text: from datetime import datetime, timedelta
  import re
  import sys
  
  import numpy as np
  
  import pandas.lib as lib
  import pandas.tslib as tslib
  import pandas.core.common as com
  from pandas.compat import StringIO, callable
  from pandas.core.common import ABCIndexClass
  import pandas.compat as compat
  from pandas.util.decorators import deprecate_kwarg
  
  try:
      import dateutil
      # raise exception if dateutil 2.0 install on 2.x platform
      if (sys.version_info[0] == 2 and
              dateutil.__version__ == '2.0'):  # pragma: no cover
          raise Exception('dateutil 2.0 incompatible with Python 2.x, you must '
                          'install version 1.5 or 2.1+!')
  except ImportError:  # pragma: no cover
      print('Please install python-dateutil via easy_install or some method!')
      raise  # otherwise a 2nd import won't show the message
  
  _DATEUTIL_LEXER_SPLIT = None
  try:
      # Since these are private methods from dateutil, it is safely imported
      # here so in case this interface changes, pandas will just fallback
      # to not using the functionality
      from dateutil.parser import _timelex
  
      if hasattr(_timelex, 'split'):
          def _lexer_split_from_str(dt_str):
              # The StringIO(str(_)) is for dateutil 2.2 compatibility
              return _timelex.split(StringIO(str(dt_str)))
  
          _DATEUTIL_LEXER_SPLIT = _lexer_split_from_str
  except (ImportError, AttributeError):
      pass
  
  def _infer_tzinfo(start, end):
      def _infer(a, b):
          tz = a.tzinfo
          if b and b.tzinfo:
              if not (tslib.get_timezone(tz) == tslib.get_timezone(b.tzinfo)):
                  raise AssertionError('Inputs must both have the same timezone,'
                                       ' {0} != {1}'.format(tz, b.tzinfo))
          return tz
      tz = None
      if start is not None:
          tz = _infer(start, end)
      elif end is not None:
          tz = _infer(end, start)
      return tz
  
  
  def _guess_datetime_format(dt_str, dayfirst=False,
                             dt_str_parse=compat.parse_date,
                             dt_str_split=_DATEUTIL_LEXER_SPLIT):
      """
      Guess the datetime format of a given datetime string.
  
      Parameters
      ----------
      dt_str : string, datetime string to guess the format of
      dayfirst : boolean, default False
          If True parses dates with the day first, eg 20/01/2005
          Warning: dayfirst=True is not strict, but will prefer to parse
          with day first (this is a known bug).
      dt_str_parse : function, defaults to `compate.parse_date` (dateutil)
          This function should take in a datetime string and return
          a `datetime.datetime` guess that the datetime string represents
      dt_str_split : function, defaults to `_DATEUTIL_LEXER_SPLIT` (dateutil)
          This function should take in a datetime string and return
          a list of strings, the guess of the various specific parts
          e.g. '2011/12/30' -> ['2011', '/', '12', '/', '30']
  
      Returns
      -------
      ret : datetime formatt string (for `strftime` or `strptime`)
      """
      if dt_str_parse is None or dt_str_split is None:
          return None
  
      if not isinstance(dt_str, compat.string_types):
          return None
  
      day_attribute_and_format = (('day',), '%d', 2)
  
      # attr name, format, padding (if any)
      datetime_attrs_to_format = [
          (('year', 'month', 'day'), '%Y%m%d', 0),
          (('year',), '%Y', 0),
          (('month',), '%B', 0),
          (('month',), '%b', 0),
          (('month',), '%m', 2),
          day_attribute_and_format,
          (('hour',), '%H', 2),
          (('minute',), '%M', 2),
          (('second',), '%S', 2),
          (('microsecond',), '%f', 6),
          (('second', 'microsecond'), '%S.%f', 0),
      ]
  
      if dayfirst:
          datetime_attrs_to_format.remove(day_attribute_and_format)
          datetime_attrs_to_format.insert(0, day_attribute_and_format)
  
      try:
          parsed_datetime = dt_str_parse(dt_str, dayfirst=dayfirst)
      except:
          # In case the datetime can't be parsed, its format cannot be guessed
          return None
  
      if parsed_datetime is None:
          return None
  
      try:
          tokens = dt_str_split(dt_str)
      except:
          # In case the datetime string can't be split, its format cannot
          # be guessed
          return None
  
      format_guess = [None] * len(tokens)
      found_attrs = set()
  
      for attrs, attr_format, padding in datetime_attrs_to_format:
          # If a given attribute has been placed in the format string, skip
          # over other formats for that same underlying attribute (IE, month
          # can be represented in multiple different ways)
          if set(attrs) & found_attrs:
              continue
  
          if all(getattr(parsed_datetime, attr) is not None for attr in attrs):
              for i, token_format in enumerate(format_guess):
                  token_filled = tokens[i].zfill(padding)
                  if (token_format is None and
                          token_filled == parsed_datetime.strftime(attr_format)):
                      format_guess[i] = attr_format
                      tokens[i] = token_filled
                      found_attrs.update(attrs)
                      break
  
      # Only consider it a valid guess if we have a year, month and day
      if len(set(['year', 'month', 'day']) & found_attrs) != 3:
          return None
  
      output_format = []
      for i, guess in enumerate(format_guess):
          if guess is not None:
              # Either fill in the format placeholder (like %Y)
              output_format.append(guess)
          else:
              # Or just the token separate (IE, the dashes in "01-01-2013")
              try:
                  # If the token is numeric, then we likely didn't parse it
                  # properly, so our guess is wrong
                  float(tokens[i])
                  return None
              except ValueError:
                  pass
  
              output_format.append(tokens[i])
  
      guessed_format = ''.join(output_format)
  
      # rebuild string, capturing any inferred padding
      dt_str = ''.join(tokens)
      if parsed_datetime.strftime(guessed_format) == dt_str:
          return guessed_format
  
  def _guess_datetime_format_for_array(arr, **kwargs):
      # Try to guess the format based on the first non-NaN element
      non_nan_elements = com.notnull(arr).nonzero()[0]
      if len(non_nan_elements):
          return _guess_datetime_format(arr[non_nan_elements[0]], **kwargs)
  
  
  @deprecate_kwarg(old_arg_name='coerce', new_arg_name='errors',
                   mapping={True: 'coerce', False: 'raise'})
  def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
                  utc=None, box=True, format=None, exact=True, coerce=None,
                  unit='ns', infer_datetime_format=False):
      """
      Convert argument to datetime.
  
      Parameters
      ----------
      arg : string, datetime, list, tuple, 1-d array, or Series
      errors : {'ignore', 'raise', 'coerce'}, default 'raise'
          - If 'raise', then invalid parsing will raise an exception
          - If 'coerce', then invalid parsing will be set as NaT
          - If 'ignore', then invalid parsing will return the input
      dayfirst : boolean, default False
          Specify a date parse order if `arg` is str or its list-likes.
          If True, parses dates with the day first, eg 10/11/12 is parsed as 2012-11-10.
          Warning: dayfirst=True is not strict, but will prefer to parse
          with day first (this is a known bug, based on dateutil behavior).
      yearfirst : boolean, default False
          Specify a date parse order if `arg` is str or its list-likes.
          - If True parses dates with the year first, eg 10/11/12 is parsed as 2010-11-12.
          - If both dayfirst and yearfirst are True, yearfirst is preceded (same as dateutil).
          Warning: yearfirst=True is not strict, but will prefer to parse
          with year first (this is a known bug, based on dateutil beahavior).
  
          .. versionadded: 0.16.1
  
      utc : boolean, default None
          Return UTC DatetimeIndex if True (converting any tz-aware
          datetime.datetime objects as well).
      box : boolean, default True
          - If True returns a DatetimeIndex
          - If False returns ndarray of values.
      format : string, default None
          strftime to parse time, eg "%d/%m/%Y", note that "%f" will parse
          all the way up to nanoseconds.
      exact : boolean, True by default
          - If True, require an exact format match.
          - If False, allow the format to match anywhere in the target string.
      unit : unit of the arg (D,s,ms,us,ns) denote the unit in epoch
          (e.g. a unix timestamp), which is an integer/float number.
      infer_datetime_format : boolean, default False
          If no `format` is given, try to infer the format based on the first
          datetime string. Provides a large speed-up in many cases.
  
      Returns
      -------
      ret : datetime if parsing succeeded.
          Return type depends on input:
  
          - list-like: DatetimeIndex
          - Series: Series of datetime64 dtype
          - scalar: Timestamp
  
          In case when it is not possible to return designated types (e.g. when
          any element of input is before Timestamp.min or after Timestamp.max)
          return will have datetime.datetime type (or correspoding array/Series).
  
      Examples
      --------
      Take separate series and convert to datetime
  
      >>> import pandas as pd
      >>> i = pd.date_range('20000101',periods=100)
      >>> df = pd.DataFrame(dict(year = i.year, month = i.month, day = i.day))
      >>> pd.to_datetime(df.year*10000 + df.month*100 + df.day, format='%Y%m%d')
      0    2000-01-01
      1    2000-01-02
      ...
      98   2000-04-08
      99   2000-04-09
      Length: 100, dtype: datetime64[ns]
  
      Or from strings
  
      >>> df = df.astype(str)
      >>> pd.to_datetime(df.day + df.month + df.year, format="%d%m%Y")
      0    2000-01-01
      1    2000-01-02
      ...
      98   2000-04-08
      99   2000-04-09
      Length: 100, dtype: datetime64[ns]
  
      Date that does not meet timestamp limitations:
  
      >>> pd.to_datetime('13000101', format='%Y%m%d')
      datetime.datetime(1300, 1, 1, 0, 0)
      >>> pd.to_datetime('13000101', format='%Y%m%d', errors='coerce')
      NaT
      """
      return _to_datetime(arg, errors=errors, dayfirst=dayfirst, yearfirst=yearfirst,
                          utc=utc, box=box, format=format, exact=exact,
                          unit=unit, infer_datetime_format=infer_datetime_format)
  
  
  def _to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
                   utc=None, box=True, format=None, exact=True,
                   unit='ns', freq=None, infer_datetime_format=False):
      """
      Same as to_datetime, but accept freq for
      DatetimeIndex internal construction
      """
      from pandas.core.series import Series
      from pandas.tseries.index import DatetimeIndex
  
      def _convert_listlike(arg, box, format, name=None):
  
          if isinstance(arg, (list, tuple)):
              arg = np.array(arg, dtype='O')
  
          # these are shortcutable
          if com.is_datetime64_ns_dtype(arg):
              if box and not isinstance(arg, DatetimeIndex):
                  try:
                      return DatetimeIndex(arg, tz='utc' if utc else None, name=name)
                  except ValueError:
                      pass
  
              return arg
  
          elif com.is_datetime64tz_dtype(arg):
              if not isinstance(arg, DatetimeIndex):
                  return DatetimeIndex(arg, tz='utc' if utc else None)
              if utc:
                  arg = arg.tz_convert(None)
              return arg
  
          elif format is None and com.is_integer_dtype(arg) and unit=='ns':
              result = arg.astype('datetime64[ns]')
              if box:
                  return DatetimeIndex(result, tz='utc' if utc else None, name=name)
              return result
          elif getattr(arg, 'ndim', 1) > 1:
              raise TypeError('arg must be a string, datetime, list, tuple, 1-d array, or Series')
  
          arg = com._ensure_object(arg)
          require_iso8601 = False
  
          if infer_datetime_format and format is None:
              format = _guess_datetime_format_for_array(arg, dayfirst=dayfirst)
  
          if format is not None:
              # There is a special fast-path for iso8601 formatted
              # datetime strings, so in those cases don't use the inferred
              # format because this path makes process slower in this
              # special case
              format_is_iso8601 = (
                  ('%Y-%m-%dT%H:%M:%S.%f'.startswith(format) or
                  '%Y-%m-%d %H:%M:%S.%f'.startswith(format)) and
  				format != '%Y'
              )
              if format_is_iso8601:
                  require_iso8601 = not infer_datetime_format
                  format = None
  
          try:
              result = None
  
              if format is not None:
                  # shortcut formatting here
                  if format == '%Y%m%d':
                      try:
                          result = _attempt_YYYYMMDD(arg, errors=errors)
                      except:
                          raise ValueError("cannot convert the input to '%Y%m%d' date format")
  
                  # fallback
                  if result is None:
                      try:
                          result = tslib.array_strptime(
                              arg, format, exact=exact, errors=errors)
                      except (tslib.OutOfBoundsDatetime):
                          if errors == 'raise':
                              raise
                          result = arg
                      except ValueError:
                          # if format was inferred, try falling back
                          # to array_to_datetime - terminate here
                          # for specified formats
                          if not infer_datetime_format:
                              if errors == 'raise':
                                  raise
                              result = arg
  
              if result is None and (format is None or infer_datetime_format):
                  result = tslib.array_to_datetime(arg, errors=errors,
                                                   utc=utc, dayfirst=dayfirst,
                                                   yearfirst=yearfirst, freq=freq,
                                                   unit=unit,
                                                   require_iso8601=require_iso8601)
  
              if com.is_datetime64_dtype(result) and box:
                  result = DatetimeIndex(result, tz='utc' if utc else None, name=name)
              return result
  
          except ValueError as e:
              try:
                  values, tz = tslib.datetime_to_datetime64(arg)
                  return DatetimeIndex._simple_new(values, name=name, tz=tz)
              except (ValueError, TypeError):
                  raise e
  
      if arg is None:
          return arg
      elif isinstance(arg, tslib.Timestamp):
          return arg
      elif isinstance(arg, Series):
          values = _convert_listlike(arg._values, False, format)
          return Series(values, index=arg.index, name=arg.name)
      elif isinstance(arg, ABCIndexClass):
          return _convert_listlike(arg, box, format, name=arg.name)
      elif com.is_list_like(arg):
          return _convert_listlike(arg, box, format)
  
      return _convert_listlike(np.array([ arg ]), box, format)[0]
  
  
  def _attempt_YYYYMMDD(arg, errors):
      """ try to parse the YYYYMMDD/%Y%m%d format, try to deal with NaT-like,
          arg is a passed in as an object dtype, but could really be ints/strings with nan-like/or floats (e.g. with nan)
  
          Parameters
          ----------
          arg : passed value
          errors : 'raise','ignore','coerce'
          """
  
      def calc(carg):
          # calculate the actual result
          carg = carg.astype(object)
          return tslib.array_to_datetime(lib.try_parse_year_month_day(carg/10000,carg/100 % 100, carg % 100), errors=errors)
  
      def calc_with_mask(carg,mask):
          result = np.empty(carg.shape, dtype='M8[ns]')
          iresult = result.view('i8')
          iresult[~mask] = tslib.iNaT
          result[mask] = calc(carg[mask].astype(np.float64).astype(np.int64)).astype('M8[ns]')
          return result
  
      # try intlike / strings that are ints
      try:
          return calc(arg.astype(np.int64))
      except:
          pass
  
      # a float with actual np.nan
      try:
          carg = arg.astype(np.float64)
          return calc_with_mask(carg,com.notnull(carg))
      except:
          pass
  
      # string with NaN-like
      try:
          mask = ~lib.ismember(arg, tslib._nat_strings)
          return calc_with_mask(arg,mask)
      except:
          pass
  
      return None
  
  
  def parse_time_string(arg, freq=None, dayfirst=None, yearfirst=None):
      """
      Try hard to parse datetime string, leveraging dateutil plus some extra
      goodies like quarter recognition.
  
      Parameters
      ----------
      arg : compat.string_types
      freq : str or DateOffset, default None
          Helps with interpreting time string if supplied
      dayfirst : bool, default None
          If None uses default from print_config
      yearfirst : bool, default None
          If None uses default from print_config
  
      Returns
      -------
      datetime, datetime/dateutil.parser._result, str
      """
      from pandas.core.config import get_option
      if not isinstance(arg, compat.string_types):
          return arg
  
      from pandas.tseries.offsets import DateOffset
      if isinstance(freq, DateOffset):
          freq = freq.rule_code
  
      if dayfirst is None:
          dayfirst = get_option("display.date_dayfirst")
      if yearfirst is None:
          yearfirst = get_option("display.date_yearfirst")
  
      return tslib.parse_datetime_string_with_reso(arg, freq=freq, dayfirst=dayfirst,
                                                   yearfirst=yearfirst)
  
  
  DateParseError = tslib.DateParseError
  normalize_date = tslib.normalize_date
  
  
  def format(dt):
      """Returns date in YYYYMMDD format."""
      return dt.strftime('%Y%m%d')
  
  OLE_TIME_ZERO = datetime(1899, 12, 30, 0, 0, 0)
  
  
  def ole2datetime(oledt):
      """function for converting excel date to normal date format"""
      val = float(oledt)
  
      # Excel has a bug where it thinks the date 2/29/1900 exists
      # we just reject any date before 3/1/1900.
      if val < 61:
          raise ValueError("Value is outside of acceptable range: %s " % val)
  
      return OLE_TIME_ZERO + timedelta(days=val)
  