docs: add inline example plot to sc.pl.highly_variable_genes (#4032)

Co-authored-by: Phil Schaf <flying-sheep@web.de>

Author: Ekin-Kahraman

.github/workflows/check-pr.yml

@@ -51,7 +51,7 @@ jobs:
     name: Check for release notes
     runs-on: ubuntu-latest
     needs: check-milestone
-    if: github.event.pull_request.user.login != 'pre-commit-ci[bot]' && needs.check-milestone.outputs.no-relnotes-reason == '' && !contains(fromJSON('["style","refactor","test","build","ci"]'), needs.check-milestone.outputs.type)
+    if: github.event.pull_request.user.login != 'pre-commit-ci[bot]' && needs.check-milestone.outputs.no-relnotes-reason == '' && !contains(fromJSON('["style","refactor","test","build","docs","ci"]'), needs.check-milestone.outputs.type)
     steps:
       - uses: actions/checkout@v6
         with: { filter: 'blob:none', fetch-depth: 0 }

src/scanpy/plotting/_preprocessing.py

@@ -41,6 +41,27 @@ def highly_variable_genes(  # noqa: PLR0912
         A string is appended to the default filename.
         Infer the filetype if ending on {{`'.pdf'`, `'.png'`, `'.svg'`}}.
 
+    Examples
+    --------
+    Compute and plot highly variable genes from raw PBMC data.
+
+    .. plot::
+        :context: close-figs
+
+        import scanpy as sc
+        adata = sc.datasets.pbmc3k()
+        sc.pp.normalize_total(adata, target_sum=1e4)
+        sc.pp.log1p(adata)
+        sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5)
+        sc.pl.highly_variable_genes(adata)
+
+    Plot on logarithmic axes.
+
+    .. plot::
+        :context: close-figs
+
+        sc.pl.highly_variable_genes(adata, log=True)
+
     """
     if isinstance(adata_or_result, AnnData):
         result = adata_or_result.var