Pushing the docs to dev/ for branch: main, commit 7fb61586b704cc4a3169288fe5379017cdfa08a0

Author: dirty-cat-ci

dev/_downloads/0489157882e9236e99043be54168dbb0/00_getting_started.ipynb

@@ -29,7 +29,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "Explore all the available datasets in `downloading_a_dataset_ref`.\n\n"
+        "Explore all the available datasets in `datasets_ref`.\n\n"
       ]
     },
     {
@@ -165,7 +165,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "For joining multiple auxiliary tables on a main table at once, use the\n:class:`~skrub.MultiAggJoiner`.\n\nSee other ways to join multiple tables in `assembling`.\n\n"
+        "For joining multiple auxiliary tables on a main table at once, use the\n:class:`~skrub.MultiAggJoiner`.\n\nSee other ways to join multiple tables in `userguide_joining_tables`.\n\n"
       ]
     },
     {

dev/_downloads/12158facaf8145cc3aa64549614a9b65/10_apply_on_cols.zip

@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n.. currentmodule:: skrub\n\nSubsampling for faster development\n==================================\n\nHere we show how to use :meth:`.skb.subsample() <DataOp.skb.subsample>` to speed-up\ninteractive construction of a skrub DataOps plan by computing previews on a subsampled\nversion of the original data.\n"
+        "\n\n# Subsampling for faster development\n\nHere we show how to use :meth:`.skb.subsample() <DataOp.skb.subsample>` to speed-up\ninteractive construction of a skrub DataOps plan by computing previews on a subsampled\nversion of the original data.\n\n.. currentmodule:: skrub\n"
       ]
     },
     {
@@ -22,7 +22,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "We are working with a dataset of over 9K rows. As we build up our plan,\nwe see previews of the intermediate results so we can check that it behaves\nas we expect. However, if some estimators are slow, fitting them and\ncomputing results on the whole data can slow us down.\n\n# Lightweight construction of the DataOps plan on a subsample\n\nWe can tell skrub to subsample the data when computing the previews, with\n:meth:`.skb.subsample() <DataOp.skb.subsample>`.\n\n"
+        "We are working with a dataset of over 9K rows. As we build up our plan,\nwe see previews of the intermediate results so we can check that it behaves\nas we expect. However, if some estimators are slow, fitting them and\ncomputing results on the whole data can slow us down.\n\n## Lightweight construction of the DataOps plan on a subsample\n\nWe can tell skrub to subsample the data when computing the previews, with\n:meth:`.skb.subsample() <DataOp.skb.subsample>`.\n\n"
       ]
     },
     {
@@ -112,7 +112,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "# Evaluating the DataOps plan on the full data\nBy default, when we do not explicitly ask for ``keep_subsampling=True``, no\nsubsampling takes place.\n\nHere we run the cross-validation **on the full data**.\nNote the longer ``fit_time`` and much better ``test_score``.\n\n"
+        "## Evaluating the DataOps plan on the full data\nBy default, when we do not explicitly ask for ``keep_subsampling=True``, no\nsubsampling takes place.\n\nHere we run the cross-validation **on the full data**.\nNote the longer ``fit_time`` and much better ``test_score``.\n\n"
       ]
     },
     {

…2f709cde35447cd437f/12_subsampling.ipynb …28918e38859c57a8705/13_subsampling.ipynbdev/_downloads/1754d86486db52f709cde35447cd437f/12_subsampling.ipynb renamed to dev/_downloads/161af8bbdec6e28918e38859c57a8705/13_subsampling.ipynb dev/_downloads/1754d86486db52f709cde35447cd437f/12_subsampling.ipynb renamed to dev/_downloads/161af8bbdec6e28918e38859c57a8705/13_subsampling.ipynb

@@ -50,8 +50,8 @@
 # number of components.
 #
 # To select columns without hardcoding their names, we introduce
-# :ref:`selectors<selectors>`, which allow for flexible matching pattern and composable
-# logic.
+# :ref:`selectors<userguide_selectors>`, which allow for flexible matching pattern
+# and composable logic.
 #
 # The regex selector below will match all columns prefixed with ``"lsa"``, and pass them
 # to :class:`~skrub.ApplyToFrame` which will assemble these columns into a dataframe and

dev/_downloads/16cb73c3c94fb6b276f4d4577a4043b5/10_apply_on_cols.py

@@ -37,8 +37,7 @@
 employees_df, salaries = dataset.X, dataset.y
 
 # %%
-# Explore all the available datasets in :ref:`downloading_a_dataset_ref`.
-
+# Explore all the available datasets in :ref:`datasets_ref`.
 
 # %%
 # Generating an interactive report for a dataframe
@@ -187,7 +186,7 @@
 # For joining multiple auxiliary tables on a main table at once, use the
 # :class:`~skrub.MultiAggJoiner`.
 #
-# See other ways to join multiple tables in :ref:`assembling`.
+# See other ways to join multiple tables in :ref:`userguide_joining_tables`.
 
 
 # %%