Pushing the docs to dev/ for branch: main, commit 7aa7485466be233498b50f9f564b8eb9fceb3702

Author: sklearn-ci

dev/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: b8475758ea3b824e55e20cfe74ffc2eb
+config: dac8c3fe1a779cbc4a2e7650e8445792
 tags: 645f666f9bcd5a90fca523b33c5a78b7

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -58,7 +58,18 @@
       },
       "outputs": [],
       "source": [
-        "import polars as pl\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.preprocessing import OneHotEncoder\nfrom sklearn.compose import ColumnTransformer\n\ndf = pl.DataFrame(\n    {\"height\": [120, 140, 150, 110, 100], \"pet\": [\"dog\", \"cat\", \"dog\", \"cat\", \"cat\"]}\n)\npreprocessor = ColumnTransformer(\n    [\n        (\"numerical\", StandardScaler(), [\"height\"]),\n        (\"categorical\", OneHotEncoder(sparse_output=False), [\"pet\"]),\n    ],\n    verbose_feature_names_out=False,\n)\npreprocessor.set_output(transform=\"polars\")\n\ndf_out = preprocessor.fit_transform(df)\nprint(f\"Output type: {type(df_out)}\")"
+        "import polars as pl\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.preprocessing import OneHotEncoder\nfrom sklearn.compose import ColumnTransformer\n\ndf = pl.DataFrame(\n    {\"height\": [120, 140, 150, 110, 100], \"pet\": [\"dog\", \"cat\", \"dog\", \"cat\", \"cat\"]}\n)\npreprocessor = ColumnTransformer(\n    [\n        (\"numerical\", StandardScaler(), [\"height\"]),\n        (\"categorical\", OneHotEncoder(sparse_output=False), [\"pet\"]),\n    ],\n    verbose_feature_names_out=False,\n)\npreprocessor.set_output(transform=\"polars\")\n\ndf_out = preprocessor.fit_transform(df)\ndf_out"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "print(f\"Output type: {type(df_out)}\")"
       ]
     },
     {

dev/_downloads/53490cdb42c3c07ba8cccd1c4ed4dca4/plot_release_highlights_1_4_0.ipynb

@@ -73,6 +73,9 @@
 preprocessor.set_output(transform="polars")
 
 df_out = preprocessor.fit_transform(df)
+df_out
+
+# %%
 print(f"Output type: {type(df_out)}")
 
 # %%