@@ -604,7 +604,7 @@ def str_extract(arr, pat, flags=0, expand=None):
604 604
return _str_extract_frame(arr._orig, pat, flags=flags)
605 605
else:
606 606
result, name = _str_extract_noexpand(arr._data, pat, flags=flags)
607 -
return arr._wrap_result(result, name=name)
607 +
return arr._wrap_result(result, name=name, expand=expand)
608 608 609 609 610 610
def str_extractall(arr, pat, flags=0):
@@ -1292,7 +1292,10 @@ def __iter__(self):
1292 1292
i += 1
1293 1293
g = self.get(i)
1294 1294 1295 -
def _wrap_result(self, result, use_codes=True, name=None):
1295 +
def _wrap_result(self, result, use_codes=True,
1296 +
name=None, expand=None):
1297 + 1298 +
from pandas.core.index import Index, MultiIndex
1296 1299 1297 1300
# for category, we do the stuff on the categories, so blow it up
1298 1301
# to the full series again
@@ -1302,48 +1305,42 @@ def _wrap_result(self, result, use_codes=True, name=None):
1302 1305
if use_codes and self._is_categorical:
1303 1306
result = take_1d(result, self._orig.cat.codes)
1304 1307 1305 -
# leave as it is to keep extract and get_dummies results
1306 -
# can be merged to _wrap_result_expand in v0.17
1307 -
from pandas.core.series import Series
1308 -
from pandas.core.frame import DataFrame
1309 -
from pandas.core.index import Index
1310 - 1311 -
if not hasattr(result, 'ndim'):
1308 +
if not hasattr(result, 'ndim') or not hasattr(result, 'dtype'):
1312 1309
return result
1310 +
assert result.ndim < 3
1313 1311 1314 -
if result.ndim == 1:
1315 -
# Wait until we are sure result is a Series or Index before
1316 -
# checking attributes (GH 12180)
1317 -
name = name or getattr(result, 'name', None) or self._orig.name
1318 -
if isinstance(self._orig, Index):
1319 -
# if result is a boolean np.array, return the np.array
1320 -
# instead of wrapping it into a boolean Index (GH 8875)
1321 -
if is_bool_dtype(result):
1322 -
return result
1323 -
return Index(result, name=name)
1324 -
return Series(result, index=self._orig.index, name=name)
1325 -
else:
1326 -
assert result.ndim < 3
1327 -
return DataFrame(result, index=self._orig.index)
1312 +
if expand is None:
1313 +
# infer from ndim if expand is not specified
1314 +
expand = False if result.ndim == 1 else True
1315 + 1316 +
elif expand is True and not isinstance(self._orig, Index):
1317 +
# required when expand=True is explicitly specified
1318 +
# not needed when infered
1319 + 1320 +
def cons_row(x):
1321 +
if is_list_like(x):
1322 +
return x
1323 +
else:
1324 +
return [x]
1325 + 1326 +
result = [cons_row(x) for x in result]
1328 1327 1329 -
def _wrap_result_expand(self, result, expand=False):
1330 1328
if not isinstance(expand, bool):
1331 1329
raise ValueError("expand must be True or False")
1332 1330 1333 -
# for category, we do the stuff on the categories, so blow it up
1334 -
# to the full series again
1335 -
if self._is_categorical:
1336 -
result = take_1d(result, self._orig.cat.codes)
1337 - 1338 -
from pandas.core.index import Index, MultiIndex
1339 -
if not hasattr(result, 'ndim'):
1340 -
return result
1331 +
if name is None:
1332 +
name = getattr(result, 'name', None)
1333 +
if name is None:
1334 +
# do not use logical or, _orig may be a DataFrame
1335 +
# which has "name" column
1336 +
name = self._orig.name
1341 1337 1338 +
# Wait until we are sure result is a Series or Index before
1339 +
# checking attributes (GH 12180)
1342 1340
if isinstance(self._orig, Index):
1343 -
name = getattr(result, 'name', None)
1344 1341
# if result is a boolean np.array, return the np.array
1345 1342
# instead of wrapping it into a boolean Index (GH 8875)
1346 -
if hasattr(result, 'dtype') and is_bool_dtype(result):
1343 +
if is_bool_dtype(result):
1347 1344
return result
1348 1345 1349 1346
if expand:
@@ -1354,18 +1351,10 @@ def _wrap_result_expand(self, result, expand=False):
1354 1351
else:
1355 1352
index = self._orig.index
1356 1353
if expand:
1357 - 1358 -
def cons_row(x):
1359 -
if is_list_like(x):
1360 -
return x
1361 -
else:
1362 -
return [x]
1363 - 1364 1354
cons = self._orig._constructor_expanddim
1365 -
data = [cons_row(x) for x in result]
1366 -
return cons(data, index=index)
1355 +
return cons(result, index=index)
1367 1356
else:
1368 -
name = getattr(result, 'name', None)
1357 +
# Must a Series
1369 1358
cons = self._orig._constructor
1370 1359
return cons(result, name=name, index=index)
1371 1360
@@ -1380,12 +1369,12 @@ def cat(self, others=None, sep=None, na_rep=None):
1380 1369
@copy(str_split)
1381 1370
def split(self, pat=None, n=-1, expand=False):
1382 1371
result = str_split(self._data, pat, n=n)
1383 -
return self._wrap_result_expand(result, expand=expand)
1372 +
return self._wrap_result(result, expand=expand)
1384 1373 1385 1374
@copy(str_rsplit)
1386 1375
def rsplit(self, pat=None, n=-1, expand=False):
1387 1376
result = str_rsplit(self._data, pat, n=n)
1388 -
return self._wrap_result_expand(result, expand=expand)
1377 +
return self._wrap_result(result, expand=expand)
1389 1378 1390 1379
_shared_docs['str_partition'] = ("""
1391 1380
Split the string at the %(side)s occurrence of `sep`, and return 3 elements
@@ -1440,7 +1429,7 @@ def rsplit(self, pat=None, n=-1, expand=False):
1440 1429
def partition(self, pat=' ', expand=True):
1441 1430
f = lambda x: x.partition(pat)
1442 1431
result = _na_map(f, self._data)
1443 -
return self._wrap_result_expand(result, expand=expand)
1432 +
return self._wrap_result(result, expand=expand)
1444 1433 1445 1434
@Appender(_shared_docs['str_partition'] % {
1446 1435
'side': 'last',
@@ -1451,7 +1440,7 @@ def partition(self, pat=' ', expand=True):
1451 1440
def rpartition(self, pat=' ', expand=True):
1452 1441
f = lambda x: x.rpartition(pat)
1453 1442
result = _na_map(f, self._data)
1454 -
return self._wrap_result_expand(result, expand=expand)
1443 +
return self._wrap_result(result, expand=expand)
1455 1444 1456 1445
@copy(str_get)
1457 1446
def get(self, i):
@@ -1597,7 +1586,8 @@ def get_dummies(self, sep='|'):
1597 1586
# methods available for making the dummies...
1598 1587
data = self._orig.astype(str) if self._is_categorical else self._data
1599 1588
result = str_get_dummies(data, sep)
1600 -
return self._wrap_result(result, use_codes=(not self._is_categorical))
1589 +
return self._wrap_result(result, use_codes=(not self._is_categorical),
1590 +
expand=True)
1601 1591 1602 1592
@copy(str_translate)
1603 1593
def translate(self, table, deletechars=None):
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