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Merged
merged 6 commits into from
May 7, 2019
Merged

Remove Panel References #26287

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4f4720b
Removed panel references from code base
WillAyd May 6, 2019
bc30088
Lint fixup
WillAyd May 6, 2019
f7b0678
Merge remote-tracking branch 'upstream/master' into panel-cleanups
WillAyd May 7, 2019
d5bf221
lint fixup
WillAyd May 7, 2019
39e46b3
Removed validate_transpose_for_generic
WillAyd May 7, 2019
c4cd707
Replaced NotImplemented with AbstractMethodError
WillAyd May 7, 2019
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17 changes: 0 additions & 17 deletions pandas/compat/numpy/function.py
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Original file line number Diff line number Diff line change
Expand Up @@ -287,23 +287,6 @@ def validate_take_with_convert(convert, args, kwargs):
method='both', max_fname_arg_count=0)


def validate_transpose_for_generic(inst, kwargs):
try:
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This previously was only modifying the exception message for Panel objects before raising again, so I simplified to just remove the try...except altogether and let it raise as is

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If it’s a one liner now, Is this still needed as a separate function?

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Yea could probably just call this directly now; I'll give it a look tonight and repush

validate_transpose(tuple(), kwargs)
except ValueError as e:
klass = type(inst).__name__
msg = str(e)

# the Panel class actual relies on the 'axes' parameter if called
# via the 'numpy' library, so let's make sure the error is specific
# about saying that the parameter is not supported for particular
# implementations of 'transpose'
if "the 'axes' parameter is not supported" in msg:
msg += " for {klass} instances".format(klass=klass)

raise ValueError(msg)


def validate_window_func(name, args, kwargs):
numpy_args = ('axis', 'dtype', 'out')
msg = ("numpy operations are not "
Expand Down
23 changes: 2 additions & 21 deletions pandas/core/frame.py
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Expand Up @@ -368,9 +368,7 @@ def _constructor(self):

@property
def _constructor_expanddim(self):
# TODO: Raise NotImplementedError or change note in extending.rst
from pandas.core.panel import Panel
return Panel
raise NotImplementedError("Not supported for DataFrames!")
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The TODO mentions changing the docs extending.rst but that looks to have already been done


# ----------------------------------------------------------------------
# Constructors
Expand Down Expand Up @@ -1934,22 +1932,6 @@ def to_sparse(self, fill_value=None, kind='block'):
columns=self.columns, default_kind=kind,
default_fill_value=fill_value)

def to_panel(self):
"""
Transform long (stacked) format (DataFrame) into wide (3D, Panel)
format.

.. deprecated:: 0.20.0

Currently the index of the DataFrame must be a 2-level MultiIndex. This
may be generalized later

Returns
-------
Panel
"""
raise NotImplementedError("Panel is being removed in pandas 0.25.0.")

@deprecate_kwarg(old_arg_name='encoding', new_arg_name=None)
def to_stata(self, fname, convert_dates=None, write_index=True,
encoding="latin-1", byteorder=None, time_stamp=None,
Expand Down Expand Up @@ -6638,8 +6620,7 @@ def append(self, other, ignore_index=False,

See Also
--------
concat : General function to concatenate DataFrame, Series
or Panel objects.
concat : General function to concatenate DataFrame or Series objects.

Notes
-----
Expand Down
40 changes: 15 additions & 25 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@
is_dict_like, is_extension_array_dtype, is_integer, is_list_like,
is_number, is_numeric_dtype, is_object_dtype, is_period_arraylike,
is_re_compilable, is_scalar, is_timedelta64_dtype, pandas_dtype)
from pandas.core.dtypes.generic import ABCDataFrame, ABCPanel, ABCSeries
from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries
from pandas.core.dtypes.inference import is_hashable
from pandas.core.dtypes.missing import isna, notna

Expand Down Expand Up @@ -688,7 +688,7 @@ def transpose(self, *args, **kwargs):
if kwargs.pop('copy', None) or (len(args) and args[-1]):
new_values = new_values.copy()

nv.validate_transpose_for_generic(self, kwargs)
nv.validate_transpose(tuple(), kwargs)
return self._constructor(new_values, **new_axes).__finalize__(self)

def swapaxes(self, axis1, axis2, copy=True):
Expand Down Expand Up @@ -978,7 +978,7 @@ def rename(self, *args, **kwargs):
----------
%(axes)s : scalar, list-like, dict-like or function, optional
Scalar or list-like will alter the ``Series.name`` attribute,
and raise on DataFrame or Panel.
and raise on DataFrame.
dict-like or functions are transformations to apply to
that axis' values
copy : bool, default True
Expand Down Expand Up @@ -1852,16 +1852,14 @@ def __iter__(self):
def keys(self):
"""Get the 'info axis' (see Indexing for more)

This is index for Series, columns for DataFrame and major_axis for
Panel.
This is index for Series, columns for DataFrame.
"""
return self._info_axis

def iteritems(self):
"""Iterate over (label, values) on info axis

This is index for Series, columns for DataFrame, major_axis for Panel,
and so on.
This is index for Series, columns for DataFrame and so on.
"""
for h in self._info_axis:
yield h, self[h]
Expand Down Expand Up @@ -3063,8 +3061,9 @@ def _create_indexer(cls, name, indexer):

def get(self, key, default=None):
"""
Get item from object for given key (DataFrame column, Panel slice,
etc.). Returns default value if not found.
Get item from object for given key (ex: DataFrame column).

Returns default value if not found.

Parameters
----------
Expand Down Expand Up @@ -4091,8 +4090,7 @@ def sort_values(self, by=None, axis=0, ascending=True, inplace=False,
0 A 2 0
1 A 1 1
"""
raise NotImplementedError("sort_values has not been implemented "
"on Panel or Panel4D objects.")
raise AbstractMethodError(self)

def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
kind='quicksort', na_position='last', sort_remaining=True):
Expand Down Expand Up @@ -4770,7 +4768,7 @@ def sample(self, n=None, frac=None, replace=False, weights=None,
object.
axis : int or string, optional
Axis to sample. Accepts axis number or name. Default is stat axis
for given data type (0 for Series and DataFrames, 1 for Panels).
for given data type (0 for Series and DataFrames).

Returns
-------
Expand Down Expand Up @@ -4853,7 +4851,7 @@ def sample(self, n=None, frac=None, replace=False, weights=None,
"a DataFrame")
else:
raise ValueError("Strings cannot be passed as weights "
"when sampling from a Series or Panel.")
"when sampling from a Series.")

weights = pd.Series(weights, dtype='float64')

Expand Down Expand Up @@ -5697,8 +5695,7 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
elif self.ndim > 2:
raise NotImplementedError(
'astype() only accepts a dtype arg of type dict when '
'invoked on Series and DataFrames. A single dtype must be '
'specified when invoked on a Panel.'
'invoked on Series and DataFrames.'
)
for col_name in dtype.keys():
if col_name not in self:
Expand Down Expand Up @@ -5751,7 +5748,7 @@ def copy(self, deep=True):

Returns
-------
copy : Series, DataFrame or Panel
copy : Series or DataFrame
Object type matches caller.

Notes
Expand Down Expand Up @@ -6822,8 +6819,7 @@ 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 "
"on Panel and Panel 4D objects.")
raise NotImplementedError("Interpolate has not been implemented ")

if axis == 0:
ax = self._info_axis_name
Expand Down Expand Up @@ -7326,9 +7322,6 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
3 6 8
4 5 3
"""
if isinstance(self, ABCPanel):
raise NotImplementedError("clip is not supported yet for panels")

inplace = validate_bool_kwarg(inplace, 'inplace')

axis = nv.validate_clip_with_axis(axis, args, kwargs)
Expand Down Expand Up @@ -9824,10 +9817,7 @@ def describe(self, percentiles=None, include=None, exclude=None):
75% NaN 2.5
max NaN 3.0
"""
if self.ndim >= 3:
msg = "describe is not implemented on Panel objects."
raise NotImplementedError(msg)
elif self.ndim == 2 and self.columns.size == 0:
if self.ndim == 2 and self.columns.size == 0:
raise ValueError("Cannot describe a DataFrame without columns")

if percentiles is not None:
Expand Down
1 change: 0 additions & 1 deletion pandas/core/groupby/groupby.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,6 @@ class providing the base-class of operations.
--------
Series.%(name)s
DataFrame.%(name)s
Panel.%(name)s
"""

_apply_docs = dict(
Expand Down
140 changes: 2 additions & 138 deletions pandas/core/ops.py
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Expand Up @@ -23,7 +23,7 @@
is_integer_dtype, is_list_like, is_object_dtype, is_period_dtype,
is_scalar, is_timedelta64_dtype, needs_i8_conversion)
from pandas.core.dtypes.generic import (
ABCDataFrame, ABCIndex, ABCIndexClass, ABCPanel, ABCSeries, ABCSparseArray,
ABCDataFrame, ABCIndex, ABCIndexClass, ABCSeries, ABCSparseArray,
ABCSparseSeries)
from pandas.core.dtypes.missing import isna, notna

Expand Down Expand Up @@ -234,7 +234,7 @@ def _gen_eval_kwargs(name):
"""
kwargs = {}

# Series and Panel appear to only pass __add__, __radd__, ...
# Series appear to only pass __add__, __radd__, ...
# but DataFrame gets both these dunder names _and_ non-dunder names
# add, radd, ...
name = name.replace('__', '')
Expand Down Expand Up @@ -991,40 +991,6 @@ def _get_op_name(op, special):
C True False
"""

_flex_doc_PANEL = """
Return {desc} of series and other, element-wise (binary operator `{op_name}`).
Equivalent to ``{equiv}``.

Parameters
----------
other : DataFrame or Panel
axis : {{items, major_axis, minor_axis}}
Axis to broadcast over

Returns
-------
Panel

See Also
--------
Panel.{reverse}
"""


_agg_doc_PANEL = """
Wrapper method for {op_name}

Parameters
----------
other : DataFrame or Panel
axis : {{items, major_axis, minor_axis}}
Axis to broadcast over

Returns
-------
Panel
"""


def _make_flex_doc(op_name, typ):
"""
Expand Down Expand Up @@ -1069,14 +1035,6 @@ def _make_flex_doc(op_name, typ):
equiv=equiv,
reverse=op_desc['reverse']
)
elif typ == 'panel':
base_doc = _flex_doc_PANEL
doc = base_doc.format(
desc=op_desc['desc'],
op_name=op_name,
equiv=equiv,
reverse=op_desc['reverse']
)
else:
raise AssertionError('Invalid typ argument.')
return doc
Expand Down Expand Up @@ -1457,12 +1415,6 @@ def _get_method_wrappers(cls):
arith_special = _arith_method_SPARSE_ARRAY
comp_special = _arith_method_SPARSE_ARRAY
bool_special = _arith_method_SPARSE_ARRAY
elif issubclass(cls, ABCPanel):
arith_flex = _flex_method_PANEL
comp_flex = _comp_method_PANEL
arith_special = _arith_method_PANEL
comp_special = _comp_method_PANEL
bool_special = _arith_method_PANEL
elif issubclass(cls, ABCDataFrame):
# Same for DataFrame and SparseDataFrame
arith_flex = _arith_method_FRAME
Expand Down Expand Up @@ -2295,94 +2247,6 @@ def f(self, other):
return f


# -----------------------------------------------------------------------------
# Panel

def _arith_method_PANEL(cls, op, special):
# work only for scalars
op_name = _get_op_name(op, special)

def f(self, other):
if not is_scalar(other):
raise ValueError('Simple arithmetic with {name} can only be '
'done with scalar values'
.format(name=self._constructor.__name__))

return self._combine(other, op)

f.__name__ = op_name
return f


def _comp_method_PANEL(cls, op, special):
str_rep = _get_opstr(op, cls)
op_name = _get_op_name(op, special)

def na_op(x, y):
import pandas.core.computation.expressions as expressions

try:
result = expressions.evaluate(op, str_rep, x, y)
except TypeError:
result = mask_cmp_op(x, y, op, np.ndarray)
return result

@Appender('Wrapper for comparison method {name}'.format(name=op_name))
def f(self, other, axis=None):
# Validate the axis parameter
if axis is not None:
self._get_axis_number(axis)

if isinstance(other, self._constructor):
return self._compare_constructor(other, na_op)
elif isinstance(other, (self._constructor_sliced, ABCDataFrame,
ABCSeries)):
raise Exception("input needs alignment for this object [{object}]"
.format(object=self._constructor))
else:
return self._combine_const(other, na_op)

f.__name__ = op_name

return f


def _flex_method_PANEL(cls, op, special):
str_rep = _get_opstr(op, cls)
op_name = _get_op_name(op, special)
eval_kwargs = _gen_eval_kwargs(op_name)
fill_zeros = _gen_fill_zeros(op_name)

def na_op(x, y):
import pandas.core.computation.expressions as expressions

try:
result = expressions.evaluate(op, str_rep, x, y,
errors='raise',
**eval_kwargs)
except TypeError:
result = op(x, y)

# handles discrepancy between numpy and numexpr on division/mod
# by 0 though, given that these are generally (always?)
# non-scalars, I'm not sure whether it's worth it at the moment
result = missing.fill_zeros(result, x, y, op_name, fill_zeros)
return result

if op_name in _op_descriptions:
doc = _make_flex_doc(op_name, 'panel')
else:
# doc strings substitors
doc = _agg_doc_PANEL.format(op_name=op_name)

@Appender(doc)
def f(self, other, axis=0):
return self._combine(other, na_op, axis=axis)

f.__name__ = op_name
return f


# -----------------------------------------------------------------------------
# Sparse

Expand Down
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