# pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed 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.
# ==============================================================================

"""Methods to allow pandas.DataFrame."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

try:
  # pylint: disable=g-import-not-at-top
  import pandas as pd
  HAS_PANDAS = True
except ImportError:
  HAS_PANDAS = False

PANDAS_DTYPES = {
    'int8': 'int',
    'int16': 'int',
    'int32': 'int',
    'int64': 'int',
    'uint8': 'int',
    'uint16': 'int',
    'uint32': 'int',
    'uint64': 'int',
    'float16': 'float',
    'float32': 'float',
    'float64': 'float',
    'bool': 'i'
}


def extract_pandas_data(data):
  """Extract data from pandas.DataFrame for predictors."""
  if not isinstance(data, pd.DataFrame):
    return data

  if all(dtype.name in PANDAS_DTYPES for dtype in data.dtypes):
    return data.values.astype('float')
  else:
    raise ValueError('Data types for data must be int, float, or bool.')


def extract_pandas_matrix(data):
  """Extracts numpy matrix from pandas DataFrame."""
  if not isinstance(data, pd.DataFrame):
    return data

  return data.as_matrix()


def extract_pandas_labels(labels):
  """Extract data from pandas.DataFrame for labels."""
  if isinstance(labels,
                pd.DataFrame):  # pandas.Series also belongs to DataFrame
    if len(labels.columns) > 1:
      raise ValueError('Only one column for labels is allowed.')

    if all(dtype.name in PANDAS_DTYPES for dtype in labels.dtypes):
      return labels.values.astype('float')
    else:
      raise ValueError('Data types for labels must be int, float, or bool.')
  else:
    return labels
