superset dataframe_utils 源码
superset dataframe_utils 代码
文件路径：/superset/common/utils/dataframe_utils.py
# 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
import datetime
from typing import Any, 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()
def is_datetime_series(series: Any) -> bool:
if series is None or not isinstance(series, pd.Series):
return False
if series.isnull().all():
return False
return pd.api.types.is_datetime64_any_dtype(series) or (
series.apply(lambda x: isinstance(x, datetime.date) or x is None).all()
)
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