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fix: pandas.cut returns labels index for numeric breaks when labels=False #1548

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chelsea-lin merged 2 commits into from
Mar 28, 2025
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fix: pandas.cut returns labels index for numeric breaks when labels=False #1548

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d766b27
refactor tests to detect the bug and other edge cases bugs
chelsea-lin Mar 26, 2025
1e85760
fix: pandas.cut returns labels for numeric breaks when labels=False
chelsea-lin Mar 26, 2025
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82 changes: 37 additions & 45 deletions bigframes/core/compile/aggregate_compiler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -360,69 +360,61 @@ def _(
if isinstance(op.bins, int):
col_min = _apply_window_if_present(x.min(), window)
col_max = _apply_window_if_present(x.max(), window)
adj = (col_max - col_min) * 0.001
bin_width = (col_max - col_min) / op.bins

if op.labels is False:
for this_bin in range(op.bins - 1):
if op.right:
case_expr = x <= (col_min + (this_bin + 1) * bin_width)
else:
case_expr = x < (col_min + (this_bin + 1) * bin_width)
out = out.when(
case_expr,
compile_ibis_types.literal_to_ibis_scalar(
this_bin, force_dtype=pd.Int64Dtype()
),
for this_bin in range(op.bins):
if op.labels is False:
value = compile_ibis_types.literal_to_ibis_scalar(
this_bin, force_dtype=pd.Int64Dtype()
)
out = out.when(x.notnull(), op.bins - 1)
else:
interval_struct = None
adj = (col_max - col_min) * 0.001
for this_bin in range(op.bins):
left_edge_adj = adj if this_bin == 0 and op.right else 0
right_edge_adj = adj if this_bin == op.bins - 1 and not op.right else 0
else:
left_adj = adj if this_bin == 0 and op.right else 0
right_adj = adj if this_bin == op.bins - 1 and not op.right else 0

left_edge = col_min + this_bin * bin_width - left_edge_adj
right_edge = col_min + (this_bin + 1) * bin_width + right_edge_adj
left = col_min + this_bin * bin_width - left_adj
right = col_min + (this_bin + 1) * bin_width + right_adj

if op.right:
interval_struct = ibis_types.struct(
{
"left_exclusive": left_edge,
"right_inclusive": right_edge,
}
value = ibis_types.struct(
{"left_exclusive": left, "right_inclusive": right}
)
else:
interval_struct = ibis_types.struct(
{
"left_inclusive": left_edge,
"right_exclusive": right_edge,
}
value = ibis_types.struct(
{"left_inclusive": left, "right_exclusive": right}
)

if this_bin < op.bins - 1:
if op.right:
case_expr = x <= (col_min + (this_bin + 1) * bin_width)
else:
case_expr = x < (col_min + (this_bin + 1) * bin_width)
out = out.when(case_expr, interval_struct)
if this_bin == op.bins - 1:
case_expr = x.notnull()
else:
if op.right:
case_expr = x <= (col_min + (this_bin + 1) * bin_width)
else:
out = out.when(x.notnull(), interval_struct)
case_expr = x < (col_min + (this_bin + 1) * bin_width)
out = out.when(case_expr, value)
else: # Interpret as intervals
for interval in op.bins:
for this_bin, interval in enumerate(op.bins):
left = compile_ibis_types.literal_to_ibis_scalar(interval[0])
right = compile_ibis_types.literal_to_ibis_scalar(interval[1])
if op.right:
condition = (x > left) & (x <= right)
interval_struct = ibis_types.struct(
{"left_exclusive": left, "right_inclusive": right}
)
else:
condition = (x >= left) & (x < right)
interval_struct = ibis_types.struct(
{"left_inclusive": left, "right_exclusive": right}

if op.labels is False:
value = compile_ibis_types.literal_to_ibis_scalar(
this_bin, force_dtype=pd.Int64Dtype()
)
out = out.when(condition, interval_struct)
else:
if op.right:
value = ibis_types.struct(
{"left_exclusive": left, "right_inclusive": right}
)
else:
value = ibis_types.struct(
{"left_inclusive": left, "right_exclusive": right}
)

out = out.when(condition, value)
return out.end()


Expand Down
15 changes: 13 additions & 2 deletions bigframes/core/reshape/tile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,8 @@ def cut(
"The 'labels' parameter must be either False or None. "
"Please provide a valid value for 'labels'."
)
if x.size == 0:
raise ValueError("Cannot cut empty array.")

if isinstance(bins, int):
if bins <= 0:
Expand All @@ -58,14 +60,19 @@ def cut(
bins = tuple((bin.left.item(), bin.right.item()) for bin in bins)
# To maintain consistency with pandas' behavior
right = True
labels = None
elif len(list(bins)) == 0:
as_index = pd.IntervalIndex.from_tuples(list(bins))
bins = tuple()
# To maintain consistency with pandas' behavior
right = True
labels = None
elif isinstance(list(bins)[0], tuple):
as_index = pd.IntervalIndex.from_tuples(list(bins))
bins = tuple(bins)
# To maintain consistency with pandas' behavior
right = True
labels = None
elif pd.api.types.is_number(list(bins)[0]):
bins_list = list(bins)
as_index = pd.IntervalIndex.from_breaks(bins_list)
Expand All @@ -83,9 +90,13 @@ def cut(
if as_index.is_overlapping:
raise ValueError("Overlapping IntervalIndex is not accepted.")
elif len(as_index) == 0:
op = agg_ops.CutOp(bins, right=right, labels=labels)
dtype = agg_ops.CutOp(bins, right=right, labels=labels).output_type()
return bigframes.series.Series(
[pd.NA] * len(x), dtype=op.output_type(), name=x.name
[pd.NA] * len(x),
dtype=dtype,
name=x.name,
index=x.index,
session=x._session,
)
else:
op = agg_ops.CutOp(bins, right=right, labels=labels)
Expand Down
2 changes: 1 addition & 1 deletion bigframes/operations/aggregations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -347,7 +347,7 @@ def skips_nulls(self):
return False

def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
if isinstance(self.bins, int) and (self.labels is False):
if self.labels is False:
return dtypes.INT_DTYPE
else:
# Assumption: buckets use same numeric type
Expand Down
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