diff --git a/datasets/flwr_datasets/utils.py b/datasets/flwr_datasets/utils.py
index b591d4d3e2ff..388865a26cf6 100644
--- a/datasets/flwr_datasets/utils.py
+++ b/datasets/flwr_datasets/utils.py
@@ -146,7 +146,8 @@ def divide_dataset(
     >>> division = [0.8, 0.2]
     >>> train, test = divide_dataset(dataset=partition, division=division)
 
-    Use `divide_dataset` with division specified as a dict.
+    Use `divide_dataset` with division specified as a dict
+    (this accomplishes the same goal as the example with a list above).
 
     >>> from flwr_datasets import FederatedDataset
     >>> from flwr_datasets.utils import divide_dataset
@@ -273,11 +274,11 @@ def concatenate_divisions(
     partition_division: Union[List[float], Tuple[float, ...], Dict[str, float]],
     division_id: Union[int, str],
 ) -> Dataset:
-    """Create a dataset by concatenation of all partitions in the same division.
+    """Create a dataset by concatenation of divisions from all partitions.
 
     The divisions are created based on the `partition_division` and accessed based
-    on the `division_id`. It can be used to create e.g. centralized dataset from
-    federated on-edge test sets.
+    on the `division_id`. This fuction can be used to create e.g. centralized dataset
+    from federated on-edge test sets.
 
     Parameters
     ----------
@@ -298,6 +299,35 @@ def concatenate_divisions(
     -------
     concatenated_divisions : Dataset
         A dataset created as concatenation of the divisions from all partitions.
+
+    Examples
+    --------
+    Use `concatenate_divisions` with division specified as a list.
+
+    >>> from flwr_datasets import FederatedDataset
+    >>> from flwr_datasets.utils import concatenate_divisions
+    >>>
+    >>> fds = FederatedDataset(dataset="mnist", partitioners={"train": 100})
+    >>> concatenated_divisions = concatenate_divisions(
+    ...     partitioner=fds.partitioners["train"],
+    ...     partition_division=[0.8, 0.2],
+    ...     division_id=1
+    ... )
+    >>> print(concatenated_divisions)
+
+    Use `concatenate_divisions` with division specified as a dict.
+    This accomplishes the same goal as the example with a list above.
+
+    >>> from flwr_datasets import FederatedDataset
+    >>> from flwr_datasets.utils import concatenate_divisions
+    >>>
+    >>> fds = FederatedDataset(dataset="mnist", partitioners={"train": 100})
+    >>> concatenated_divisions = concatenate_divisions(
+    ...     partitioner=fds["train"],
+    ...     partition_division={"train": 0.8, "test": 0.2},
+    ...     division_id="test"
+    ... )
+    >>> print(concatenated_divisions)
     """
     _check_division_config_correctness(partition_division)
     divisions = []