def to_datetime(arg, errors='ignore', dayfirst=False, box=True):
"""
Convert argument to datetime
Parameters
----------
arg : string, datetime, array of strings (with possible NAs)
errors : {'ignore', 'raise'}, default 'ignore'
Errors are ignored by default (values left untouched)
Returns
-------
ret : datetime if parsing succeeded
"""
from pandas.core.series import Series
from pandas.tseries.index import DatetimeIndex
if arg is None:
return arg
elif isinstance(arg, datetime):
return arg
elif isinstance(arg, Series):
values = lib.array_to_datetime(com._ensure_object(arg.values),
raise_=errors == 'raise',
dayfirst=dayfirst)
return Series(values, index=arg.index, name=arg.name)
elif isinstance(arg, (np.ndarray, list)):
if isinstance(arg, list):
arg = np.array(arg, dtype='O')
result = lib.array_to_datetime(com._ensure_object(arg),
raise_=errors == 'raise',
dayfirst=dayfirst)
if com.is_datetime64_dtype(result) and box:
result = DatetimeIndex(result)
return result
try:
if not arg:
return arg
return _dtparser.parse(arg, dayfirst=dayfirst)
except Exception:
if errors == 'raise':
raise
return arg
def _convert_f(arg):
arg = com._ensure_object(arg)
try:
result = lib.array_to_datetime(arg, raise_=errors == 'raise',
utc=utc, dayfirst=dayfirst)
if com.is_datetime64_dtype(result) and box:
result = DatetimeIndex(result, tz='utc' if utc else None)
return result
except ValueError, e:
try:
values, tz = lib.datetime_to_datetime64(arg)
return DatetimeIndex._simple_new(values, None, tz=tz)
except (ValueError, TypeError):
raise e