columnar Expressions
  • Sort Columns
  • Perform Groupby Calculations
  • Append Rows/Columns

Python API

• Python API
  • Frame

Indices and tables

• Index
• Module Index
• Search Page