diff --git a/docs/examples/getting-started/quickstart.py b/docs/examples/getting-started/quickstart.py
index 2e5530781..89dc198d5 100644
--- a/docs/examples/getting-started/quickstart.py
+++ b/docs/examples/getting-started/quickstart.py
@@ -31,11 +31,7 @@
 
 # docsnip datasets
 @dataset
-@source(
-    postgres.table("product_info", cursor="last_modified"),
-    every="1m",
-    tier="prod",
-)
+@source(postgres.table("product", cursor="updated"), every="1m", tier="prod")
 @source(webhook.endpoint("Product"), tier="dev")
 @meta(owner="chris@fennel.ai", tags=["PII"])
 class Product:
@@ -83,20 +79,12 @@ class UserSellerOrders:
     @inputs(Order, Product)
     def my_pipeline(cls, orders: Dataset, products: Dataset):
         orders = orders.join(products, how="left", on=["product_id"])
-        orders = orders.transform(
-            lambda df: df[["uid", "seller_id", "timestamp"]].fillna(0),
-            schema={
-                "uid": int,
-                "seller_id": int,
-                "timestamp": datetime,
-            },
-        )
-
+        orders = orders.transform(lambda df: df.fillna(0))
+        orders = orders.drop("product_id", "desc", "price")
+        orders = orders.dropnull()
         return orders.groupby("uid", "seller_id").aggregate(
-            [
-                Count(window=Window("1d"), into_field="num_orders_1d"),
-                Count(window=Window("1w"), into_field="num_orders_1w"),
-            ]
+            Count(window=Window("1d"), into_field="num_orders_1d"),
+            Count(window=Window("1w"), into_field="num_orders_1w"),
         )
 
 
diff --git a/fennel/client_tests/test_dataset.py b/fennel/client_tests/test_dataset.py
index 2a8c87206..35516a51f 100644
--- a/fennel/client_tests/test_dataset.py
+++ b/fennel/client_tests/test_dataset.py
@@ -1111,43 +1111,39 @@ class MovieRatingWindowed:
     @inputs(RatingActivity)
     def pipeline_aggregate(cls, activity: Dataset):
         return activity.groupby("movie").aggregate(
-            [
-                Count(window=Window("3d"), into_field=str(cls.num_ratings_3d)),
-                Sum(
-                    window=Window("7d"),
-                    of="rating",
-                    into_field=str(cls.sum_ratings_7d),
-                ),
-                Average(
-                    window=Window("6h"),
-                    of="rating",
-                    into_field=str(cls.avg_rating_6h),
-                ),
-                Count(
-                    window=Window("forever"), into_field=str(cls.total_ratings)
-                ),
-                Stddev(
-                    window=Window("3d"),
-                    of="rating",
-                    into_field=str(cls.std_rating_3d),
-                ),
-                Stddev(
-                    window=Window("7d"),
-                    of="rating",
-                    into_field=str(cls.std_rating_7d),
-                ),
-                Stddev(
-                    window=Window("10m"),
-                    of="rating",
-                    into_field=str(cls.std_rating_10m),
-                ),
-                Stddev(
-                    window=Window("10m"),
-                    of="rating",
-                    default=-3.14159,
-                    into_field=str(cls.std_rating_10m_other_default),
-                ),
-            ]
+            Count(window=Window("3d"), into_field=str(cls.num_ratings_3d)),
+            Sum(
+                window=Window("7d"),
+                of="rating",
+                into_field=str(cls.sum_ratings_7d),
+            ),
+            Average(
+                window=Window("6h"),
+                of="rating",
+                into_field=str(cls.avg_rating_6h),
+            ),
+            Count(window=Window("forever"), into_field=str(cls.total_ratings)),
+            Stddev(
+                window=Window("3d"),
+                of="rating",
+                into_field=str(cls.std_rating_3d),
+            ),
+            Stddev(
+                window=Window("7d"),
+                of="rating",
+                into_field=str(cls.std_rating_7d),
+            ),
+            Stddev(
+                window=Window("10m"),
+                of="rating",
+                into_field=str(cls.std_rating_10m),
+            ),
+            Stddev(
+                window=Window("10m"),
+                of="rating",
+                default=-3.14159,
+                into_field=str(cls.std_rating_10m_other_default),
+            ),
         )
 
 
diff --git a/fennel/client_tests/test_fraud_detection.py b/fennel/client_tests/test_fraud_detection.py
index b8ddaba94..831e5201a 100644
--- a/fennel/client_tests/test_fraud_detection.py
+++ b/fennel/client_tests/test_fraud_detection.py
@@ -65,10 +65,8 @@ class UserTransactionSums:
     @inputs(CreditCardTransactions)
     def first_pipeline(cls, transactions: Dataset):
         return transactions.groupby("cc_num").aggregate(
-            [
-                Sum(of="amt", window=Window("1d"), into_field="sum_amt_1d"),
-                Sum(of="amt", window=Window("7d"), into_field="sum_amt_7d"),
-            ]
+            Sum(of="amt", window=Window("1d"), into_field="sum_amt_1d"),
+            Sum(of="amt", window=Window("7d"), into_field="sum_amt_7d"),
         )
 
 
diff --git a/fennel/datasets/datasets.py b/fennel/datasets/datasets.py
index e7412be3e..37d355182 100644
--- a/fennel/datasets/datasets.py
+++ b/fennel/datasets/datasets.py
@@ -443,12 +443,15 @@ def __init__(self, node: _Node, *args):
         self.node = node
         self.node.out_edges.append(self)
 
-    def aggregate(self, aggregates: List[AggregateType], *args) -> _Node:
-        if len(args) > 0 or not isinstance(aggregates, list):
+    def aggregate(self, *args) -> _Node:
+        if len(args) == 0:
             raise TypeError(
-                "aggregate operator, takes a list of aggregates "
-                "found: {}".format(type(aggregates))
+                "aggregate operator expects atleast one aggregation operation"
             )
+        if len(args) == 1 and isinstance(args[0], list):
+            aggregates = args[0]
+        else:
+            aggregates = list(args)
         if len(self.keys) == 1 and isinstance(self.keys[0], list):
             self.keys = self.keys[0]  # type: ignore
         return Aggregate(self.node, list(self.keys), aggregates)