docs: fix typo in README, update roadmap + related projects (#613)

* docs: update readme + roadmap

* docs: update readme + roadmap

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
 

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).

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