diff --git a/tpch/notebooks/gpu/execute.ipynb b/tpch/notebooks/gpu/execute.ipynb
index f11580ae1..87ba3ae7c 100755
--- a/tpch/notebooks/gpu/execute.ipynb
+++ b/tpch/notebooks/gpu/execute.ipynb
@@ -22,7 +22,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install -U narwhals>=0.7.1"
+    "!pip install -U narwhals>=0.7.2"
    ]
   },
   {
diff --git a/tpch/notebooks/q1/execute.ipynb b/tpch/notebooks/q1/execute.ipynb
index 90bac970b..50d0c073f 100755
--- a/tpch/notebooks/q1/execute.ipynb
+++ b/tpch/notebooks/q1/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
diff --git a/tpch/notebooks/q2/execute.ipynb b/tpch/notebooks/q2/execute.ipynb
index b178d2718..4ad33bd93 100755
--- a/tpch/notebooks/q2/execute.ipynb
+++ b/tpch/notebooks/q2/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
@@ -126,9 +126,11 @@
     "        .join(supplier_ds, left_on=\"ps_suppkey\", right_on=\"s_suppkey\")\n",
     "        .join(nation_ds, left_on=\"s_nationkey\", right_on=\"n_nationkey\")\n",
     "        .join(region_ds, left_on=\"n_regionkey\", right_on=\"r_regionkey\")\n",
-    "        .filter(nw.col(\"p_size\") == var_1)\n",
-    "        .filter(nw.col(\"p_type\").str.ends_with(var_2))\n",
-    "        .filter(nw.col(\"r_name\") == var_3)\n",
+    "        .filter(\n",
+    "            nw.col(\"p_size\") == var_1,\n",
+    "            nw.col(\"p_type\").str.ends_with(var_2),\n",
+    "            nw.col(\"r_name\") == var_3,\n",
+    "        )\n",
     "    )\n",
     "\n",
     "    final_cols = [\n",
diff --git a/tpch/notebooks/q3/execute.ipynb b/tpch/notebooks/q3/execute.ipynb
index 856315a10..51823c7c5 100755
--- a/tpch/notebooks/q3/execute.ipynb
+++ b/tpch/notebooks/q3/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
@@ -120,9 +120,10 @@
     "        customer_ds.filter(nw.col(\"c_mktsegment\") == var_3)\n",
     "        .join(orders_ds, left_on=\"c_custkey\", right_on=\"o_custkey\")\n",
     "        .join(line_item_ds, left_on=\"o_orderkey\", right_on=\"l_orderkey\")\n",
-    "        .filter(nw.col(\"o_orderdate\") < var_2)\n",
-    "        .filter(nw.col(\"l_shipdate\") > var_1)\n",
-    "        .with_columns(\n",
+    "        .filter(\n",
+    "            nw.col(\"o_orderdate\") < var_2,\n",
+    "            nw.col(\"l_shipdate\") > var_1,\n",
+    "        ).with_columns(\n",
     "            (nw.col(\"l_extendedprice\") * (1 - nw.col(\"l_discount\"))).alias(\"revenue\")\n",
     "        )\n",
     "        .group_by([\"o_orderkey\", \"o_orderdate\", \"o_shippriority\"])\n",
diff --git a/tpch/notebooks/q4/execute.ipynb b/tpch/notebooks/q4/execute.ipynb
index 6b3d29e73..44881bfef 100755
--- a/tpch/notebooks/q4/execute.ipynb
+++ b/tpch/notebooks/q4/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
@@ -116,9 +116,10 @@
     "\n",
     "    result = (\n",
     "        line_item_ds.join(orders_ds, left_on=\"l_orderkey\", right_on=\"o_orderkey\")\n",
-    "        .filter(nw.col(\"o_orderdate\").is_between(var_1, var_2, closed=\"left\"))\n",
-    "        .filter(nw.col(\"l_commitdate\") < nw.col(\"l_receiptdate\"))\n",
-    "        .unique(subset=[\"o_orderpriority\", \"l_orderkey\"])\n",
+    "        .filter(\n",
+    "            nw.col(\"o_orderdate\").is_between(var_1, var_2, closed=\"left\"),\n",
+    "            nw.col(\"l_commitdate\") < nw.col(\"l_receiptdate\"),\n",
+    "        ).unique(subset=[\"o_orderpriority\", \"l_orderkey\"])\n",
     "        .group_by(\"o_orderpriority\")\n",
     "        .agg(nw.len().alias(\"order_count\"))\n",
     "        .sort(by=\"o_orderpriority\")\n",
diff --git a/tpch/notebooks/q5/execute.ipynb b/tpch/notebooks/q5/execute.ipynb
index ac5f40428..57f065725 100755
--- a/tpch/notebooks/q5/execute.ipynb
+++ b/tpch/notebooks/q5/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
diff --git a/tpch/notebooks/q6/execute.ipynb b/tpch/notebooks/q6/execute.ipynb
index 95323f67b..5cb9e5d65 100755
--- a/tpch/notebooks/q6/execute.ipynb
+++ b/tpch/notebooks/q6/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
@@ -113,11 +113,10 @@
     "\n",
     "    result = (\n",
     "        line_item_ds.filter(\n",
-    "            nw.col(\"l_shipdate\").is_between(var_1, var_2, closed=\"left\")\n",
-    "        )\n",
-    "        .filter(nw.col(\"l_discount\").is_between(0.05, 0.07))\n",
-    "        .filter(nw.col(\"l_quantity\") < var_3)\n",
-    "        .with_columns(\n",
+    "            nw.col(\"l_shipdate\").is_between(var_1, var_2, closed=\"left\"),\n",
+    "            nw.col(\"l_discount\").is_between(0.05, 0.07),\n",
+    "            nw.col(\"l_quantity\") < var_3,\n",
+    "        ).with_columns(\n",
     "            (nw.col(\"l_extendedprice\") * nw.col(\"l_discount\")).alias(\"revenue\")\n",
     "        )\n",
     "        .select(nw.sum(\"revenue\"))\n",
@@ -446,7 +445,7 @@
    "source": [
     "tool = 'polars[lazy]'\n",
     "fn = IO_FUNCS[tool]\n",
-    "timings = %timeit -o q6(fn(lineitem))\n",
+    "timings = %timeit -o q6(fn(lineitem)).collect()\n",
     "results[tool] = timings.best"
    ]
   },
diff --git a/tpch/notebooks/q7/execute.ipynb b/tpch/notebooks/q7/execute.ipynb
index bcae5a969..5ce34e8b5 100755
--- a/tpch/notebooks/q7/execute.ipynb
+++ b/tpch/notebooks/q7/execute.ipynb
@@ -47,7 +47,7 @@
     }
    ],
    "source": [
-    "!pip install -U pandas polars pyarrow narwhals>=0.7.1"
+    "!pip install -U polars pyarrow narwhals>=0.7.2 && pip uninstall pandas -y && pip install --pre --extra-index https://pypi.anaconda.org/scientific-python-nightly-wheels/simple pandas"
    ]
   },
   {
@@ -120,8 +120,8 @@
     "    n1 = nation_ds.filter(nw.col(\"n_name\") == \"FRANCE\")\n",
     "    n2 = nation_ds.filter(nw.col(\"n_name\") == \"GERMANY\")\n",
     "\n",
-    "    var_1 = date(1995, 1, 1)\n",
-    "    var_2 = date(1996, 12, 31)\n",
+    "    var_1 = datetime(1995, 1, 1)\n",
+    "    var_2 = datetime(1996, 12, 31)\n",
     "\n",
     "    df1 = (\n",
     "        customer_ds.join(n1, left_on=\"c_nationkey\", right_on=\"n_nationkey\")\n",
@@ -476,7 +476,7 @@
    "source": [
     "tool = 'polars[lazy]'\n",
     "fn = IO_FUNCS[tool]\n",
-    "timings = %timeit -o q7(fn(nation), fn(customer), fn(lineitem), fn(orders), fn(supplier))\n",
+    "timings = %timeit -o q7(fn(nation), fn(customer), fn(lineitem), fn(orders), fn(supplier)).collect()\n",
     "results[tool] = timings.best"
    ]
   },