allow using Iterable in Series and DataFrame constructor (pandas-dev#21987)

Author: holymonson

doc/source/whatsnew/v0.24.0.txt

@@ -179,7 +179,7 @@ Other Enhancements
 - :class:`IntervalIndex` has gained the :meth:`~IntervalIndex.set_closed` method to change the existing ``closed`` value (:issue:`21670`)
 - :func:`~DataFrame.to_csv` and :func:`~DataFrame.to_json` now support ``compression='infer'`` to infer compression based on filename (:issue:`15008`)
 - :func:`to_timedelta` now supports iso-formated timedelta strings (:issue:`21877`)
--
+- :class:`Series` and :class:`DataFrame` now support :class:`Iterable` in constructor (:issue:`2193`)
 
 .. _whatsnew_0240.api_breaking:
 

pandas/core/frame.py

@@ -16,7 +16,6 @@
 import collections
 import itertools
 import sys
-import types
 import warnings
 from textwrap import dedent
 
@@ -75,7 +74,8 @@
 from pandas.core.arrays import Categorical, ExtensionArray
 import pandas.core.algorithms as algorithms
 from pandas.compat import (range, map, zip, lrange, lmap, lzip, StringIO, u,
-                           OrderedDict, raise_with_traceback)
+                           OrderedDict, raise_with_traceback,
+                           string_and_binary_types)
 from pandas import compat
 from pandas.compat import PY36
 from pandas.compat.numpy import function as nv
@@ -267,7 +267,7 @@ class DataFrame(NDFrame):
 
     Parameters
     ----------
-    data : numpy ndarray (structured or homogeneous), dict, or DataFrame
+    data : ndarray (structured or homogeneous), Iterable, dict, or DataFrame
         Dict can contain Series, arrays, constants, or list-like objects
 
         .. versionchanged :: 0.23.0
@@ -391,8 +391,11 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,
             else:
                 mgr = self._init_ndarray(data, index, columns, dtype=dtype,
                                          copy=copy)
-        elif isinstance(data, (list, types.GeneratorType)):
-            if isinstance(data, types.GeneratorType):
+
+        # For data is list-like, or Iterable (will consume into list)
+        elif (isinstance(data, collections.Iterable)
+              and not isinstance(data, string_and_binary_types)):
+            if not isinstance(data, collections.Sequence):
                 data = list(data)
             if len(data) > 0:
                 if is_list_like(data[0]) and getattr(data[0], 'ndim', 1) == 1:
@@ -417,8 +420,6 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,
                                              copy=copy)
             else:
                 mgr = self._init_dict({}, index, columns, dtype=dtype)
-        elif isinstance(data, collections.Iterator):
-            raise TypeError("data argument can't be an iterator")
         else:
             try:
                 arr = np.array(data, dtype=dtype, copy=copy)

pandas/core/series.py

@@ -6,7 +6,7 @@
 # pylint: disable=E1101,E1103
 # pylint: disable=W0703,W0622,W0613,W0201
 
-import types
+import collections
 import warnings
 from textwrap import dedent
 
@@ -144,7 +144,7 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
 
     Parameters
     ----------
-    data : array-like, dict, or scalar value
+    data : array-like, Iterable, dict, or scalar value
         Contains data stored in Series
 
         .. versionchanged :: 0.23.0
@@ -238,12 +238,13 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
 
             elif is_extension_array_dtype(data):
                 pass
-            elif (isinstance(data, types.GeneratorType) or
-                  (compat.PY3 and isinstance(data, map))):
-                data = list(data)
             elif isinstance(data, (set, frozenset)):
                 raise TypeError("{0!r} type is unordered"
                                 "".format(data.__class__.__name__))
+            # If data is Iterable but not list-like, consume into list.
+            elif (isinstance(data, collections.Iterable)
+                  and not isinstance(data, collections.Sized)):
+                data = list(data)
             else:
 
                 # handle sparse passed here (and force conversion)

pandas/tests/frame/test_constructors.py

@@ -865,12 +865,6 @@ def test_constructor_more(self):
         dm = DataFrame(index=np.arange(10))
         assert dm.values.shape == (10, 0)
 
-        # corner, silly
-        # TODO: Fix this Exception to be better...
-        with tm.assert_raises_regex(ValueError, 'constructor not '
-                                    'properly called'):
-            DataFrame((1, 2, 3))
-
         # can't cast
         mat = np.array(['foo', 'bar'], dtype=object).reshape(2, 1)
         with tm.assert_raises_regex(ValueError, 'cast'):
@@ -953,6 +947,17 @@ def __len__(self, n):
                             array.array('i', range(10))])
         tm.assert_frame_equal(result, expected, check_dtype=False)
 
+    def test_constructor_iterable(self):
+        # GH 21987
+        class Iter():
+            def __iter__(self):
+                for i in range(10):
+                    yield [1, 2, 3]
+
+        expected = DataFrame([[1, 2, 3]] * 10)
+        result = DataFrame(Iter())
+        tm.assert_frame_equal(result, expected)
+
     def test_constructor_iterator(self):
 
         expected = DataFrame([list(range(10)), list(range(10))])
@@ -1374,10 +1379,6 @@ def test_constructor_miscast_na_int_dtype(self):
         expected = DataFrame([[np.nan, 1], [1, 0]])
         tm.assert_frame_equal(df, expected)
 
-    def test_constructor_iterator_failure(self):
-        with tm.assert_raises_regex(TypeError, 'iterator'):
-            DataFrame(iter([1, 2, 3]))
-
     def test_constructor_column_duplicates(self):
         # it works! #2079
         df = DataFrame([[8, 5]], columns=['a', 'a'])

pandas/tests/series/test_constructors.py

@@ -156,12 +156,29 @@ def test_constructor_series(self):
 
         assert_series_equal(s2, s1.sort_index())
 
-    def test_constructor_iterator(self):
+    def test_constructor_iterable(self):
+        # GH 21987
+        class Iter():
+            def __iter__(self):
+                for i in range(10):
+                    yield i
 
+        expected = Series(list(range(10)), dtype='int64')
+        result = Series(Iter(), dtype='int64')
+        assert_series_equal(result, expected)
+
+    def test_constructor_sequence(self):
+        # GH 21987
         expected = Series(list(range(10)), dtype='int64')
         result = Series(range(10), dtype='int64')
         assert_series_equal(result, expected)
 
+    def test_constructor_single_str(self):
+        # GH 21987
+        expected = Series(['abc'])
+        result = Series('abc')
+        assert_series_equal(result, expected)
+
     def test_constructor_list_like(self):
 
         # make sure that we are coercing different