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CLN: remove Panel-specific parts of core.generic #26738

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Merged
merged 4 commits into from
Jun 9, 2019
Merged

CLN: remove Panel-specific parts of core.generic #26738

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b7d221d
CLN: remove Panel-specific parts of core.generic
simonjayhawkins Jun 8, 2019
ff2747d
remove monkeypatch from test_ndframe_not_implemented_raises
simonjayhawkins Jun 8, 2019
626c4dc
remove ndim>2 checks
simonjayhawkins Jun 8, 2019
a2cedd7
Merge remote-tracking branch 'upstream/master' into core-generic
simonjayhawkins Jun 8, 2019
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80 changes: 6 additions & 74 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1570,11 +1570,6 @@ def _is_level_reference(self, key, axis=0):
"""
axis = self._get_axis_number(axis)
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actually I wouldn't worry about checking ndim at all in any methods and just remove all of the checks.

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sounds good. thanks.


if self.ndim > 2:
raise NotImplementedError(
"_is_level_reference is not implemented for {type}"
.format(type=type(self)))

return (key is not None and
is_hashable(key) and
key in self.axes[axis].names and
Expand All @@ -1600,11 +1595,6 @@ def _is_label_reference(self, key, axis=0):
-------
is_label: bool
"""
if self.ndim > 2:
raise NotImplementedError(
"_is_label_reference is not implemented for {type}"
.format(type=type(self)))

axis = self._get_axis_number(axis)
other_axes = (ax for ax in range(self._AXIS_LEN) if ax != axis)

Expand Down Expand Up @@ -1632,12 +1622,6 @@ def _is_label_or_level_reference(self, key, axis=0):
-------
is_label_or_level: bool
"""

if self.ndim > 2:
raise NotImplementedError(
"_is_label_or_level_reference is not implemented for {type}"
.format(type=type(self)))

return (self._is_level_reference(key, axis=axis) or
self._is_label_reference(key, axis=axis))

Expand All @@ -1659,11 +1643,6 @@ def _check_label_or_level_ambiguity(self, key, axis=0):
------
ValueError: `key` is ambiguous
"""
if self.ndim > 2:
raise NotImplementedError(
"_check_label_or_level_ambiguity is not implemented for {type}"
.format(type=type(self)))

axis = self._get_axis_number(axis)
other_axes = (ax for ax in range(self._AXIS_LEN) if ax != axis)

Expand Down Expand Up @@ -1724,11 +1703,6 @@ def _get_label_or_level_values(self, key, axis=0):
if `key` is ambiguous. This will become an ambiguity error in a
future version
"""
if self.ndim > 2:
raise NotImplementedError(
"_get_label_or_level_values is not implemented for {type}"
.format(type=type(self)))

axis = self._get_axis_number(axis)
other_axes = [ax for ax in range(self._AXIS_LEN) if ax != axis]

Expand Down Expand Up @@ -1787,11 +1761,6 @@ def _drop_labels_or_levels(self, keys, axis=0):
ValueError
if any `keys` match neither a label nor a level
"""
if self.ndim > 2:
raise NotImplementedError(
"_drop_labels_or_levels is not implemented for {type}"
.format(type=type(self)))

axis = self._get_axis_number(axis)

# Validate keys
Expand Down Expand Up @@ -2781,7 +2750,6 @@ class (index) object 'bird' 'bird' 'mammal' 'mammal'
Data variables:
speed (date, animal) int64 350 18 361 15
"""

try:
import xarray
except ImportError:
Expand All @@ -2794,15 +2762,9 @@ class (index) object 'bird' 'bird' 'mammal' 'mammal'

if self.ndim == 1:
return xarray.DataArray.from_series(self)
elif self.ndim == 2:
else:
return xarray.Dataset.from_dataframe(self)

# > 2 dims
coords = [(a, self._get_axis(a)) for a in self._AXIS_ORDERS]
return xarray.DataArray(self,
coords=coords,
)

def to_latex(self, buf=None, columns=None, col_space=None, header=True,
index=True, na_rep='NaN', formatters=None, float_format=None,
sparsify=None, index_names=True, bold_rows=False,
Expand Down Expand Up @@ -5692,11 +5654,7 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
'the key in Series dtype mappings.')
new_type = dtype[self.name]
return self.astype(new_type, copy, errors, **kwargs)
elif self.ndim > 2:
raise NotImplementedError(
'astype() only accepts a dtype arg of type dict when '
'invoked on Series and DataFrames.'
)

for col_name in dtype.keys():
if col_name not in self:
raise KeyError('Only a column name can be used for the '
Expand Down Expand Up @@ -6051,26 +6009,10 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,

return result

# > 3d
if self.ndim > 3:
raise NotImplementedError('Cannot fillna with a method for > '
'3dims')

# 3d
elif self.ndim == 3:
# fill in 2d chunks
result = {col: s.fillna(method=method, value=value)
for col, s in self.iteritems()}
prelim_obj = self._constructor.from_dict(result)
new_obj = prelim_obj.__finalize__(self)
new_data = new_obj._data

else:
# 2d or less
new_data = self._data.interpolate(method=method, axis=axis,
limit=limit, inplace=inplace,
coerce=True,
downcast=downcast)
new_data = self._data.interpolate(method=method, axis=axis,
limit=limit, inplace=inplace,
coerce=True,
downcast=downcast)
else:
if len(self._get_axis(axis)) == 0:
return self
Expand Down Expand Up @@ -6782,9 +6724,6 @@ def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
"""
inplace = validate_bool_kwarg(inplace, 'inplace')

if self.ndim > 2:
raise NotImplementedError("Interpolate has not been implemented ")

if axis == 0:
ax = self._info_axis_name
_maybe_transposed_self = self
Expand Down Expand Up @@ -6964,9 +6903,6 @@ def asof(self, where, subset=None):
if is_series:
if subset is not None:
raise ValueError("subset is not valid for Series")
elif self.ndim > 2:
raise NotImplementedError("asof is not implemented "
"for {type}".format(type=type(self)))
else:
if subset is None:
subset = self.columns
Expand Down Expand Up @@ -8373,10 +8309,6 @@ def rank(self, axis=0, method='average', numeric_only=None,
"""
axis = self._get_axis_number(axis)

if self.ndim > 2:
msg = "rank does not make sense when ndim > 2"
raise NotImplementedError(msg)

if na_option not in {'keep', 'top', 'bottom'}:
msg = "na_option must be one of 'keep', 'top', or 'bottom'"
raise ValueError(msg)
Expand Down