diff --git a/docs/source/src/python/user-guide/io/cloud-storage.py b/docs/source/src/python/user-guide/io/cloud-storage.py
index 12b02df28e61..f0cbe67a9a0c 100644
--- a/docs/source/src/python/user-guide/io/cloud-storage.py
+++ b/docs/source/src/python/user-guide/io/cloud-storage.py
@@ -77,20 +77,39 @@ def get_credentials() -> pl.CredentialProviderFunctionReturn:
 # --8<-- [end:scan_pyarrow_dataset]
 
 # --8<-- [start:write_parquet]
+import polars as pl
+
+df = pl.DataFrame(
+    {
+        "foo": ["a", "b", "c", "d", "d"],
+        "bar": [1, 2, 3, 4, 5],
+    }
+)
+
+destination = "s3://bucket/my_file.parquet"
+
+df.write_parquet(destination)
 
+# --8<-- [end:write_parquet]
+
+# --8<-- [start:write_file_object]
 import polars as pl
 import s3fs
+import gzip
+
+df = pl.DataFrame(
+    {
+        "foo": ["a", "b", "c", "d", "d"],
+        "bar": [1, 2, 3, 4, 5],
+    }
+)
 
-df = pl.DataFrame({
-    "foo": ["a", "b", "c", "d", "d"],
-    "bar": [1, 2, 3, 4, 5],
-})
+destination = "s3://bucket/my_file.csv.gz"
 
 fs = s3fs.S3FileSystem()
-destination = "s3://bucket/my_file.parquet"
 
-# write parquet
-with fs.open(destination, mode='wb') as f:
-    df.write_parquet(f)
-# --8<-- [end:write_parquet]
+with fs.open(destination, "wb") as cloud_f:
+    with gzip.open(cloud_f, "w") as f:
+        df.write_csv(f)
+# --8<-- [end:write_file_object]
 """
diff --git a/docs/source/src/rust/user-guide/io/cloud-storage.rs b/docs/source/src/rust/user-guide/io/cloud-storage.rs
index 2df882a39c00..19fe4e66b815 100644
--- a/docs/source/src/rust/user-guide/io/cloud-storage.rs
+++ b/docs/source/src/rust/user-guide/io/cloud-storage.rs
@@ -44,3 +44,6 @@ async fn main() {
 
 // --8<-- [start:write_parquet]
 // --8<-- [end:write_parquet]
+
+// --8<-- [start:write_file_object]
+// --8<-- [end:write_file_object]
diff --git a/docs/source/user-guide/io/cloud-storage.md b/docs/source/user-guide/io/cloud-storage.md
index f12ad4576ebd..5d1449c02c19 100644
--- a/docs/source/user-guide/io/cloud-storage.md
+++ b/docs/source/user-guide/io/cloud-storage.md
@@ -71,7 +71,12 @@ We first create a PyArrow dataset and then create a `LazyFrame` from the dataset
 
 ## Writing to cloud storage
 
-We can write a `DataFrame` to cloud storage in Python using s3fs for S3, adlfs for Azure Blob
-Storage and gcsfs for Google Cloud Storage. In this example, we write a Parquet file to S3.
+`DataFrame`s can also be written to cloud storage by passing a cloud URL:
 
 {{code_block('user-guide/io/cloud-storage','write_parquet',['write_parquet'])}}
+
+Note that `DataFrame`s can also be written to any Python file object that supports writes. This can
+be helpful for performing operations that are not yet natively supported, e.g. writing a compressed
+CSV directly to cloud:
+
+{{code_block('user-guide/io/cloud-storage','write_file_object',['write_csv'])}}