Modify where the info is stored

Author: charlottecrevier

docs/pystac-into-xarray.md

@@ -1,6 +1,6 @@
 # Additional Libraries
 
-The following examples focus on loading COG data into xarray object backed by Dask for efficient in memory reading and processing. 
+The following examples focus on loading COG data into xarray object backed by Dask for efficient in-memory reading and processing. 
 
 !!! info
     [Xarray] is build on NumPy and Pandas, adding capabilities for labeled and multi-dimensional arrays (e.g., climate data, satellite images). It extends NumPy arrays by attaching metadata (coordinates, labels), making it easier to work with data dimensions like time, latitude, longitude, and other variables.
@@ -16,10 +16,6 @@ The following examples focus on loading COG data into xarray object backed by Da
 
 ## Using Rioxarray
 
-Load a single COG, using the link to the s3 object, into an xarray.
-
-Rioxarray is based on rasterio, and can be used to read data into Xarray object. The developers of the rioxarray library provide additional usage examples, like this [one](https://corteva.github.io/rioxarray/stable/examples/read-locks.html).
-
 ``` sh
 --8<-- "how-to-guides/rioxarray-requirements.txt"
 ```
@@ -31,9 +27,6 @@ Source :  [rioxarray installation]
         members: no
         show_root_toc_entry: false # To remove the name of the file in the TOC
 
-!!! Note 
-    When using `rioxarray.open_rasterio()` set `chunks` to enable lazy loading with Dask. This allows Dask to read data in smaller chunks, improving speed and memory usage through parallel computing. For example, a `chunk` size of 1000 for both x and y means Dask reads 100x100 boxes instead of the entire array, processing multiple chunks simultaneously.
-
 ``` py linenums="1" hl_lines="20-23"
 --8<-- "how-to-guides/rioxarray-example.py:code"
 ```
@@ -57,12 +50,9 @@ See [pystac.Item] or [pystac-client] for more information.
 
 ### Using [stackstac]
 
-This is a third party library based on Xarray, but not listed under the Xarray documentation. 
-
 ``` sh
 --8<-- "how-to-guides/stackstac-requirements.txt"
 ```
-If you have problems with the installation, please refer to [stackstac installation].
 
 <!-- START: Read with stackstac-stac -->
 ::: how-to-guides.stackstac-example
@@ -76,14 +66,12 @@ If you have problems with the installation, please refer to [stackstac installat
 ```
 
 See [working-with-xarray-object] or [community-notebook-complete-examples] section for an example on using Xarray object.
-### Using [odc-stac]
 
-This is a third party library based on Xarray, but not listed under the Xarray documentation. 
+### Using [odc-stac]
 
 ``` sh
 --8<-- "how-to-guides/odc-stac-requirements.txt"
 ```
-If you have problems with the installation, please refer to [odc-stac installation].
 
 <!-- START: Read with odc-stac -->
 ::: how-to-guides.odc-stac-example
@@ -112,8 +100,6 @@ See `Xarray.DataArray` for details on methods : <https://docs.xarray.dev/en/stab
 [Xarray: Parallel Computing with Dask]: https://docs.xarray.dev/en/stable/user-guide/dask.html
 [STAC documentation on proj:transform]:  https://github.com/stac-extensions/projection?tab=readme-ov-file#projtransform
 [Re-order the STAC proj:Transform]: reorder-transform-example.md
-[odc-stac installation]: https://odc-stac.readthedocs.io/en/latest/intro.html#installation
-[stackstac installation]: https://stackstac.readthedocs.io/en/latest/#installation
 [STAC utils]: https://github.com/stac-utils
 [pystac-client]: https://pystac-client.readthedocs.io/en/stable/
 [pystac.Item]: https://pystac.readthedocs.io/en/latest/api/pystac.html#item

how-to-guides/odc-stac-example.py

@@ -1,4 +1,9 @@
 """
+This is a third party library based on Xarray, but not listed under the Xarray documentation. 
+
+If you have problems with the installation, please refer to [odc-stac installation](https://odc-stac.readthedocs.io/en/latest/intro.html#installation).
+
+
 ### Load pystac items into an Xarray
 
 In this code you will : 

how-to-guides/rioxarray-example.py

@@ -1,4 +1,10 @@
 """
+Load a single COG, using the link to the s3 object, into an xarray.
+
+Rioxarray is based on rasterio, and can be used to read data into Xarray object. 
+The developers of the rioxarray library provide additional usage examples, 
+like this [one](https://corteva.github.io/rioxarray/stable/examples/read-locks.html).
+
 ## Read a portion of a remote COG into an xarray
 
 In this code you will : 
@@ -15,6 +21,12 @@
     By default, the bbox used for clipping data inside `rio.clip_bbox()` needs to be in 
     the projected coordinate system.  
     See <https://corteva.github.io/rioxarray/stable/examples/clip_box.html#Clip-using-a-bounding-box>
+
+!!! Note 
+    When using `rioxarray.open_rasterio()` set `chunks` to enable lazy loading with Dask. This allows 
+    Dask to read data in smaller chunks, improving speed and memory usage through parallel computing. 
+    For example, a `chunk` size of 1000 for both x and y means Dask reads 100x100 boxes instead of the 
+    entire array, processing multiple chunks simultaneously.
 """
 # --8<-- [start:code]
 import pystac_client

how-to-guides/stackstac-example.py

@@ -1,4 +1,9 @@
 """
+This is a third party library based on Xarray, but not listed under the Xarray documentation. 
+
+If you have problems with the installation, please refer to [stackstac installation](https://stackstac.readthedocs.io/en/latest/#installation).
+
+
 ### Load pystac items into an Xarray
 
 In this code you will :