Update the documentation

.github/workflows/publish-book.yml

@@ -30,6 +30,7 @@ jobs:
         pip install jupyter-book
         pip install matplotlib  # Pandas style
         pip install .[polars]
+        pip install .[widget]
 
     - name: Create a kernel
       run: |

docs/_toc.yml

@@ -4,23 +4,24 @@ parts:
   - caption: ITables in Notebooks
     chapters:
     - file: advanced_parameters
+    - file: select
+    - file: extensions
+    - file: custom_extensions
     - file: custom_css
     - file: formatting
     - file: pandas_style
-    - file: extensions
-    - file: custom_extensions
     - file: dark_mode
     - file: quarto
     - file: downsampling
     - file: references
     - file: supported_editors
   - caption: ITables in Applications
     chapters:
-      - file: html_export
-      - file: dash
-      - file: shiny
-      - file: streamlit
       - file: ipywidgets
+      - file: streamlit
+      - file: shiny
+      - file: dash
+      - file: html_export
   - caption: Contributing to ITables
     chapters:
       - file: contributing

docs/extensions.md

@@ -105,7 +105,7 @@ show(
 ```{tip}
 Only the filtered or selected rows are exported to CSV/Excel. To filter the rows you
 can use the simple search box, the [SearchPanes](#searchpanes) and [SearchBuilder](#searchbuilder)
-options, or the [select](#row-selection) extension.
+options, or the [select](select.md) extension.
 ```
 
 ```{warning}
@@ -261,40 +261,6 @@ opt.keys = True
 The KeyTable extension works in Jupyter Book (try it here in the documentation) but not in JupyterLab.
 ```
 
-## Row selection
-
-The [select](https://datatables.net/extensions/select) extension let you select rows (or cells). When you do so,
-only the selected rows are exported
-
-```{code-cell}
-:tags: [full-width]
-
-show(
-    df,
-    select=True,
-    selected_rows=[2, 4, 5],
-    buttons=["copyHtml5", "csvHtml5", "excelHtml5"],
-)
-```
-
-```{tip}
-The `select` option accept multiple values, as documented [here](https://datatables.net/extensions/select):
-- `select=True` or `select="os"` let you select using single click, shift-click and ctrl-click
-- `select="single"` let you select a single row
-- `select="multi"` for single click selection of multiple rows, `select="multi+shift"`, ...
-
-With `select={"style": "os", "items": "cell"}` you can let the user select specific cells,
-however cell selection is not taken into account when exporting the data.
-```
-
-```{tip}
-It is possible to get the updated `selected_rows` back in Python but for this you will have to use,
-instead of `show`, either
-- the `ITable` [Jupyter Widget](ipywidgets.md)
-- the `interactive_table` [Streamlit component](streamlit.md)
-- or `DT` in a [Shiny app](shiny.md).
-```
-
 ## RowGroup
 
 Use the [RowGroup](https://datatables.net/extensions/rowgroup/) extension to group

docs/ipywidgets.md

@@ -40,7 +40,7 @@ table
 ## The `selected_rows` traits
 
 The `selected_rows` attribute of the `ITable` object provides a view on the
-rows that have been selected in the table (remember to pass `select=True`
+rows that have been selected in the table (remember to pass [`select=True`](select.md)
 to activate the row selection). You can use it to either retrieve
 or change the current row selection:
 

docs/select.md

@@ -0,0 +1,84 @@
+---
+jupytext:
+  formats: md:myst
+  notebook_metadata_filter: -jupytext.text_representation.jupytext_version
+  text_representation:
+    extension: .md
+    format_name: myst
+    format_version: 0.13
+kernelspec:
+  display_name: itables
+  language: python
+  name: itables
+---
+
+## Row selection
+
+The [select](https://datatables.net/extensions/select) extension let you select rows (or cells). When you do so,
+only the selected rows are exported
+
+```{code-cell}
+from itables import init_notebook_mode, show
+
+init_notebook_mode()
+```
+
+```{code-cell}
+:tags: [hide-input]
+
+import string
+
+import numpy as np
+import pandas as pd
+
+from itables.sample_dfs import get_countries
+
+df = get_countries(html=False)
+# Add columns for the searchPanes demo
+df["climate_zone"] = np.where(
+    df["latitude"].abs() < 23.43615,
+    "Tropical",
+    np.where(
+        df["latitude"].abs() < 35,
+        "Sub-tropical",
+        # Artic circle is 66.563861 but there is no capital there => using 64
+        np.where(df["latitude"].abs() < 64, "Temperate", "Frigid"),
+    ),
+)
+df["hemisphere"] = np.where(df["latitude"] > 0, "North", "South")
+wide_df = pd.DataFrame(
+    {
+        letter: np.random.normal(size=100)
+        for letter in string.ascii_lowercase + string.ascii_uppercase
+    }
+)
+```
+
+```{code-cell}
+:tags: [full-width]
+
+show(
+    df,
+    select=True,
+    selected_rows=[2, 4, 5],
+    buttons=["copyHtml5", "csvHtml5", "excelHtml5"],
+)
+```
+
+```{tip}
+It is possible to get the updated `selected_rows` back in Python but for this you will have to use,
+instead of `show`, either
+- the `ITable` [Jupyter Widget](ipywidgets.md)
+- the `interactive_table` [Streamlit component](streamlit.md)
+- or `DT` in a [Shiny app](shiny.md).
+```
+
+```{tip}
+The `select` option accept multiple values, as documented [here](https://datatables.net/extensions/select):
+- `select=True` or `select="os"` let you select using single click, shift-click and ctrl-click
+- `select="single"` let you select a single row
+- `select="multi"` for single click selection of multiple rows, `select="multi+shift"`, ...
+
+With `select={"style": "os", "items": "cell"}` you can let the user select specific cells,
+however cell selection is not taken into account when exporting the data.
+```