def isnull(input):
'''
Replacement for numpy.isnan / -numpy.isfinite which is suitable
for use on object arrays.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if isinstance(input, np.ndarray):
if input.dtype.kind in ('O', 'S'):
# Working around NumPy ticket 1542
shape = input.shape
result = np.empty(shape, dtype=bool)
vec = _tseries.isnullobj(input.ravel())
result[:] = vec.reshape(shape)
else:
result = -np.isfinite(input)
else:
result = _tseries.checknull(input)
return result
def isnull(input):
'''
Replacement for numpy.isnan / -numpy.isfinite which is suitable
for use on object arrays.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
from pandas.core.generic import PandasObject
from pandas import Series
if isinstance(input, np.ndarray):
if input.dtype.kind in ('O', 'S'):
# Working around NumPy ticket 1542
shape = input.shape
result = np.empty(shape, dtype=bool)
vec = _tseries.isnullobj(input.ravel())
result[:] = vec.reshape(shape)
if isinstance(input, Series):
result = Series(result, index=input.index, copy=False)
else:
result = -np.isfinite(input)
elif isinstance(input, PandasObject):
# TODO: optimize for DataFrame, etc.
return input.apply(isnull)
else:
result = _tseries.checknull(input)
return result
def _format(s, dtype, space=None, na_rep=None, float_format=None,
col_width=None):
def _just_help(x):
if space is None:
return x
return x[:space].ljust(space)
def _make_float_format(x):
if na_rep is not None and isnull(x):
if np.isnan(x):
x = ' ' + na_rep
return _just_help('%s' % x)
if float_format:
formatted = float_format(x)
elif print_config.float_format:
formatted = print_config.float_format(x)
else:
formatted = _float_format_default(x, col_width)
return _just_help(formatted)
def _make_int_format(x):
return _just_help('% d' % x)
if is_float_dtype(dtype):
return _make_float_format(s)
elif is_integer_dtype(dtype):
return _make_int_format(s)
else:
if na_rep is not None and lib.checknull(s):
return na_rep
else:
# object dtype
return _just_help('%s' % _stringify(s))
def _format(x):
if self.na_rep is not None and lib.checknull(x):
if x is None:
return 'None'
return self.na_rep
else:
# object dtype
return '%s' % formatter(x)
def _format(x):
if self.na_rep is not None and lib.checknull(x):
if x is None:
return 'None'
return self.na_rep
else:
# object dtype
return '%s' % formatter(x)
def notnull(input):
'''
Replacement for numpy.isfinite / -numpy.isnan which is suitable
for use on object arrays.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if isinstance(input, np.ndarray):
return -isnull(input)
else:
return not _tseries.checknull(input)
def isnull(obj):
'''
Replacement for numpy.isnan / -numpy.isfinite which is suitable
for use on object arrays.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if np.isscalar(obj) or obj is None:
return lib.checknull(obj)
from pandas.core.generic import PandasObject
from pandas import Series
if isinstance(obj, np.ndarray):
if obj.dtype.kind in ('O', 'S'):
# Working around NumPy ticket 1542
shape = obj.shape
result = np.empty(shape, dtype=bool)
vec = lib.isnullobj(obj.ravel())
result[:] = vec.reshape(shape)
if isinstance(obj, Series):
result = Series(result, index=obj.index, copy=False)
elif obj.dtype == np.dtype('M8[ns]'):
# this is the NaT pattern
result = np.array(obj).view('i8') == lib.NaT
else:
result = -np.isfinite(obj)
return result
elif isinstance(obj, PandasObject):
# TODO: optimize for DataFrame, etc.
return obj.apply(isnull)
else:
return obj is None
def _format(s,
dtype,
space=None,
na_rep=None,
float_format=None,
col_width=None):
def _just_help(x):
if space is None:
return x
return x[:space].ljust(space)
def _make_float_format(x):
if na_rep is not None and isnull(x):
if np.isnan(x):
x = ' ' + na_rep
return _just_help('%s' % x)
if float_format:
formatted = float_format(x)
elif print_config.float_format:
formatted = print_config.float_format(x)
else:
formatted = _float_format_default(x, col_width)
return _just_help(formatted)
def _make_int_format(x):
return _just_help('% d' % x)
if is_float_dtype(dtype):
return _make_float_format(s)
elif is_integer_dtype(dtype):
return _make_int_format(s)
else:
if na_rep is not None and lib.checknull(s):
return na_rep
else:
# object dtype
return _just_help('%s' % _stringify(s))
def isnull(obj):
'''
Replacement for numpy.isnan / -numpy.isfinite which is suitable
for use on object arrays.
Parameters
----------
arr: ndarray or object value
Returns
-------
boolean ndarray or boolean
'''
if np.isscalar(obj) or obj is None:
return lib.checknull(obj)
from pandas.core.generic import PandasObject
from pandas import Series
if isinstance(obj, np.ndarray):
if obj.dtype.kind in ('O', 'S'):
# Working around NumPy ticket 1542
shape = obj.shape
result = np.empty(shape, dtype=bool)
vec = lib.isnullobj(obj.ravel())
result[:] = vec.reshape(shape)
if isinstance(obj, Series):
result = Series(result, index=obj.index, copy=False)
else:
result = -np.isfinite(obj)
return result
elif isinstance(obj, PandasObject):
# TODO: optimize for DataFrame, etc.
return obj.apply(isnull)
else:
return obj is None
