mirror of
https://github.com/apache/superset.git
synced 2026-04-14 21:54:31 +00:00
48 lines
1.7 KiB
Python
48 lines
1.7 KiB
Python
# 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.
|
|
import io
|
|
from typing import Any
|
|
|
|
import pandas as pd
|
|
|
|
from superset.utils.core import GenericDataType
|
|
|
|
|
|
def df_to_excel(df: pd.DataFrame, **kwargs: Any) -> Any:
|
|
output = io.BytesIO()
|
|
|
|
# pylint: disable=abstract-class-instantiated
|
|
with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
|
|
df.to_excel(writer, **kwargs)
|
|
|
|
return output.getvalue()
|
|
|
|
|
|
def apply_column_types(
|
|
df: pd.DataFrame, column_types: list[GenericDataType]
|
|
) -> pd.DataFrame:
|
|
for column, column_type in zip(df.columns, column_types):
|
|
if column_type == GenericDataType.NUMERIC:
|
|
try:
|
|
df[column] = pd.to_numeric(df[column])
|
|
except ValueError:
|
|
df[column] = df[column].astype(str)
|
|
elif pd.api.types.is_datetime64tz_dtype(df[column]):
|
|
# timezones are not supported
|
|
df[column] = df[column].astype(str)
|
|
return df
|