From b1ffab6f68ddbfd8aa88de776a18de297048eec0 Mon Sep 17 00:00:00 2001 From: Marco Edward Gorelli Date: Wed, 24 Jul 2024 12:03:15 +0100 Subject: [PATCH] docs: fix typo in README, update roadmap + related projects (#613) * docs: update readme + roadmap * docs: update readme + roadmap --- README.md | 2 +- docs/related.md | 14 -------------- docs/roadmap.md | 10 +++++----- 3 files changed, 6 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index bd85b56b8..a9954402f 100644 --- a/README.md +++ b/README.md @@ -72,7 +72,7 @@ There are three steps to writing dataframe-agnostic code using Narwhals: - if you started with Polars, you'll get Polars back - if you started with Modin, you'll get Modin back (and compute will be distributed) - if you started with cuDF, you'll get cuDF back (and compute will happen on GPU) - - if you started with PyArrow, you'll get PyArrow back (and compute will happen on GPU) + - if you started with PyArrow, you'll get PyArrow back ## Example diff --git a/docs/related.md b/docs/related.md index 682a18d42..38b0522d8 100644 --- a/docs/related.md +++ b/docs/related.md @@ -8,20 +8,6 @@ Standardised way of interchanging data between libraries, see Narwhals builds upon it by providing one level of support to libraries which implement it - this includes Ibis and Vaex. See [levels](levels.md) for details. -## DataFrame API Standard - -Now-discontinued project which aimed to "provide a standard interface that encapsulates implementation details of dataframe libraries. This will allow users and third-party libraries to write code that interacts and operates with a standard dataframe, and not with specific implementations.", see [here](https://data-apis.org/dataframe-api/draft/). - -The Narwhals author was originally involved, but left due to irreconcilable differences in vision, and -the project was ultimately abandoned. - -Some notable difference are: - -- Narwhals just uses a subset of the Polars API, whereas the dataframe standard introduces a new API -- Narwhals supports expressions, and separates lazy and eager execution -- Narwhals is a standalone, independent project, whereas the dataframe standard aimed to be upstreamed - and implemented by major dataframe libraries. - ## Array API Array counterpart to the DataFrame API, see [here](https://data-apis.org/array-api/2022.12/index.html). diff --git a/docs/roadmap.md b/docs/roadmap.md index 8ce877268..f0397ca34 100644 --- a/docs/roadmap.md +++ b/docs/roadmap.md @@ -1,8 +1,8 @@ # Roadmap -Priorities, as of June 2024, are: +Priorities, as of July 2024, are: -- add support for PyArrow -- works towards supporting projects which have shown interest in Narwhals: Altair, scikit-learn, shiny. -- make sure Narwhals' API coverage is enough to able to compute all (or at least, most of) the TPC-H - queries +- Works towards supporting projects which have shown interest in Narwhals: scikit-learn, shiny, tubular +- Implement when/then/otherwise so that Narwhals is API-complete enough to complete all the TPC-H queries +- Add support for extra backends such as Dask +- Add extra docs and tutorials to make the project more accessible and easy to get started with