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perf: simplify pandas-like with_columns #1366

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merged 2 commits into from
Nov 13, 2024
Merged

perf: simplify pandas-like with_columns #1366

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9c2817d
wip try using fastpath always
MarcoGorelli Nov 13, 2024
212be77
simplify
MarcoGorelli Nov 13, 2024
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59 changes: 20 additions & 39 deletions narwhals/_pandas_like/dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,6 @@
from typing import overload

from narwhals._expression_parsing import evaluate_into_exprs
from narwhals._pandas_like.expr import PandasLikeExpr
from narwhals._pandas_like.utils import broadcast_series
from narwhals._pandas_like.utils import convert_str_slice_to_int_slice
from narwhals._pandas_like.utils import create_compliant_series
Expand Down Expand Up @@ -411,46 +410,28 @@ def with_columns(
if not new_columns and len(self) == 0:
return self

# If the inputs are all Expressions
# (as opposed to Series), we can use a fast path (concat, instead of assign).
# We can't use the fastpath if any input is not an expression (e.g.
# if it's a Series) because then we might be changing its flags.
# See `test_memmap` for an example of where this is necessary.
fast_path = all(isinstance(x, PandasLikeExpr) for x in exprs) and all(
isinstance(x, PandasLikeExpr) for (_, x) in named_exprs.items()
)

if fast_path:
new_column_name_to_new_column_map = {s.name: s for s in new_columns}
to_concat = []
# Make sure to preserve column order
for name in self._native_frame.columns:
if name in new_column_name_to_new_column_map:
to_concat.append(
validate_dataframe_comparand(
index, new_column_name_to_new_column_map.pop(name)
)
new_column_name_to_new_column_map = {s.name: s for s in new_columns}
to_concat = []
# Make sure to preserve column order
for name in self._native_frame.columns:
if name in new_column_name_to_new_column_map:
to_concat.append(
validate_dataframe_comparand(
index, new_column_name_to_new_column_map.pop(name)
)
else:
to_concat.append(self._native_frame[name])
to_concat.extend(
validate_dataframe_comparand(index, new_column_name_to_new_column_map[s])
for s in new_column_name_to_new_column_map
)

df = horizontal_concat(
to_concat,
implementation=self._implementation,
backend_version=self._backend_version,
)
else:
# This is the logic in pandas' DataFrame.assign
if self._backend_version < (2,):
df = self._native_frame.copy(deep=True)
)
else:
df = self._native_frame.copy(deep=False)
for s in new_columns:
df[s.name] = validate_dataframe_comparand(index, s)
to_concat.append(self._native_frame[name])
to_concat.extend(
validate_dataframe_comparand(index, new_column_name_to_new_column_map[s])
for s in new_column_name_to_new_column_map
)

df = horizontal_concat(
to_concat,
implementation=self._implementation,
backend_version=self._backend_version,
)
return self._from_native_frame(df)

def rename(self, mapping: dict[str, str]) -> Self:
Expand Down
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