From 86dc6abf1b58ba8119f40313a2768054bbb4a369 Mon Sep 17 00:00:00 2001
From: Sanjay Kumar Sakamuri Kamalakar <sksanjaykumar010307@gmail.com>
Date: Wed, 13 Aug 2025 19:38:01 +0530
Subject: [PATCH 1/2] Update about_map_batch.mdx

---
 docs/source/about_map_batch.mdx | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

diff --git a/docs/source/about_map_batch.mdx b/docs/source/about_map_batch.mdx
index 4ebbdf9acaf..d92999bbd07 100644
--- a/docs/source/about_map_batch.mdx
+++ b/docs/source/about_map_batch.mdx
@@ -38,3 +38,22 @@ To make it valid, you have to drop one of the columns:
 >>> len(dataset_with_duplicates)
 6
 ```
+Alternatively, you can overwrite the existing column to achieve the same result.
+For example, here’s how to duplicate every row in the dataset by overwriting column `"a"`:
+
+```py
+>>> from datasets import Dataset
+>>> dataset = Dataset.from_dict({"a": [0, 1, 2]})
+# Overwrites the existing "a" column with duplicated values
+>>> duplicated_dataset = dataset.map(
+...     lambda batch: {"a": [x for x in batch["a"] for _ in range(2)]},
+...     batched=True
+... )
+>>> duplicated_dataset
+Dataset({
+    features: ['a'],
+    num_rows: 6
+})
+>>> duplicated_dataset["a"]
+[0, 0, 1, 1, 2, 2]
+```

From 7018bf9a00146542f0921ea92221f37c2c0aaccd Mon Sep 17 00:00:00 2001
From: Sanjay Kumar Sakamuri Kamalakar <sksanjaykumar010307@gmail.com>
Date: Wed, 13 Aug 2025 19:46:26 +0530
Subject: [PATCH 2/2] Update about_map_batch.mdx

---
 docs/source/about_map_batch.mdx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/about_map_batch.mdx b/docs/source/about_map_batch.mdx
index d92999bbd07..6c33fed593f 100644
--- a/docs/source/about_map_batch.mdx
+++ b/docs/source/about_map_batch.mdx
@@ -44,7 +44,7 @@ For example, here’s how to duplicate every row in the dataset by overwriting c
 ```py
 >>> from datasets import Dataset
 >>> dataset = Dataset.from_dict({"a": [0, 1, 2]})
-# Overwrites the existing "a" column with duplicated values
+# overwrites the existing "a" column with duplicated values
 >>> duplicated_dataset = dataset.map(
 ...     lambda batch: {"a": [x for x in batch["a"] for _ in range(2)]},
 ...     batched=True