From 84d449dcc049c110357ad5d5059063ae75273f84 Mon Sep 17 00:00:00 2001
From: Inessa Pawson <inessapawson@gmail.com>
Date: Tue, 6 Oct 2026 23:50:26 -0400
Subject: [PATCH] docs: fix rendering issues on package-data.md

---
 tests/package-data.md | 25 +++++++++----------------
 1 file changed, 9 insertions(+), 16 deletions(-)

diff --git a/tests/package-data.md b/tests/package-data.md
index 75b7d3f90..37a4ad3b2 100644
--- a/tests/package-data.md
+++ b/tests/package-data.md
@@ -8,6 +8,7 @@ Here, you will learn about working with data for your scientific Python package.
 * When and why you might need data,
 * Where you can store your package's data,
 * How you can access the data both from within your package and by downloading it as your package is used or as tests are run
+:::
 
 :::{note}
 
@@ -41,7 +42,7 @@ We will show you how to implement both, including data in your package or downlo
 
 * **movingpandas** is a pyOpenSci-accepted package that uses data to support some of its tutorials. [Here is an example of a tutorial that shows how to use MovingPandas to process bird migration data.](https://movingpandas.github.io/movingpandas-website/2-analysis-examples/bird-migration.html)
 
-* [scikit-image](https://github.com/scikit-image/scikit-image/tree/main/skimage/data)
+* [scikit-image](https://github.com/scikit-image/scikit-image/tree/main/src/skimage/data)
 * [scikit-learn:](https://github.com/scikit-learn/scikit-learn/tree/main/sklearn/datasets/data)
 
 ### Data for tests
@@ -125,7 +126,6 @@ The cons include:
 
 You want to avoid adding these files to your version control history (git) and draining the resources of PyPI.
 
-<!-- I'm not sure what the intent of these example packages is - are they examples of packages that do this well? or poorly? -->
 * examples:
   * pyOpenSci:
     * opengenomics: <https://github.com/JonnyTran/OpenOmics/tree/master/tests/data/TCGA_LUAD>
@@ -185,7 +185,6 @@ And also some cons:
 * **[Google Cloud Platform](https://cloud.google.com/storage)** - Cloud Storage with strong AI/ML tool integration
 * **[Linode](https://www.linode.com/products/object-storage/)** - Object Storage with straightforward pricing and developer-friendly tools
 
-<!-- I don't understand how these platforms are different from things like figshare - can we clarify that? and how / why someone would pick these vs figshare / dryad? -->
 ```{admonition} Version control platforms for your data
 :class: tip
 
@@ -193,8 +192,6 @@ Platforms exist that allow you to track changes to datasets in the same way as v
 
 Such tools are essential if your package primarily focuses on providing data access.
 
-<!-- I am not sure how to fix this section as i don't know much about these tools -->
-
 Some tools provide distributed access to larger data.
 
 - **[DataLad](https://www.datalad.org/)** - Distributed data management for scientific datasets
@@ -205,12 +202,6 @@ Some tools provide distributed access to larger data.
 - **[Pachyderm](https://www.pachyderm.com/)** - Data pipeline platform with version control
 ```
 
-<!-- I am not sure how this section relates to data stored in a package. I understand it's important, but does it belong in a page focused on how and where to store data for your Python package? It might be that I just don't understand as written!-->
-
-:::{todo}
-<!-- I am not sure about this statement in terms of what it means and whether we have tools that consider standards or not  we might also want to link to FAIR-->
-:::
-
 ```{admonition} Field specific standards + metadata
 :class: tip
 
@@ -257,7 +248,7 @@ See the [importlib-resources documentation](https://importlib-resources.readthed
 
 * examples:
   * pyOpenSci packages:
-    * crowsetta: <https://github.com/vocalpy/crowsetta/blob/main/src/crowsetta/data/data.py>
+    * crowsetta: <https://github.com/vocalpy/crowsetta/blob/main/src/crowsetta/examples/_examples.py>
   * core scientific Python packages:
     * scikit-learn: <https://github.com/scikit-learn/scikit-learn/blob/f86f41d80bff882689fc16bd7da1fef4a805b464/sklearn/datasets/_base.py#L297>
 
@@ -273,14 +264,16 @@ Pooch features include:
 * **Version management:** Pooch can handle different versions of the same dataset
 
 Here is an example of using Pooch to download and cache a remote data file:
-:::{todo}
-TODO: I copied some code online. THIS NEEDS TO BE TESTED // verified
-:::
+
+```python
+import pandas as pd
+import pooch
+import xarray as xr
 
 # Define your data registry
 data_registry = pooch.create(
     path=pooch.os_cache("my_package"),
-    base_url="https://github.com/my_org/my_data/raw/main/",
+    base_url="https://example.com/my_package/data/",
     registry={
         "sample_data.csv": "sha256:abc123...",  # File hash for verification
         "large_dataset.nc": "sha256:def456...",