add to_timedelta

Author: chelsea-lin

tests/unit/core/compile/sqlglot/aggregations/test_unary_compiler.py

@@ -57,16 +57,17 @@ def test_max(scalar_types_df: bpd.DataFrame, snapshot):
 
 
 def test_mean(scalar_types_df: bpd.DataFrame, snapshot):
-    bf_df = scalar_types_df[["int64_col", "bool_col", "duration_col"]]
-    # bf_df["duration_col"] = bpd.to_timedelta(bf_df["duration_col"], unit="us")
+    # bf_df = scalar_types_df[["int64_col", "bool_col", "duration_col"]]
+    bf_df = scalar_types_df[["duration_col"]]
+    bf_df["duration_col"] = bpd.to_timedelta(bf_df["duration_col"], unit="us")
 
     agg_ops_map = {
-        "int64_col": agg_ops.MeanOp().as_expr("int64_col"),
-        "bool_col": agg_ops.MeanOp().as_expr("bool_col"),
+        # "int64_col": agg_ops.MeanOp().as_expr("int64_col"),
+        # "bool_col": agg_ops.MeanOp().as_expr("bool_col"),
         "duration_col": agg_ops.MeanOp().as_expr("duration_col"),
-        "int64_col_w_floor": agg_ops.MeanOp(should_floor_result=True).as_expr(
-            "int64_col"
-        ),
+        # "int64_col_w_floor": agg_ops.MeanOp(should_floor_result=True).as_expr(
+        #     "int64_col"
+        # ),
     }
     sql = _apply_unary_agg_ops(
         bf_df, list(agg_ops_map.values()), list(agg_ops_map.keys())