Merge main

web/pandas/community/ecosystem.md

@@ -158,6 +158,19 @@ Plotly can be used as a pandas plotting backend via:
 pd.set_option("plotting.backend", "plotly")
 ```
 
+### IO engines
+
+Table with the third-party [IO engines](https://pandas.pydata.org/docs/development/extending.html#io-engines)
+available to `read_*` functions and `DataFrame.to_*` methods.
+
+  | Engine name     | Library                                               | Supported formats               |
+  | ----------------|------------------------------------------------------ | ------------------------------- |
+  |                 |                                                       |                                 |
+
+IO engines can be used by specifying the engine when calling a reader or writer
+(e.g. `pd.read_csv("myfile.csv", engine="myengine")`).
+
+
 ## Domain specific pandas extensions
 
 #### [Geopandas](https://github.com/geopandas/geopandas)
@@ -424,82 +437,9 @@ Pyjanitor provides a clean API for cleaning data, using method chaining.
 
 #### [Hamilton](https://github.com/dagworks-inc/hamilton)
 
-db-dtypes provides an extension types for working with types like
-DATE, TIME, and JSON from database systems. This package is used
-by pandas-gbq to provide natural dtypes for BigQuery data types without
-a natural numpy type.
-
-### [Pandas-Genomics](https://pandas-genomics.readthedocs.io/en/latest/)
-
-Pandas-Genomics provides an extension type and extension array for working
- with genomics data.  It also includes `genomics` accessors for many useful properties
- and methods related to QC and analysis of genomics data.
-
-### [Physipandas](https://github.com/mocquin/physipandas)
-
-Physipandas provides an extension for manipulating physical quantities
- (like scalar and numpy.ndarray) in association with a physical unit
- (like meter or joule) and additional features for integration of
- `physipy` accessors with pandas Series and Dataframe.
-
-### [Pint-Pandas](https://github.com/hgrecco/pint-pandas)
-
-Pint-Pandas provides an extension type for storing numeric arrays with units.
-These arrays can be stored inside pandas' Series and DataFrame. Operations
-between Series and DataFrame columns which use pint's extension array are then
-units aware.
-
-### [Text Extensions](https://ibm.biz/text-extensions-for-pandas)
-
-Text Extensions for Pandas provides extension types to cover common data structures for representing natural language data, plus library integrations that convert the outputs of popular natural language processing libraries into pandas DataFrames.
-
-## Accessors
-
-A directory of projects providing
-[extension accessors](https://pandas.pydata.org/docs/development/extending.html#registering-custom-accessors).
-This is for users to discover new accessors and for library
-authors to coordinate on the namespace.
-
-  | Library                                                              | Accessor   | Classes               |
-  | -------------------------------------------------------------------- | ---------- | --------------------- |
-  | [awkward-pandas](https://awkward-pandas.readthedocs.io/en/latest/)   | `ak`       | `Series`              |
-  | [pdvega](https://altair-viz.github.io/pdvega/)                       | `vgplot`   | `Series`, `DataFrame` |
-  | [pandas-genomics](https://pandas-genomics.readthedocs.io/en/latest/) | `genomics` | `Series`, `DataFrame` |
-  | [pint-pandas](https://github.com/hgrecco/pint-pandas)                | `pint`     | `Series`, `DataFrame` |
-  | [physipandas](https://github.com/mocquin/physipandas)                | `physipy`  | `Series`, `DataFrame` |
-  | [composeml](https://github.com/alteryx/compose)                      | `slice`    | `DataFrame`           |
-  | [gurobipy-pandas](https://github.com/Gurobi/gurobipy-pandas)         | `gppd`     | `Series`, `DataFrame` |
-  | [staircase](https://www.staircase.dev/)                              | `sc`       | `Series`, `DataFrame` |
-  | [woodwork](https://github.com/alteryx/woodwork)                      | `slice`    | `Series`, `DataFrame` |
-
-## IO engines
-
-Table with the third-party [IO engines](https://pandas.pydata.org/docs/development/extending.html#io-engines)
-available to `read_*` functions and `DataFrame.to_*` methods.
-
-  | Engine name     | Library                                               | Supported formats               |
-  | ----------------|------------------------------------------------------ | ------------------------------- |
-  |                 |                                                       |                                 |
-
-IO engines can be used by specifying the engine when calling a reader or writer
-(e.g. `pd.read_csv("myfile.csv", engine="myengine")`).
-
-## Development tools
-
-### [pandas-stubs](https://github.com/VirtusLab/pandas-stubs)
-
-While pandas repository is partially typed, the package itself doesn't expose this information for external use.
-Install pandas-stubs to enable basic type coverage of pandas API.
-
-Learn more by reading through these issues [14468](https://github.com/pandas-dev/pandas/issues/14468),
-[26766](https://github.com/pandas-dev/pandas/issues/26766), [28142](https://github.com/pandas-dev/pandas/issues/28142).
-
-See installation and usage instructions on the [GitHub page](https://github.com/VirtusLab/pandas-stubs).
-
-### [Hamilton](https://github.com/dagworks-inc/hamilton)
-
-Hamilton is a declarative dataflow framework that came out of Stitch Fix. It was designed to help one manage a
-Pandas code base, specifically with respect to feature engineering for machine learning models.
+Hamilton is a declarative dataflow framework that came out of Stitch Fix. It was
+designed to help one manage a Pandas code base, specifically with respect to
+feature engineering for machine learning models.
 
 It prescribes an opinionated paradigm, that ensures all code is: