refactor(QueryContext): move df methods utils to utils package (#17496)

* chore(common.utils): modified utils from module based to package based

* refactor(common.utils): move QueryCacheManager to ad-hoc module

* refactor(QueryContext): move df method utils to utils module

superset/common/utils/dataframe_utils.py

@@ -0,0 +1,42 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+from __future__ import annotations
+
+from typing import List, TYPE_CHECKING
+
+import numpy as np
+import pandas as pd
+
+if TYPE_CHECKING:
+    from superset.common.query_object import QueryObject
+
+
+def left_join_df(
+    left_df: pd.DataFrame, right_df: pd.DataFrame, join_keys: List[str],
+) -> pd.DataFrame:
+    df = left_df.set_index(join_keys).join(right_df.set_index(join_keys))
+    df.reset_index(inplace=True)
+    return df
+
+
+def df_metrics_to_num(df: pd.DataFrame, query_object: QueryObject) -> None:
+    """Converting metrics to numeric when pandas.read_sql cannot"""
+    for col, dtype in df.dtypes.items():
+        if dtype.type == np.object_ and col in query_object.metric_names:
+            # soft-convert a metric column to numeric
+            # will stay as strings if conversion fails
+            df[col] = df[col].infer_objects()