diff --git a/search.json b/search.json
index 1722e87..008076d 100644
--- a/search.json
+++ b/search.json
@@ -292,7 +292,7 @@
"href": "reference/steps-encoding.html#examples",
"title": "Encoding",
"section": "Examples",
- "text": "Examples\n>>> import ibisml as ml\nOne-hot encode all string columns\n>>> step = ml.OneHotEncode(ml.string())\nOne-hot encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.OneHotEncode(\"x\", min_frequency=20)\nOne-hot encode a specific column, including at most 10 categories.\n>>> step = ml.OneHotEncode(\"x\", max_categories=10)",
+ "text": "Examples\n>>> import ibisml as ml\nOne-hot encode all string columns.\n>>> step = ml.OneHotEncode(ml.string())\nOne-hot encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.OneHotEncode(\"x\", min_frequency=20)\nOne-hot encode a specific column, including at most 10 categories.\n>>> step = ml.OneHotEncode(\"x\", max_categories=10)",
"crumbs": [
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@@ -314,7 +314,7 @@
"href": "reference/steps-encoding.html#examples-1",
"title": "Encoding",
"section": "Examples",
- "text": "Examples\n>>> import ibisml as ml\nCategorical encode all string columns\n>>> step = ml.CategoricalEncode(ml.string())\nCategorical encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.CategoricalEncode(\"x\", min_frequency=20)\nCategorical encode a specific column, including at most 10 categories.\n>>> step = ml.CategoricalEncode(\"x\", max_categories=10)",
+ "text": "Examples\n>>> import ibisml as ml\nCategorical encode all string columns.\n>>> step = ml.CategoricalEncode(ml.string())\nCategorical encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.CategoricalEncode(\"x\", min_frequency=20)\nCategorical encode a specific column, including at most 10 categories.\n>>> step = ml.CategoricalEncode(\"x\", max_categories=10)",
"crumbs": [
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