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REF: insert self.on column _after_ concat #35746

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merged 2 commits into from
Aug 20, 2020
Merged

REF: insert self.on column _after_ concat #35746

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REF: insert self.on column _after_ concat
jbrockmendel Aug 15, 2020
8c90cc4
Merge branch 'master' of https://github.com/pandas-dev/pandas into re…
jbrockmendel Aug 17, 2020
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50 changes: 21 additions & 29 deletions pandas/core/window/rolling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@
from pandas.core.base import DataError, PandasObject, SelectionMixin, ShallowMixin
import pandas.core.common as com
from pandas.core.construction import extract_array
from pandas.core.indexes.api import Index, MultiIndex, ensure_index
from pandas.core.indexes.api import Index, MultiIndex
from pandas.core.util.numba_ import NUMBA_FUNC_CACHE, maybe_use_numba
from pandas.core.window.common import (
WindowGroupByMixin,
Expand Down Expand Up @@ -402,36 +402,27 @@ def _wrap_results(self, results, blocks, obj, exclude=None) -> FrameOrSeries:
return result
final.append(result)

# if we have an 'on' column
# we want to put it back into the results
# in the same location
columns = self._selected_obj.columns
if self.on is not None and not self._on.equals(obj.index):

name = self._on.name
final.append(Series(self._on, index=obj.index, name=name))

if self._selection is not None:

selection = ensure_index(self._selection)

# need to reorder to include original location of
# the on column (if its not already there)
if name not in selection:
columns = self.obj.columns
indexer = columns.get_indexer(selection.tolist() + [name])
columns = columns.take(sorted(indexer))

# exclude nuisance columns so that they are not reindexed
if exclude is not None and exclude:
columns = [c for c in columns if c not in exclude]
exclude = exclude or []
columns = [c for c in self._selected_obj.columns if c not in exclude]
if not columns and not len(final) and exclude:
raise DataError("No numeric types to aggregate")
elif not len(final):
return obj.astype("float64")

if not columns:
raise DataError("No numeric types to aggregate")
df = concat(final, axis=1).reindex(columns=columns, copy=False)

if not len(final):
return obj.astype("float64")
return concat(final, axis=1).reindex(columns=columns, copy=False)
# if we have an 'on' column we want to put it back into
# the results in the same location
if self.on is not None and not self._on.equals(obj.index):
name = self._on.name
extra_col = Series(self._on, index=obj.index, name=name)
if name not in df.columns and name not in df.index.names:
new_loc = len(df.columns)
df.insert(new_loc, name, extra_col)
elif name in df.columns:
# TODO: sure we want to overwrite results?
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@mroeschke can you comment on why we do this?

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I haven't really touched _wrap_results much so can't really speak to why we do this. What's an example where this is overwriting results?

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i dont have an example on hand, but can find one bc i know this line is covered by tests. ATM im inclined to not-worry about it

df[name] = extra_col
return df

def _center_window(self, result, window) -> np.ndarray:
"""
Expand Down Expand Up @@ -2277,6 +2268,7 @@ def _get_window_indexer(self, window: int) -> GroupbyRollingIndexer:
if isinstance(self.window, BaseIndexer):
rolling_indexer = type(self.window)
indexer_kwargs = self.window.__dict__
assert isinstance(indexer_kwargs, dict)
# We'll be using the index of each group later
indexer_kwargs.pop("index_array", None)
elif self.is_freq_type:
Expand Down