8000 DEPR: Remove Panel-specific parts of io.pytables by jbrockmendel · Pull Request #25233 · pandas-dev/pandas · GitHub
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DEPR: Remove Panel-specific parts of io.pytables #25233

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Merged
merged 4 commits into from
Feb 8, 2019
Merged

DEPR: Remove Panel-specific parts of io.pytables #25233

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4f1f87c
disable LegacyTable read of dim>2 objects
jbrockmendel Feb 8, 2019
43f5dd1
remove code only used by io.pytables for Panel
jbrockmendel Feb 8, 2019
d8d45ea
remove Panel-specific classes in io.pytables
jbrockmendel Feb 8, 2019
8e1534a
typo fixups
jbrockmendel Feb 8, 2019
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remove code only used by io.pytables for Panel
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@jbrockmendel
jbrockmendel committed Feb 8, 2019
commit 43f5dd1af4ce2155a9af8263cdc41db673ac38a6
2 changes: 1 addition & 1 deletion pandas/core/internals/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# -*- coding: utf-8 -*-
from .blocks import ( # noqa:F401
_block2d_to_blocknd, _factor_indexer, _block_shape, # io.pytables
_block_shape, # io.pytables
_safe_reshape, # io.packers
make_block, # io.pytables, io.packers
FloatBlock, IntBlock, ComplexBlock, BoolBlock, ObjectBlock,
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35 changes: 0 additions & 35 deletions pandas/core/internals/blocks.py
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Expand Up @@ -3134,31 +3134,6 @@ def _merge_blocks(blocks, dtype=None, _can_consolidate=True):
return blocks


def _block2d_to_blocknd(values, placement, shape, labels, ref_items):
""" pivot to the labels shape """
panel_shape = (len(placement),) + shape

# TODO: lexsort depth needs to be 2!!

# Create observation selection vector using major and minor
# labels, for converting to panel format.
selector = _factor_indexer(shape[1:], labels)
mask = np.zeros(np.prod(shape), dtype=bool)
mask.put(selector, True)

if mask.all():
pvalues = np.empty(panel_shape, dtype=values.dtype)
else:
dtype, fill_value = maybe_promote(values.dtype)
pvalues = np.empty(panel_shape, dtype=dtype)
pvalues.fill(fill_value)

for i in range(len(placement)):
pvalues[i].flat[mask] = values[:, i]

return make_block(pvalues, placement=placement)


def _safe_reshape(arr, new_shape):
"""
If possible, reshape `arr` to have shape `new_shape`,
Expand All @@ -3181,16 +3156,6 @@ def _safe_reshape(arr, new_shape):
return arr


def _factor_indexer(shape, labels):
"""
given a tuple of shape and a list of Categorical labels, return the
expanded label indexer
"""
mult = np.array(shape)[::-1].cumprod()[::-1]
return ensure_platform_int(
np.sum(np.array(labels).T * np.append(mult, [1]), axis=1).T)


def _putmask_smart(v, m, n):
"""
Return a new ndarray, try to preserve dtype if possible.
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