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DEPR: Deprecate from_items
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-73
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8 files changed

+111
-73
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‎doc/source/whatsnew/v0.23.0.txt

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -329,7 +329,7 @@ Deprecations
329329
- :func:`read_excel` has deprecated the ``skip_footer`` parameter. Use ``skipfooter`` instead (:issue:`18836`)
330330
- The ``is_copy`` attribute is deprecated and will be removed in a future version (:issue:`18801`).
331331
- ``IntervalIndex.from_intervals`` is deprecated in favor of the :class:`IntervalIndex` constructor (:issue:`19263`)
332-
332+
- :func:``DataFrame.from_items`` is deprecated. Use ``DataFrame.from_dict(OrderedDict())`` instead (:issue:`17320`)
333333

334334
.. _whatsnew_0230.prior_deprecations:
335335

‎pandas/core/frame.py

Lines changed: 9 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -313,7 +313,7 @@ def _constructor(self):
313313

314314
_constructor_sliced = Series
315315
_deprecations = NDFrame._deprecations | frozenset(
316-
['sortlevel', 'get_value', 'set_value', 'from_csv'])
316+
['sortlevel', 'get_value', 'set_value', 'from_csv', 'from_items'])
317317

318318
@property
319319
def _constructor_expanddim(self):
@@ -1246,6 +1246,9 @@ def to_records(self, index=True, convert_datetime64=True):
12461246
@classmethod
12471247
def from_items(cls, items, columns=None, orient='columns'):
12481248
"""
1249+
DEPRECATED: from_items is deprecated and will be removed in a
1250+
future version. Use :meth:`DataFrame(dict())` instead.
1251+
12491252
Convert (key, value) pairs to DataFrame. The keys will be the axis
12501253
index (usually the columns, but depends on the specified
12511254
orientation). The values should be arrays or Series.
@@ -1266,6 +1269,11 @@ def from_items(cls, items, columns=None, orient='columns'):
12661269
-------
12671270
frame : DataFrame
12681271
"""
1272+
1273+
warnings.warn("from_items is deprecated. Please use "
1274+
"DataFrame(dict()) instead.",
1275+
FutureWarning, stacklevel=2)
1276+
12691277
keys, values = lzip(*items)
12701278

12711279
if orient == 'columns':

‎pandas/io/stata.py

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1571,7 +1571,7 @@ def read(self, nrows=None, convert_dates=None,
15711571
else:
15721572
data_formatted.append((col, data[col]))
15731573
if requires_type_conversion:
1574-
data = DataFrame.from_items(data_formatted)
1574+
data = DataFrame(dict(data_formatted), columns=dict(data_formatted).keys())
15751575
del data_formatted
15761576

15771577
self._do_convert_missing(data, convert_missing)
@@ -1609,7 +1609,7 @@ def read(self, nrows=None, convert_dates=None,
16091609
convert = True
16101610
retyped_data.append((col, data[col].astype(dtype)))
16111611
if convert:
1612-
data = DataFrame.from_items(retyped_data)
1612+
data = DataFrame(dict(retyped_data), columns=dict(retyped_data).keys())
16131613

16141614
if index_col is not None:
16151615
data = data.set_index(data.pop(index_col))
@@ -1722,7 +1722,7 @@ def _do_convert_categoricals(self, data, value_label_dict, lbllist,
17221722
cat_converted_data.append((col, cat_data))
17231723
else:
17241724
cat_converted_data.append((col, data[col]))
1725-
data = DataFrame.from_items(cat_converted_data)
1725+
data = DataFrame(dict(cat_converted_data), columns=dict(cat_converted_data).keys())
17261726
return data
17271727

17281728
def data_label(self):
@@ -1997,7 +1997,7 @@ def _prepare_categoricals(self, data):
19971997
data_formatted.append((col, values))
19981998
else:
19991999
data_formatted.append((col, data[col]))
2000-
return DataFrame.from_items(data_formatted)
2000+
return DataFrame(dict(data_formatted), columns=dict(data_formatted).keys())
20012001

20022002
def _replace_nans(self, data):
20032003
# return data

‎pandas/tests/frame/test_constructors.py

Lines changed: 52 additions & 21 deletions
Original file line numberDiff line numberDiff line change
@@ -871,7 +871,7 @@ def __len__(self, n):
871871
# GH 4297
872872
# support Array
873873
import array
874-
result = DataFrame.from_items([('A', array.array('i', range(10)))])
874+
result = DataFrame({'A': array.array('i', range(10))})
875875
expected = DataFrame({'A': list(range(10))})
876876
tm.assert_frame_equal(result, expected, check_dtype=False)
877877

@@ -1175,44 +1175,55 @@ def test_constructor_manager_resize(self):
11751175

11761176
def test_constructor_from_items(self):
11771177
items = [(c, self.frame[c]) for c in self.frame.columns]
1178-
recons = DataFrame.from_items(items)
1178+
with tm.assert_produces_warning(FutureWarning,
1179+
check_stacklevel=False):
1180+
recons = DataFrame.from_items(items)
11791181
tm.assert_frame_equal(recons, self.frame)
11801182

11811183
# pass some columns
1182-
recons = DataFrame.from_items(items, columns=['C', 'B', 'A'])
1184+
with tm.assert_produces_warning(FutureWarning,
1185+
check_stacklevel=False):
1186+
recons = DataFrame.from_items(items, columns=['C', 'B', 'A'])
11831187
tm.assert_frame_equal(recons, self.frame.loc[:, ['C', 'B', 'A']])
11841188

11851189
# orient='index'
11861190

11871191
row_items = [(idx, self.mixed_frame.xs(idx))
11881192
for idx in self.mixed_frame.index]
1189-
1190-
recons = DataFrame.from_items(row_items,
1191-
columns=self.mixed_frame.columns,
1192-
orient='index')
1193+
with tm.assert_produces_warning(FutureWarning,
1194+
check_stacklevel=False):
1195+
recons = DataFrame.from_items(row_items,
1196+
columns=self.mixed_frame.columns,
1197+
orient='index')
11931198
tm.assert_frame_equal(recons, self.mixed_frame)
11941199
assert recons['A'].dtype == np.float64
11951200

11961201
with tm.assert_raises_regex(TypeError,
11971202
"Must pass columns with "
11981203
"orient='index'"):
1199-
DataFrame.from_items(row_items, orient='index')
1204+
with tm.assert_produces_warning(FutureWarning,
1205+
check_stacklevel=False):
1206+
DataFrame.from_items(row_items, orient='index')
12001207

12011208
# orient='index', but thar be tuples
12021209
arr = construct_1d_object_array_from_listlike(
12031210
[('bar', 'baz')] * len(self.mixed_frame))
12041211
self.mixed_frame['foo'] = arr
12051212
row_items = [(idx, list(self.mixed_frame.xs(idx)))
12061213
for idx in self.mixed_frame.index]
1207-
recons = DataFrame.from_items(row_items,
1208-
columns=self.mixed_frame.columns,
1209-
orient='index')
1214+
with tm.assert_produces_warning(FutureWarning,
1215+
check_stacklevel=False):
1216+
recons = DataFrame.from_items(row_items,
1217+
columns=self.mixed_frame.columns,
1218+
orient='index')
12101219
tm.assert_frame_equal(recons, self.mixed_frame)
12111220
assert isinstance(recons['foo'][0], tuple)
12121221

1213-
rs = DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])],
1214-
orient='index',
1215-
columns=['one', 'two', 'three'])
1222+
with tm.assert_produces_warning(FutureWarning,
1223+
check_stacklevel=False):
1224+
rs = DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])],
1225+
orient='index',
1226+
columns=['one', 'two', 'three'])
12161227
xp = DataFrame([[1, 2, 3], [4, 5, 6]], index=['A', 'B'],
12171228
columns=['one', 'two', 'three'])
12181229
tm.assert_frame_equal(rs, xp)
@@ -1222,12 +1233,28 @@ def test_constructor_from_items_scalars(self):
12221233
with tm.assert_raises_regex(ValueError,
12231234
r'The value in each \(key, value\) '
12241235
'pair must be an array, Series, or dict'):
1225-
DataFrame.from_items([('A', 1), ('B', 4)])
1236+
with tm.assert_produces_warning(FutureWarning,
1237+
check_stacklevel=False):
1238+
DataFrame.from_items([('A', 1), ('B', 4)])
12261239

12271240
with tm.assert_raises_regex(ValueError,
12281241
r'The value in each \(key, value\) '
12291242
'pair must be an array, Series, or dict'):
1230-
DataFrame.from_items([('A', 1), ('B', 2)], columns=['col1'],
1243+
with tm.assert_produces_warning(FutureWarning,
1244+
check_stacklevel=False):
1245+
DataFrame.from_items([('A', 1), ('B', 2)], columns=['col1'],
1246+
orient='index')
1247+
1248+
def test_from_items_deprecation(self):
1249+
# GH 17320
1250+
with tm.assert_produces_warning(FutureWarning,
1251+
check_stacklevel=False):
1252+
DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])])
1253+
1254+
with tm.assert_produces_warning(FutureWarning,
1255+
check_stacklevel=False):
1256+
DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])],
1257+
columns=['col1', 'col2', 'col3'],
12311258
orient='index')
12321259

12331260
def test_constructor_mix_series_nonseries(self):
@@ -1256,13 +1283,17 @@ def test_constructor_column_duplicates(self):
12561283

12571284
tm.assert_frame_equal(df, edf)
12581285

1259-
idf = DataFrame.from_items(
1260-
[('a', [8]), ('a', [5])], columns=['a', 'a'])
1286+
with tm.assert_produces_warning(FutureWarning,
1287+
check_stacklevel=False):
1288+
idf = DataFrame.from_items([('a', [8]), ('a', [5])],
1289+
columns=['a', 'a'])
12611290
tm.assert_frame_equal(idf, edf)
12621291

1263-
pytest.raises(ValueError, DataFrame.from_items,
1264-
[('a', [8]), ('a', [5]), ('b', [6])],
1265-
columns=['b', 'a', 'a'])
1292+
with tm.assert_produces_warning(FutureWarning,
1293+
check_stacklevel=False):
1294+
pytest.raises(ValueError, DataFrame.from_items,
1295+
[('a', [8]), ('a', [5]), ('b', [6])],
1296+
columns=['b', 'a', 'a'])
12661297

12671298
def test_constructor_empty_with_string_dtype(self):
12681299
# GH 9428

‎pandas/tests/frame/test_nonunique_indexes.py

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -214,9 +214,10 @@ def check(result, expected=None):
214214
for index in [df.index, pd.Index(list('edcba'))]:
215215
this_df = df.copy()
216216
expected_ser = pd.Series(index.values, index=this_df.index)
217-
expected_df = DataFrame.from_items([('A', expected_ser),
218-
('B', this_df['B']),
219-
('A', expected_ser)])
217+
expected_df = DataFrame({'A': expected_ser,
218+
'B': this_df['B'],
219+
'A': expected_ser},
220+
columns=['A', 'B', 'A'])
220221
this_df['A'] = index
221222
check(this_df, expected_df)
222223

‎pandas/tests/io/parser/common.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -924,8 +924,8 @@ def test_float_parser(self):
924924

925925
def test_scientific_no_exponent(self):
926926
# see gh-12215
927-
df = DataFrame.from_items([('w', ['2e']), ('x', ['3E']),
928-
('y', ['42e']), ('z', ['632E'])])
927+
df = DataFrame({'w': ['2e'], 'x': ['3E'],
928+
'y': ['42e'], 'z': ['632E']})
929929
data = df.to_csv(index=False)
930930
for prec in self.float_precision_choices:
931931
df_roundtrip = self.read_csv(

‎pandas/tests/io/test_excel.py

Lines changed: 38 additions & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -315,17 +315,17 @@ def test_excel_table(self):
315315

316316
def test_reader_special_dtypes(self):
317317

318-
expected = DataFrame.from_items([
319-
("IntCol", [1, 2, -3, 4, 0]),
320-
("FloatCol", [1.25, 2.25, 1.83, 1.92, 0.0000000005]),
321-
("BoolCol", [True, False, True, True, False]),
322-
("StrCol", [1, 2, 3, 4, 5]),
318+
expected = DataFrame({
319+
"IntCol": [1, 2, -3, 4, 0],
320+
"FloatCol": [1.25, 2.25, 1.83, 1.92, 0.0000000005],
321+
"BoolCol": [True, False, True, True, False],
322+
"StrCol": [1, 2, 3, 4, 5],
323323
# GH5394 - this is why convert_float isn't vectorized
324-
("Str2Col", ["a", 3, "c", "d", "e"]),
325-
("DateCol", [datetime(2013, 10, 30), datetime(2013, 10, 31),
324+
"Str2Col": ["a", 3, "c", "d", "e"],
325+
"DateCol": [datetime(2013, 10, 30), datetime(2013, 10, 31),
326326
datetime(1905, 1, 1), datetime(2013, 12, 14),
327-
datetime(2015, 3, 14)])
328-
])
327+
datetime(2015, 3, 14)]
328+
}, columns=["IntCol", "FloatCol", "BoolCol", "StrCol", "Str2Col", "DateCol"])
329329

330330
basename = 'test_types'
331331

@@ -363,12 +363,12 @@ def test_reader_converters(self):
363363

364364
basename = 'test_converters'
365365

366-
expected = DataFrame.from_items([
367-
("IntCol", [1, 2, -3, -1000, 0]),
368-
("FloatCol", [12.5, np.nan, 18.3, 19.2, 0.000000005]),
369-
("BoolCol", ['Found', 'Found', 'Found', 'Not found', 'Found']),
370-
("StrCol", ['1', np.nan, '3', '4', '5']),
371-
])
366+
expected = DataFrame({
367+
"IntCol": [1, 2, -3, -1000, 0],
368+
"FloatCol": [12.5, np.nan, 18.3, 19.2, 0.000000005],
369+
"BoolCol": ['Found', 'Found', 'Found', 'Not found', 'Found'],
370+
"StrCol": ['1', np.nan, '3', '4', '5'],
371+
}, columns=['IntCol', 'FloatCol', 'BoolCol', 'StrCol'])
372372

373373
converters = {'IntCol': lambda x: int(x) if x != '' else -1000,
374374
'FloatCol': lambda x: 10 * x if x else np.nan,
@@ -718,32 +718,30 @@ def test_reader_seconds(self):
718718

719719
if LooseVersion(xlrd.__VERSION__) >= LooseVersion("0.9.3"):
720720
# Xlrd >= 0.9.3 can handle Excel milliseconds.
721-
expected = DataFrame.from_items([("Time",
722-
[time(1, 2, 3),
723-
time(2, 45, 56, 100000),
724-
time(4, 29, 49, 200000),
725-
time(6, 13, 42, 300000),
726-
time(7, 57, 35, 400000),
727-
time(9, 41, 28, 500000),
728-
time(11, 25, 21, 600000),
729-
time(13, 9, 14, 700000),
730-
time(14, 53, 7, 800000),
731-
time(16, 37, 0, 900000),
732-
time(18, 20, 54)])])
721+
expected = DataFrame({"Time": [time(1, 2, 3),
722+
time(2, 45, 56, 100000),
723+
time(4, 29, 49, 200000),
724+
time(6, 13, 42, 300000),
725+
time(7, 57, 35, 400000),
726+
time(9, 41, 28, 500000),
727+
time(11, 25, 21, 600000),
728+
time(13, 9, 14, 700000),
729+
time(14, 53, 7, 800000),
730+
time(16, 37, 0, 900000),
731+
time(18, 20, 54)]})
733732
else:
734733
# Xlrd < 0.9.3 rounds Excel milliseconds.
735-
expected = DataFrame.from_items([("Time",
736-
[time(1, 2, 3),
737-
time(2, 45, 56),
738-
time(4, 29, 49),
739-
time(6, 13, 42),
740-
time(7, 57, 35),
741-
time(9, 41, 29),
742-
time(11, 25, 22),
743-
time(13, 9, 15),
744-
time(14, 53, 8),
745-
time(16, 37, 1),
746-
time(18, 20, 54)])])
734+
expected = DataFrame({"Time": [time(1, 2, 3),
735+
time(2, 45, 56),
736+
time(4, 29, 49),
737+
time(6, 13, 42),
738+
time(7, 57, 35),
739+
time(9, 41, 29),
740+
time(11, 25, 22),
741+
time(13, 9, 15),
742+
time(14, 53, 8),
743+
time(16, 37, 1),
744+
time(18, 20, 54)]})
747745

748746
actual = self.get_exceldf('times_1900', 'Sheet1')
749747
tm.assert_frame_equal(actual, expected)
@@ -1988,7 +1986,7 @@ def test_datetimes(self):
19881986
datetime(2013, 1, 13, 18, 20, 52)]
19891987

19901988
with ensure_clean(self.ext) as path:
1991-
write_frame = DataFrame.from_items([('A', datetimes)])
1989+
write_frame = DataFrame({'A': datetimes})
19921990
write_frame.to_excel(path, 'Sheet1')
19931991
read_frame = read_excel(path, 'Sheet1', header=0)
19941992

‎pandas/tests/io/test_stata.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -945,7 +945,7 @@ def test_categorical_order(self, file):
945945
cols.append((col, pd.Categorical.from_codes(codes, labels)))
946946
else:
947947
cols.append((col, pd.Series(labels, dtype=np.float32)))
948-
expected = DataFrame.from_items(cols)
948+
expected = DataFrame(dict(cols), columns=dict(cols).keys())
949949

950950
# Read with and with out categoricals, ensure order is identical
951951
file = getattr(self, file)

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