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WillAydjavadnoorb
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Removed dead groupby code (pandas-dev#20457)
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pandas/core/groupby.py

Lines changed: 0 additions & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -944,23 +944,6 @@ def _cumcount_array(self, ascending=True):
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rev[sorter] = np.arange(count, dtype=np.intp)
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return out[rev].astype(np.int64, copy=False)
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947-
def _index_with_as_index(self, b):
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"""
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Take boolean mask of index to be returned from apply, if as_index=True
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"""
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# TODO perf, it feels like this should already be somewhere...
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from itertools import chain
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original = self._selected_obj.index
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gp = self.grouper
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levels = chain((gp.levels[i][gp.labels[i][b]]
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for i in range(len(gp.groupings))),
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(original._get_level_values(i)[b]
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for i in range(original.nlevels)))
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new = MultiIndex.from_arrays(list(levels))
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new.names = gp.names + original.names
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return new
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def _try_cast(self, result, obj, numeric_only=False):
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"""
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try to cast the result to our obj original type,
@@ -2295,18 +2278,6 @@ def size(self):
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index=self.result_index,
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dtype='int64')
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@cache_readonly
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def _max_groupsize(self):
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"""
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Compute size of largest group
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"""
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# For many items in each group this is much faster than
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# self.size().max(), in worst case marginally slower
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if self.indices:
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return max(len(v) for v in self.indices.values())
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else:
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return 0
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@cache_readonly
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def groups(self):
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""" dict {group name -> group labels} """
@@ -2941,9 +2912,6 @@ def __init__(self, index, grouper=None, obj=None, name=None, level=None,
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if isinstance(grouper, MultiIndex):
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self.grouper = grouper.values
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2944-
# pre-computed
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self._should_compress = True
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# we have a single grouper which may be a myriad of things,
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# some of which are dependent on the passing in level
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@@ -4964,10 +4932,6 @@ def _wrap_aggregated_output(self, output, names=None):
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raise com.AbstractMethodError(self)
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class NDArrayGroupBy(GroupBy):
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pass
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# ----------------------------------------------------------------------
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# Splitting / application
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@@ -5020,10 +4984,6 @@ def apply(self, f):
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raise com.AbstractMethodError(self)
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5023-
class ArraySplitter(DataSplitter):
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pass
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class SeriesSplitter(DataSplitter):
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50294989
def _chop(self, sdata, slice_obj):

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