Prepare 0.6 release (#53)

* add some decoration icons to homepage * prepare release
arviz-devs · Jul 10, 2023 · 4d9b8c7 · 4d9b8c7
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diff --git a/docs/source/changelog.md b/docs/source/changelog.md
@@ -1,6 +1,6 @@
 # Change Log
 
-## v0.x.x (Unreleased)
+## v0.6.0 (2023 Jul 11)
 ### New features
 * {func}`.ecdf` now returns a DataArray to be compatible with {meth}`~xarray.Dataset.map` {pull}`47`
 * Added `.linalg` and `.einops` accessors for `DataArray` objects {pull}`51`

diff --git a/docs/source/index.md b/docs/source/index.md
@@ -57,29 +57,29 @@ and around [einops](https://einops.rocks/) with an api and features adapted to x
 :gutter: 3
 
 ::::{grid-item-card}
-Label aware
+{material-outlined}`bookmarks;1.1em` Label aware
 ^^^
 
 Apply operations over named dimensions.
 Automatically aligns and broadcasts inputs,
 and preserves dimensions and coordinates.
 ::::
 ::::{grid-item-card}
-Interoperability
+{material-outlined}`hub;1.1em` Interoperability
 ^^^
 
 Wrappers in xarray-einstats are designed to be minimal
 to preserve as many features from xarray as possible,
 for example, Dask support.
 ::::
 ::::{grid-item-card}
-Batched operations
+{material-outlined}`backup_table;1.1em` Batched operations
 ^^^
 
 All operations can be batched over one or multiple dimensions.
 ::::
 ::::{grid-item-card}
-Flexible inputs
+{material-outlined}`mediation;1.1em` Flexible inputs
 ^^^
 
 DataArrays, Datasets and even GroupBy xarray objects can

diff --git a/docs/source/tutorials/einops-basics-port.ipynb b/docs/source/tutorials/einops-basics-port.ipynb
diff --git a/docs/source/tutorials/linalg_tutorial.ipynb b/docs/source/tutorials/linalg_tutorial.ipynb
diff --git a/docs/source/tutorials/np_linalg_tutorial_port.ipynb b/docs/source/tutorials/np_linalg_tutorial_port.ipynb
diff --git a/docs/source/tutorials/stats_tutorial.ipynb b/docs/source/tutorials/stats_tutorial.ipynb
diff --git a/src/xarray_einstats/__init__.py b/src/xarray_einstats/__init__.py
@@ -19,7 +19,7 @@
     "EinopsAccessor",
 ]
 
-__version__ = "0.6.0.dev0"
+__version__ = "0.6.0"
 
 
 def sort(da, dim, **kwargs):