{"repo":"h2oai/datatable","free":true,"listed":false,"github":"https://github.com/h2oai/datatable","clone":"git clone https://github.com/h2oai/datatable.git","description":"A Python package for manipulating 2-dimensional tabular data structures","language":"C++","stars":1876,"topics":["python","data-analysis","data-structure","performance","ftrl","fedramp"],"license":"MPL-2.0","category":"dev-tools","readme_excerpt":"datatable This 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. Requirements: Python 3.6+ (64 bit) and pip 20.3+. Project goals datatable started in 2017 as a toolkit for performing big data (up to 100GB) operations on a single-node machine, at the maximum speed possible. Such requirements are dictated by modern machine-learning applications, which need to process large volumes of data and generate many features in order to achieve the best model accuracy. The first user of datatable was [Driverless.ai][]. The set of features that we want to implement with datatable is at least the following: Column-oriented data storage. Native-C implementation for all datatypes, including strings. Packages such as pandas and numpy already do that for numeric columns, but not for strings. Support for date-time and categorical types. Object type is also supported, but promotion into object discouraged. All types should support null values, with as little overhead as possible. Data should be stored on disk in the same format as in memory. This will allow us to memory-map data on disk and work on out-of-memory datasets transparently. Work with memory-mapped datasets to avoid loading into memory more data than nece","default_branch":null,"files":null,"tree":[],"storefront":"/r/h2oai","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/h2oai/datatable/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}