Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Support Series derived from a different dataframe as row_sel. #1155

Merged
merged 1 commit into from
Dec 30, 2019
Merged

Support Series derived from a different dataframe as row_sel. #1155

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 12 additions & 1 deletion databricks/koalas/indexing.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -142,6 +142,11 @@ def __getitem__(self, key):
raise SparkPandasIndexingError('Too many indexers')
key = key[0]

if isinstance(key, Series) and key._kdf is not self._kdf_or_kser._kdf:
kdf = self._kdf_or_kser.to_frame()
kdf['__temp_col__'] = key
return type(self)(kdf[self._kdf_or_kser.name])[kdf['__temp_col__']]

cond, limit = self._select_rows(key)
if cond is None and limit is None:
return self._kdf_or_kser
Expand All @@ -159,6 +164,12 @@ def __getitem__(self, key):
rows_sel = key
cols_sel = None

if isinstance(rows_sel, Series) and rows_sel._kdf is not self._kdf_or_kser:
kdf = self._kdf_or_kser.copy()
kdf['__temp_col__'] = rows_sel
return type(self)(kdf)[kdf['__temp_col__'],
cols_sel][list(self._kdf_or_kser.columns)]

cond, limit = self._select_rows(rows_sel)
column_index, column_scols, returns_series = self._select_cols(cols_sel)

Expand Down Expand Up @@ -719,7 +730,7 @@ def _select_rows(self, rows_sel):
return None, rows_sel.stop
else:
ILocIndexer._raiseNotImplemented(".iloc requires numeric slice or conditional "
"boolean Index, got {}".format(rows_sel))
"boolean Index, got {}".format(type(rows_sel)))

def _select_cols(self, cols_sel):
from databricks.koalas.series import Series
Expand Down
14 changes: 1 addition & 13 deletions databricks/koalas/series.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4278,19 +4278,7 @@ def __len__(self):

def __getitem__(self, key):
if isinstance(key, Series) and isinstance(key.spark_type, BooleanType):
should_try_ops_on_diff_frame = key._kdf is not self._kdf

if should_try_ops_on_diff_frame:
kdf = self.to_frame()
kdf["__temp_col__"] = key
sdf = kdf._sdf.filter(F.col("__temp_col__")).drop("__temp_col__")
return _col(ks.DataFrame(_InternalFrame(
sdf=sdf,
index_map=self._internal.index_map,
column_index=self._internal.column_index,
column_index_names=self._internal.column_index_names)))
else:
return _col(DataFrame(self._internal.copy(sdf=self._kdf._sdf.filter(key._scol))))
return self.loc[key]

if not isinstance(key, tuple):
key = (key,)
Expand Down
34 changes: 28 additions & 6 deletions databricks/koalas/tests/test_ops_on_diff_frames.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -298,16 +298,38 @@ def test_arithmetic_chain(self):
(pser1 + pser2 * pser3).sort_index(), almost=True)

def test_getitem_boolean_series(self):
pdf1 = pd.DataFrame({'A': [0, 1, 2, 3, 4], 'B': [100, 200, 300, 400, 500]})
pdf2 = pd.DataFrame({'A': [0, -1, -2, -3, -4], 'B': [-100, -200, -300, -400, -500]})
pdf1 = pd.DataFrame({'A': [0, 1, 2, 3, 4], 'B': [100, 200, 300, 400, 500]},
index=[20, 10, 30, 0, 50])
pdf2 = pd.DataFrame({'A': [0, -1, -2, -3, -4], 'B': [-100, -200, -300, -400, -500]},
index=[0, 30, 10, 20, 50])
kdf1 = ks.from_pandas(pdf1)
kdf2 = ks.from_pandas(pdf2)

self.assert_eq(pdf1.A[pdf2.A > 100],
kdf1.A[kdf2.A > 100].sort_index())
self.assert_eq(pdf1[pdf2.A > -3].sort_index(),
kdf1[kdf2.A > -3].sort_index())

self.assert_eq(pdf1.A[pdf2.A > -3].sort_index(),
kdf1.A[kdf2.A > -3].sort_index())

self.assert_eq((pdf1.A + 1)[pdf2.A > -3].sort_index(),
(kdf1.A + 1)[kdf2.A > -3].sort_index())

def test_loc_getitem_boolean_series(self):
pdf1 = pd.DataFrame({'A': [0, 1, 2, 3, 4], 'B': [100, 200, 300, 400, 500]},
index=[20, 10, 30, 0, 50])
pdf2 = pd.DataFrame({'A': [0, -1, -2, -3, -4], 'B': [-100, -200, -300, -400, -500]},
index=[20, 10, 30, 0, 50])
kdf1 = ks.from_pandas(pdf1)
kdf2 = ks.from_pandas(pdf2)

self.assert_eq(pdf1.loc[pdf2.A > -3].sort_index(),
kdf1.loc[kdf2.A > -3].sort_index())

self.assert_eq(pdf1.A.loc[pdf2.A > -3].sort_index(),
kdf1.A.loc[kdf2.A > -3].sort_index())

self.assert_eq((pdf1.A + 1)[pdf2.A > 100],
(kdf1.A + 1)[kdf2.A > 100].sort_index())
self.assert_eq((pdf1.A + 1).loc[pdf2.A > -3].sort_index(),
(kdf1.A + 1).loc[kdf2.A > -3].sort_index())

def test_bitwise(self):
pser1 = pd.Series([True, False, True, False, np.nan, np.nan, True, False, np.nan])
Expand Down