From 550885735e13c0c5595177a84ce3ae39f4b891aa Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Tue, 9 Oct 2018 23:21:06 +0200
Subject: [PATCH 01/17] Add strict-kwarg to is_list_like

---
 doc/source/whatsnew/v0.24.0.txt         |  1 +
 pandas/core/algorithms.py               |  6 ++--
 pandas/core/apply.py                    |  2 +-
 pandas/core/arrays/base.py              |  3 +-
 pandas/core/arrays/categorical.py       | 10 +++----
 pandas/core/arrays/datetimelike.py      |  2 +-
 pandas/core/arrays/integer.py           |  4 +--
 pandas/core/arrays/timedeltas.py        |  2 +-
 pandas/core/base.py                     |  3 +-
 pandas/core/computation/ops.py          |  4 +--
 pandas/core/computation/pytables.py     |  5 ++--
 pandas/core/dtypes/cast.py              |  6 ++--
 pandas/core/dtypes/common.py            |  4 +--
 pandas/core/dtypes/inference.py         | 32 ++++++++++++++-------
 pandas/core/dtypes/missing.py           |  2 +-
 pandas/core/frame.py                    | 19 +++++++------
 pandas/core/generic.py                  | 38 ++++++++++++++-----------
 pandas/core/groupby/base.py             |  3 +-
 pandas/core/groupby/grouper.py          |  4 +--
 pandas/core/indexes/accessors.py        |  4 +--
 pandas/core/indexes/base.py             | 21 +++++++-------
 pandas/core/indexes/category.py         |  2 +-
 pandas/core/indexes/datetimelike.py     |  2 +-
 pandas/core/indexes/datetimes.py        |  2 +-
 pandas/core/indexes/interval.py         |  4 +--
 pandas/core/indexes/multi.py            | 36 ++++++++++++-----------
 pandas/core/indexes/timedeltas.py       |  5 ++--
 pandas/core/indexing.py                 | 16 +++++------
 pandas/core/internals/blocks.py         | 23 ++++++++-------
 pandas/core/ops.py                      |  5 ++--
 pandas/core/panel.py                    |  4 +--
 pandas/core/reshape/melt.py             |  8 +++---
 pandas/core/reshape/merge.py            |  4 +--
 pandas/core/reshape/pivot.py            |  5 ++--
 pandas/core/reshape/reshape.py          |  2 +-
 pandas/core/reshape/util.py             |  4 +--
 pandas/core/series.py                   | 23 ++++++++-------
 pandas/core/sorting.py                  |  4 +--
 pandas/core/sparse/array.py             |  2 +-
 pandas/core/strings.py                  | 11 +++----
 pandas/core/tools/datetimes.py          |  6 ++--
 pandas/core/tools/timedeltas.py         |  2 +-
 pandas/core/util/hashing.py             |  2 +-
 pandas/core/window.py                   |  3 +-
 pandas/io/excel.py                      | 13 +++++----
 pandas/io/formats/format.py             |  4 +--
 pandas/io/formats/style.py              |  2 +-
 pandas/io/html.py                       |  3 +-
 pandas/io/parsers.py                    |  6 ++--
 pandas/io/pytables.py                   |  2 +-
 pandas/io/sql.py                        |  4 +--
 pandas/tests/computation/test_eval.py   |  2 +-
 pandas/tests/dtypes/test_inference.py   | 17 +++++++----
 pandas/tests/extension/decimal/array.py |  2 +-
 pandas/tests/plotting/common.py         |  6 ++--
 pandas/tests/plotting/test_frame.py     |  2 +-
 56 files changed, 229 insertions(+), 184 deletions(-)

diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
index a4209ba90aaee..6598a381a950d 100644
--- a/doc/source/whatsnew/v0.24.0.txt
+++ b/doc/source/whatsnew/v0.24.0.txt
@@ -629,6 +629,7 @@ Other API Changes
 - :class:`Index` subtraction will attempt to operate element-wise instead of raising ``TypeError`` (:issue:`19369`)
 - :class:`pandas.io.formats.style.Styler` supports a ``number-format`` property when using :meth:`~pandas.io.formats.style.Styler.to_excel` (:issue:`22015`)
 - :meth:`DataFrame.corr` and :meth:`Series.corr` now raise a ``ValueError`` along with a helpful error message instead of a ``KeyError`` when supplied with an invalid method (:issue:`22298`)
+- :meth:`dtypes.common.is_list_like` has gained a ``strict``-kwarg, which is ``False`` by default. If set to ``True``, sets are not considered list-like. (:issue:`22397`)
 - :meth:`shift` will now always return a copy, instead of the previous behaviour of returning self when shifting by 0 (:issue:`22397`)
 
 .. _whatsnew_0240.deprecations:
diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index e91cc8ec1e996..f5e8ebe210863 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -396,11 +396,11 @@ def isin(comps, values):
     boolean array same length as comps
     """
 
-    if not is_list_like(comps):
+    if not is_list_like(comps, strict=False):
         raise TypeError("only list-like objects are allowed to be passed"
                         " to isin(), you passed a [{comps_type}]"
                         .format(comps_type=type(comps).__name__))
-    if not is_list_like(values):
+    if not is_list_like(values, strict=False):
         raise TypeError("only list-like objects are allowed to be passed"
                         " to isin(), you passed a [{values_type}]"
                         .format(values_type=type(values).__name__))
@@ -1178,7 +1178,7 @@ class SelectNFrame(SelectN):
 
     def __init__(self, obj, n, keep, columns):
         super(SelectNFrame, self).__init__(obj, n, keep)
-        if not is_list_like(columns):
+        if not is_list_like(columns, strict=False):
             columns = [columns]
         columns = list(columns)
         self.columns = columns
diff --git a/pandas/core/apply.py b/pandas/core/apply.py
index 40cd952a62138..2b3fe0ef891f5 100644
--- a/pandas/core/apply.py
+++ b/pandas/core/apply.py
@@ -110,7 +110,7 @@ def get_result(self):
         """ compute the results """
 
         # dispatch to agg
-        if is_list_like(self.f) or is_dict_like(self.f):
+        if is_list_like(self.f, strict=False) or is_dict_like(self.f):
             return self.obj.aggregate(self.f, axis=self.axis,
                                       *self.args, **self.kwds)
 
diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index efe587c6aaaad..53f72624e8d87 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -769,7 +769,8 @@ def _create_method(cls, op, coerce_to_dtype=True):
 
         def _binop(self, other):
             def convert_values(param):
-                if isinstance(param, ExtensionArray) or is_list_like(param):
+                if (isinstance(param, ExtensionArray)
+                        or is_list_like(param, strict=False)):
                     ovalues = param
                 else:  # Assume its an object
                     ovalues = [param] * len(self)
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 216bccf7d6309..3d6034ba1c541 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -1017,7 +1017,7 @@ def add_categories(self, new_categories, inplace=False):
         set_categories
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        if not is_list_like(new_categories):
+        if not is_list_like(new_categories, strict=False):
             new_categories = [new_categories]
         already_included = set(new_categories) & set(self.dtype.categories)
         if len(already_included) != 0:
@@ -1065,7 +1065,7 @@ def remove_categories(self, removals, inplace=False):
         set_categories
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        if not is_list_like(removals):
+        if not is_list_like(removals, strict=False):
             removals = [removals]
 
         removal_set = set(list(removals))
@@ -1981,7 +1981,7 @@ def __setitem__(self, key, value):
                 raise ValueError("Cannot set a Categorical with another, "
                                  "without identical categories")
 
-        rvalue = value if is_list_like(value) else [value]
+        rvalue = value if is_list_like(value, strict=False) else [value]
 
         from pandas import Index
         to_add = Index(rvalue).difference(self.categories)
@@ -2350,7 +2350,7 @@ def isin(self, values):
         array([ True, False,  True, False,  True, False])
         """
         from pandas.core.series import _sanitize_array
-        if not is_list_like(values):
+        if not is_list_like(values, strict=False):
             raise TypeError("only list-like objects are allowed to be passed"
                             " to isin(), you passed a [{values_type}]"
                             .format(values_type=type(values).__name__))
@@ -2523,7 +2523,7 @@ def _factorize_from_iterable(values):
     """
     from pandas.core.indexes.category import CategoricalIndex
 
-    if not is_list_like(values):
+    if not is_list_like(values, strict=False):
         raise TypeError("Input must be list-like")
 
     if is_categorical(values):
diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
index e4ace2bfe1509..0b0b24f410384 100644
--- a/pandas/core/arrays/datetimelike.py
+++ b/pandas/core/arrays/datetimelike.py
@@ -751,7 +751,7 @@ def _evaluate_compare(self, other, op):
 
         if not isinstance(other, type(self)):
             # coerce to a similar object
-            if not is_list_like(other):
+            if not is_list_like(other, strict=False):
                 # scalar
                 other = [other]
             elif lib.is_scalar(lib.item_from_zerodim(other)):
diff --git a/pandas/core/arrays/integer.py b/pandas/core/arrays/integer.py
index e58109a25e1a5..a6f098f7a3c70 100644
--- a/pandas/core/arrays/integer.py
+++ b/pandas/core/arrays/integer.py
@@ -505,7 +505,7 @@ def cmp_method(self, other):
             mask = None
             if isinstance(other, IntegerArray):
                 other, mask = other._data, other._mask
-            elif is_list_like(other):
+            elif is_list_like(other, strict=False):
                 other = np.asarray(other)
                 if other.ndim > 0 and len(self) != len(other):
                     raise ValueError('Lengths must match to compare')
@@ -568,7 +568,7 @@ def integer_arithmetic_method(self, other):
             elif getattr(other, 'ndim', 0) > 1:
                 raise NotImplementedError(
                     "can only perform ops with 1-d structures")
-            elif is_list_like(other):
+            elif is_list_like(other, strict=False):
                 other = np.asarray(other)
                 if not other.ndim:
                     other = other.item()
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index df9e57cb5f0e1..25d6c7f4c10a6 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -76,7 +76,7 @@ def wrapper(self, other):
             if isna(other):
                 result.fill(nat_result)
 
-        elif not is_list_like(other):
+        elif not is_list_like(other, strict=False):
             raise TypeError(msg.format(cls=type(self).__name__,
                                        typ=type(other).__name__))
         else:
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 00c049497c0d8..dc493cc71c3fd 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -543,7 +543,8 @@ def is_any_frame():
                                 name=getattr(self, 'name', None))
 
             return result, True
-        elif is_list_like(arg) and arg not in compat.string_types:
+        elif (is_list_like(arg, strict=False)
+              and arg not in compat.string_types):
             # we require a list, but not an 'str'
             return self._aggregate_multiple_funcs(arg,
                                                   _level=_level,
diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
index ca0c4db4947c4..4c16d59d7c44d 100644
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -234,7 +234,7 @@ def _in(x, y):
     try:
         return x.isin(y)
     except AttributeError:
-        if is_list_like(x):
+        if is_list_like(x, strict=False):
             try:
                 return y.isin(x)
             except AttributeError:
@@ -249,7 +249,7 @@ def _not_in(x, y):
     try:
         return ~x.isin(y)
     except AttributeError:
-        if is_list_like(x):
+        if is_list_like(x, strict=False):
             try:
                 return ~y.isin(x)
             except AttributeError:
diff --git a/pandas/core/computation/pytables.py b/pandas/core/computation/pytables.py
index e08df3e340138..a7ae037b24f38 100644
--- a/pandas/core/computation/pytables.py
+++ b/pandas/core/computation/pytables.py
@@ -127,7 +127,7 @@ def pr(left, right):
 
     def conform(self, rhs):
         """ inplace conform rhs """
-        if not is_list_like(rhs):
+        if not is_list_like(rhs, strict=False):
             rhs = [rhs]
         if isinstance(rhs, np.ndarray):
             rhs = rhs.ravel()
@@ -472,7 +472,8 @@ def _validate_where(w):
     TypeError : An invalid data type was passed in for w (e.g. dict).
     """
 
-    if not (isinstance(w, (Expr, string_types)) or is_list_like(w)):
+    if not (isinstance(w, (Expr, string_types))
+            or is_list_like(w, strict=False)):
         raise TypeError("where must be passed as a string, Expr, "
                         "or list-like of Exprs")
 
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index a95a45d5f9ae4..5cde4c4fdc69a 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -472,7 +472,7 @@ def infer_dtype_from_array(arr, pandas_dtype=False):
     if isinstance(arr, np.ndarray):
         return arr.dtype, arr
 
-    if not is_list_like(arr):
+    if not is_list_like(arr, strict=False):
         arr = [arr]
 
     if pandas_dtype and is_extension_type(arr):
@@ -518,7 +518,7 @@ def maybe_infer_dtype_type(element):
     tipo = None
     if hasattr(element, 'dtype'):
         tipo = element.dtype
-    elif is_list_like(element):
+    elif is_list_like(element, strict=False):
         element = np.asarray(element)
         tipo = element.dtype
     return tipo
@@ -914,7 +914,7 @@ def maybe_infer_to_datetimelike(value, convert_dates=False):
 
     v = value
 
-    if not is_list_like(v):
+    if not is_list_like(v, strict=False):
         v = [v]
     v = np.array(v, copy=False)
 
diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index a9fc9d13d4ab3..227a0b457bcdd 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -327,8 +327,8 @@ def is_offsetlike(arr_or_obj):
     """
     if isinstance(arr_or_obj, ABCDateOffset):
         return True
-    elif (is_list_like(arr_or_obj) and len(arr_or_obj) and
-          is_object_dtype(arr_or_obj)):
+    elif (is_list_like(arr_or_obj, strict=False) and len(arr_or_obj)
+          and is_object_dtype(arr_or_obj)):
         return all(isinstance(x, ABCDateOffset) for x in arr_or_obj)
     return False
 
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 67f391615eedb..2dd1e3f217ecf 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -7,6 +7,7 @@
 from pandas.compat import (PY2, string_types, text_type,
                            string_and_binary_types, re_type)
 from pandas._libs import lib
+import warnings
 
 is_bool = lib.is_bool
 
@@ -247,7 +248,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj):
+def is_list_like(obj, strict=None):
     """
     Check if the object is list-like.
 
@@ -259,6 +260,8 @@ def is_list_like(obj):
     Parameters
     ----------
     obj : The object to check.
+    strict : boolean, default None
+        Whether `set` should be counted as list-like
 
     Returns
     -------
@@ -282,12 +285,20 @@ def is_list_like(obj):
     >>> is_list_like(np.array(2)))
     False
     """
-
-    return (isinstance(obj, compat.Iterable) and
-            # we do not count strings/unicode/bytes as list-like
-            not isinstance(obj, string_and_binary_types) and
-            # exclude zero-dimensional numpy arrays, effectively scalars
-            not (isinstance(obj, np.ndarray) and obj.ndim == 0))
+    if strict is None and isinstance(obj, set):
+        # only raise warning if necessary
+        warnings.warn('is_list_like will in the future return False for sets. '
+                      'To keep the previous behavior, pass `strict=False`. To '
+                      'adapt the future behavior and silence this warning, '
+                      'pass `strict=True`', FutureWarning)
+    strict = False if strict is None else strict
+
+    list_like = (isinstance(obj, compat.Iterable)
+                 # we do not count strings/unicode/bytes as set-like
+                 and not isinstance(obj, string_and_binary_types)
+                 # exclude zero-dimensional numpy arrays, effectively scalars
+                 and not (isinstance(obj, np.ndarray) and obj.ndim == 0))
+    return list_like and (not strict or not isinstance(obj, set))
 
 
 def is_array_like(obj):
@@ -320,7 +331,7 @@ def is_array_like(obj):
     False
     """
 
-    return is_list_like(obj) and hasattr(obj, "dtype")
+    return is_list_like(obj, strict=False) and hasattr(obj, "dtype")
 
 
 def is_nested_list_like(obj):
@@ -363,8 +374,9 @@ def is_nested_list_like(obj):
     --------
     is_list_like
     """
-    return (is_list_like(obj) and hasattr(obj, '__len__') and
-            len(obj) > 0 and all(is_list_like(item) for item in obj))
+    return (is_list_like(obj, strict=False) and hasattr(obj, '__len__')
+            and len(obj) > 0 and all(is_list_like(item, strict=False)
+                                     for item in obj))
 
 
 def is_dict_like(obj):
diff --git a/pandas/core/dtypes/missing.py b/pandas/core/dtypes/missing.py
index 66998aa6866f6..b04bae77faf1a 100644
--- a/pandas/core/dtypes/missing.py
+++ b/pandas/core/dtypes/missing.py
@@ -464,7 +464,7 @@ def _infer_fill_value(val):
     element to provide proper block construction
     """
 
-    if not is_list_like(val):
+    if not is_list_like(val, strict=False):
         val = [val]
     val = np.array(val, copy=False)
     if is_datetimelike(val):
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 35c476f3539ee..8f1082fb16f80 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -421,7 +421,8 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,
             if not isinstance(data, compat.Sequence):
                 data = list(data)
             if len(data) > 0:
-                if is_list_like(data[0]) and getattr(data[0], 'ndim', 1) == 1:
+                if (is_list_like(data[0], strict=False)
+                        and getattr(data[0], 'ndim', 1) == 1):
                     if is_named_tuple(data[0]) and columns is None:
                         columns = data[0]._fields
                     arrays, columns = _to_arrays(data, columns, dtype=dtype)
@@ -2790,7 +2791,8 @@ def __getitem__(self, key):
 
         # We are left with two options: a single key, and a collection of keys,
         # We interpret tuples as collections only for non-MultiIndex
-        is_single_key = isinstance(key, tuple) or not is_list_like(key)
+        is_single_key = (isinstance(key, tuple)
+                         or not is_list_like(key, strict=False))
 
         if is_single_key:
             if self.columns.nlevels > 1:
@@ -3152,9 +3154,9 @@ def select_dtypes(self, include=None, exclude=None):
         5  False  2.0
         """
 
-        if not is_list_like(include):
+        if not is_list_like(include, strict=False):
             include = (include,) if include is not None else ()
-        if not is_list_like(exclude):
+        if not is_list_like(exclude, strict=False):
             exclude = (exclude,) if exclude is not None else ()
 
         selection = tuple(map(frozenset, (include, exclude)))
@@ -3279,7 +3281,7 @@ def _ensure_valid_index(self, value):
         passed value
         """
         # GH5632, make sure that we are a Series convertible
-        if not len(self.index) and is_list_like(value):
+        if not len(self.index) and is_list_like(value, strict=False):
             try:
                 value = Series(value)
             except (ValueError, NotImplementedError, TypeError):
@@ -7661,7 +7663,7 @@ def isin(self, values):
                                  "a duplicate axis.")
             return self.eq(values.reindex_like(self))
         else:
-            if not is_list_like(values):
+            if not is_list_like(values, strict=False):
                 raise TypeError("only list-like or dict-like objects are "
                                 "allowed to be passed to DataFrame.isin(), "
                                 "you passed a "
@@ -7731,7 +7733,7 @@ def extract_index(data):
             elif isinstance(v, dict):
                 have_dicts = True
                 indexes.append(list(v.keys()))
-            elif is_list_like(v) and getattr(v, 'ndim', 1) == 1:
+            elif is_list_like(v, strict=False) and getattr(v, 'ndim', 1) == 1:
                 have_raw_arrays = True
                 raw_lengths.append(len(v))
 
@@ -7774,7 +7776,8 @@ def convert(v):
         # this is equiv of np.asarray, but does object conversion
         # and platform dtype preservation
         try:
-            if is_list_like(values[0]) or hasattr(values[0], 'len'):
+            if (is_list_like(values[0], strict=False)
+                    or hasattr(values[0], 'len')):
                 values = np.array([convert(v) for v in values])
             elif isinstance(values[0], np.ndarray) and values[0].ndim == 0:
                 # GH#21861
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 0b5a10283946c..275c7d70cc7dd 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -1179,8 +1179,8 @@ def rename_axis(self, mapper, axis=0, copy=True, inplace=False):
         2    3  6
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        non_mapper = is_scalar(mapper) or (is_list_like(mapper) and not
-                                           is_dict_like(mapper))
+        non_mapper = is_scalar(mapper) or (is_list_like(mapper, strict=False)
+                                           and not is_dict_like(mapper))
         if non_mapper:
             return self._set_axis_name(mapper, axis=axis, inplace=inplace)
         else:
@@ -3263,7 +3263,7 @@ def xs(self, key, axis=0, level=None, drop_level=True):
             # if we encounter an array-like and we only have 1 dim
             # that means that their are list/ndarrays inside the Series!
             # so just return them (GH 6394)
-            if not is_list_like(new_values) or self.ndim == 1:
+            if not is_list_like(new_values, strict=False) or self.ndim == 1:
                 return com.maybe_box_datetimelike(new_values)
 
             result = self._constructor_sliced(
@@ -4674,7 +4674,8 @@ def __setattr__(self, name, value):
                 else:
                     object.__setattr__(self, name, value)
             except (AttributeError, TypeError):
-                if isinstance(self, ABCDataFrame) and (is_list_like(value)):
+                if (isinstance(self, ABCDataFrame)
+                        and is_list_like(value, strict=False)):
                     warnings.warn("Pandas doesn't allow columns to be "
                                   "created via a new attribute name - see "
                                   "https://pandas.pydata.org/pandas-docs/"
@@ -5668,7 +5669,7 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
                 if isinstance(value, (dict, ABCSeries)):
                     from pandas import Series
                     value = Series(value)
-                elif not is_list_like(value):
+                elif not is_list_like(value, strict=False):
                     pass
                 else:
                     raise TypeError('"value" parameter must be a scalar, dict '
@@ -5693,7 +5694,7 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
                     obj.fillna(v, limit=limit, inplace=True, downcast=downcast)
                 return result if not inplace else None
 
-            elif not is_list_like(value):
+            elif not is_list_like(value, strict=False):
                 new_data = self._data.fillna(value=value, limit=limit,
                                              inplace=inplace,
                                              downcast=downcast)
@@ -6094,7 +6095,7 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                     return None if inplace else res
 
                 # {'A': NA} -> 0
-                elif not is_list_like(value):
+                elif not is_list_like(value, strict=False):
                     keys = [(k, src) for k, src in compat.iteritems(to_replace)
                             if k in self]
                     keys_len = len(keys) - 1
@@ -6110,8 +6111,9 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                     raise TypeError('value argument must be scalar, dict, or '
                                     'Series')
 
-            elif is_list_like(to_replace):  # [NA, ''] -> [0, 'missing']
-                if is_list_like(value):
+            elif is_list_like(to_replace, strict=False):
+                # [NA, ''] -> [0, 'missing']
+                if is_list_like(value, strict=False):
                     if len(to_replace) != len(value):
                         raise ValueError('Replacement lists must match '
                                          'in length. Expecting %d got %d ' %
@@ -6127,8 +6129,9 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                                                   value=value, inplace=inplace,
                                                   regex=regex)
             elif to_replace is None:
-                if not (is_re_compilable(regex) or
-                        is_list_like(regex) or is_dict_like(regex)):
+                if not (is_re_compilable(regex)
+                        or is_list_like(regex, strict=False)
+                        or is_dict_like(regex)):
                     raise TypeError("'regex' must be a string or a compiled "
                                     "regular expression or a list or dict of "
                                     "strings or regular expressions, you "
@@ -6149,7 +6152,7 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                                                         inplace=inplace,
                                                         regex=regex)
 
-                elif not is_list_like(value):  # NA -> 0
+                elif not is_list_like(value, strict=False):  # NA -> 0
                     new_data = self._data.replace(to_replace=to_replace,
                                                   value=value, inplace=inplace,
                                                   regex=regex)
@@ -6474,10 +6477,10 @@ def asof(self, where, subset=None):
         else:
             if subset is None:
                 subset = self.columns
-            if not is_list_like(subset):
+            if not is_list_like(subset, strict=False):
                 subset = [subset]
 
-        is_list = is_list_like(where)
+        is_list = is_list_like(where, strict=False)
         if not is_list:
             start = self.index[0]
             if isinstance(self.index, PeriodIndex):
@@ -6709,7 +6712,8 @@ def _clip_with_one_bound(self, threshold, method, axis, inplace):
         # GH #15390
         # In order for where method to work, the threshold must
         # be transformed to NDFrame from other array like structure.
-        if (not isinstance(threshold, ABCSeries)) and is_list_like(threshold):
+        if (not isinstance(threshold, ABCSeries)
+                and is_list_like(threshold, strict=False)):
             if isinstance(self, ABCSeries):
                 threshold = pd.Series(threshold, index=self.index)
             else:
@@ -6810,9 +6814,9 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         # so ignore
         # GH 19992
         # numpy doesn't drop a list-like bound containing NaN
-        if not is_list_like(lower) and np.any(pd.isnull(lower)):
+        if not is_list_like(lower, strict=False) and np.any(pd.isnull(lower)):
             lower = None
-        if not is_list_like(upper) and np.any(pd.isnull(upper)):
+        if not is_list_like(upper, strict=False) and np.any(pd.isnull(upper)):
             upper = None
 
         # GH 2747 (arguments were reversed)
diff --git a/pandas/core/groupby/base.py b/pandas/core/groupby/base.py
index ac84971de08d8..228e2434ebb2c 100644
--- a/pandas/core/groupby/base.py
+++ b/pandas/core/groupby/base.py
@@ -57,7 +57,8 @@ def _gotitem(self, key, ndim, subset=None):
                               **kwargs)
         self._reset_cache()
         if subset.ndim == 2:
-            if is_scalar(key) and key in subset or is_list_like(key):
+            if (is_scalar(key) and key in subset
+                    or is_list_like(key, strict=False)):
                 self._selection = key
         return self
 
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index e7144fb1d2932..d23acea6f168e 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -440,7 +440,7 @@ def _get_grouper(obj, key=None, axis=0, level=None, sort=True,
         # on the outside of this condition.
         # (GH 17621)
         if isinstance(group_axis, MultiIndex):
-            if is_list_like(level) and len(level) == 1:
+            if is_list_like(level, strict=False) and len(level) == 1:
                 level = level[0]
 
             if key is None and is_scalar(level):
@@ -452,7 +452,7 @@ def _get_grouper(obj, key=None, axis=0, level=None, sort=True,
             # allow level to be a length-one list-like object
             # (e.g., level=[0])
             # GH 13901
-            if is_list_like(level):
+            if is_list_like(level, strict=False):
                 nlevels = len(level)
                 if nlevels == 1:
                     level = level[0]
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index a1868980faed3..594770294a3cd 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -63,7 +63,7 @@ def _delegate_property_get(self, name):
         if isinstance(result, np.ndarray):
             if is_integer_dtype(result):
                 result = result.astype('int64')
-        elif not is_list_like(result):
+        elif not is_list_like(result, strict=False):
             return result
 
         result = np.asarray(result)
@@ -97,7 +97,7 @@ def _delegate_method(self, name, *args, **kwargs):
         method = getattr(values, name)
         result = method(*args, **kwargs)
 
-        if not is_list_like(result):
+        if not is_list_like(result, strict=False):
             return result
 
         result = Series(result, index=self.index, name=self.name)
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 51c84d6e28cb4..4fb92ca6fb266 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -445,7 +445,7 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
         elif data is None or is_scalar(data):
             cls._scalar_data_error(data)
         else:
-            if tupleize_cols and is_list_like(data):
+            if tupleize_cols and is_list_like(data, strict=False):
                 # GH21470: convert iterable to list before determining if empty
                 if is_iterator(data):
                     data = list(data)
@@ -1020,11 +1020,11 @@ def _validate_names(self, name=None, names=None, deep=False):
         elif names is None and name is None:
             return deepcopy(self.names) if deep else self.names
         elif names is not None:
-            if not is_list_like(names):
+            if not is_list_like(names, strict=False):
                 raise TypeError("Must pass list-like as `names`.")
             return names
         else:
-            if not is_list_like(name):
+            if not is_list_like(name, strict=False):
                 return [name]
             return name
 
@@ -1222,7 +1222,7 @@ def _to_safe_for_reshape(self):
         return self
 
     def _assert_can_do_setop(self, other):
-        if not is_list_like(other):
+        if not is_list_like(other, strict=False):
             raise TypeError('Input must be Index or array-like')
         return True
 
@@ -1267,7 +1267,7 @@ def _set_names(self, values, level=None):
         ------
         TypeError if each name is not hashable.
         """
-        if not is_list_like(values):
+        if not is_list_like(values, strict=False):
             raise ValueError('Names must be a list-like')
         if len(values) != 1:
             raise ValueError('Length of new names must be 1, got %d' %
@@ -1337,17 +1337,18 @@ def set_names(self, names, level=None, inplace=False):
         if level is not None and not isinstance(self, MultiIndex):
             raise ValueError('Level must be None for non-MultiIndex')
 
-        if level is not None and not is_list_like(level) and is_list_like(
-                names):
+        if (level is not None and not is_list_like(level, strict=False)
+                and is_list_like(names, strict=False)):
             msg = "Names must be a string when a single level is provided."
             raise TypeError(msg)
 
-        if not is_list_like(names) and level is None and self.nlevels > 1:
+        if (not is_list_like(names, strict=False)
+                and level is None and self.nlevels > 1):
             raise TypeError("Must pass list-like as `names`.")
 
-        if not is_list_like(names):
+        if not is_list_like(names, strict=False):
             names = [names]
-        if level is not None and not is_list_like(level):
+        if level is not None and not is_list_like(level, strict=False):
             level = [level]
 
         if inplace:
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 45703c220a4be..4d2aaaa3ddaad 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -244,7 +244,7 @@ def _is_dtype_compat(self, other):
                                 "when appending")
         else:
             values = other
-            if not is_list_like(values):
+            if not is_list_like(values, strict=False):
                 values = [values]
             other = CategoricalIndex(self._create_categorical(
                 other, dtype=self.dtype))
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index 1ec30ecbb3a3b..ed896e55270b6 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -322,7 +322,7 @@ def __contains__(self, key):
         try:
             res = self.get_loc(key)
             return (is_scalar(res) or isinstance(res, slice) or
-                    (is_list_like(res) and len(res)))
+                    (is_list_like(res, strict=False) and len(res)))
         except (KeyError, TypeError, ValueError):
             return False
 
diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
index e40ceadc1a083..616f5336a7899 100644
--- a/pandas/core/indexes/datetimes.py
+++ b/pandas/core/indexes/datetimes.py
@@ -1396,7 +1396,7 @@ def delete(self, loc):
             if loc in (0, -len(self), -1, len(self) - 1):
                 freq = self.freq
         else:
-            if is_list_like(loc):
+            if is_list_like(loc, strict=False):
                 loc = lib.maybe_indices_to_slice(
                     ensure_int64(np.array(loc)), len(self))
             if isinstance(loc, slice) and loc.step in (1, None):
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 25d4dd0cbcc81..b9760f3b8d683 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -560,7 +560,7 @@ def _maybe_convert_i8(self, key):
             Int64Index if converted list-like.
         """
         original = key
-        if is_list_like(key):
+        if is_list_like(key, strict=False):
             key = ensure_index(key)
 
         if not self._needs_i8_conversion(key):
@@ -734,7 +734,7 @@ def get_loc(self, key, method=None):
     def get_value(self, series, key):
         if com.is_bool_indexer(key):
             loc = key
-        elif is_list_like(key):
+        elif is_list_like(key, strict=False):
             loc = self.get_indexer(key)
         elif isinstance(key, slice):
 
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 3cccb65503378..367f25b21889d 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -389,15 +389,16 @@ def set_levels(self, levels, level=None, inplace=False,
                    labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
                    names=[u'foo', u'bar'])
         """
-        if level is not None and not is_list_like(level):
-            if not is_list_like(levels):
+        if level is not None and not is_list_like(level, strict=False):
+            if not is_list_like(levels, strict=False):
                 raise TypeError("Levels must be list-like")
-            if is_list_like(levels[0]):
+            if is_list_like(levels[0], strict=False):
                 raise TypeError("Levels must be list-like")
             level = [level]
             levels = [levels]
-        elif level is None or is_list_like(level):
-            if not is_list_like(levels) or not is_list_like(levels[0]):
+        elif level is None or is_list_like(level, strict=False):
+            if (not is_list_like(levels, strict=False)
+                    or not is_list_like(levels[0], strict=False)):
                 raise TypeError("Levels must be list of lists-like")
 
         if inplace:
@@ -485,15 +486,16 @@ def set_labels(self, labels, level=None, inplace=False,
                    labels=[[1, 0, 1, 0], [0, 0, 1, 1]],
                    names=[u'foo', u'bar'])
         """
-        if level is not None and not is_list_like(level):
-            if not is_list_like(labels):
+        if level is not None and not is_list_like(level, strict=False):
+            if not is_list_like(labels, strict=False):
                 raise TypeError("Labels must be list-like")
-            if is_list_like(labels[0]):
+            if is_list_like(labels[0], strict=False):
                 raise TypeError("Labels must be list-like")
             level = [level]
             labels = [labels]
-        elif level is None or is_list_like(level):
-            if not is_list_like(labels) or not is_list_like(labels[0]):
+        elif level is None or is_list_like(level, strict=False):
+            if (not is_list_like(labels, strict=False)
+                    or not is_list_like(labels[0], strict=False)):
                 raise TypeError("Labels must be list of lists-like")
 
         if inplace:
@@ -685,7 +687,7 @@ def _set_names(self, names, level=None, validate=True):
         """
         # GH 15110
         # Don't allow a single string for names in a MultiIndex
-        if names is not None and not is_list_like(names):
+        if names is not None and not is_list_like(names, strict=False):
             raise ValueError('Names should be list-like for a MultiIndex')
         names = list(names)
 
@@ -1178,7 +1180,7 @@ def to_frame(self, index=True, name=None):
 
         from pandas import DataFrame
         if name is not None:
-            if not is_list_like(name):
+            if not is_list_like(name, strict=False):
                 raise TypeError("'name' must be a list / sequence "
                                 "of column names.")
 
@@ -1295,7 +1297,7 @@ def from_arrays(cls, arrays, sortorder=None, names=None):
         MultiIndex.from_product : Make a MultiIndex from cartesian product
                                   of iterables
         """
-        if not is_list_like(arrays):
+        if not is_list_like(arrays, strict=False):
             raise TypeError("Input must be a list / sequence of array-likes.")
         elif is_iterator(arrays):
             arrays = list(arrays)
@@ -1344,7 +1346,7 @@ def from_tuples(cls, tuples, sortorder=None, names=None):
         MultiIndex.from_product : Make a MultiIndex from cartesian product
                                   of iterables
         """
-        if not is_list_like(tuples):
+        if not is_list_like(tuples, strict=False):
             raise TypeError('Input must be a list / sequence of tuple-likes.')
         elif is_iterator(tuples):
             tuples = list(tuples)
@@ -1403,7 +1405,7 @@ def from_product(cls, iterables, sortorder=None, names=None):
         from pandas.core.arrays.categorical import _factorize_from_iterables
         from pandas.core.reshape.util import cartesian_product
 
-        if not is_list_like(iterables):
+        if not is_list_like(iterables, strict=False):
             raise TypeError("Input must be a list / sequence of iterables.")
         elif is_iterator(iterables):
             iterables = list(iterables)
@@ -1976,7 +1978,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
         target = ensure_index(target)
 
         # empty indexer
-        if is_list_like(target) and not len(target):
+        if is_list_like(target, strict=False) and not len(target):
             return ensure_platform_int(np.array([]))
 
         if not isinstance(target, MultiIndex):
@@ -2574,7 +2576,7 @@ def _update_indexer(idxr, indexer=indexer):
                 indexer = _update_indexer(_convert_to_indexer(k),
                                           indexer=indexer)
 
-            elif is_list_like(k):
+            elif is_list_like(k, strict=False):
                 # a collection of labels to include from this level (these
                 # are or'd)
                 indexers = None
diff --git a/pandas/core/indexes/timedeltas.py b/pandas/core/indexes/timedeltas.py
index ee604f44b98e0..a0a683106bef2 100644
--- a/pandas/core/indexes/timedeltas.py
+++ b/pandas/core/indexes/timedeltas.py
@@ -488,7 +488,8 @@ def get_loc(self, key, method=None, tolerance=None):
         -------
         loc : int
         """
-        if is_list_like(key) or (isinstance(key, datetime) and key is not NaT):
+        if (is_list_like(key, strict=False)
+                or (isinstance(key, datetime) and key is not NaT)):
             # GH#20464 datetime check here is to ensure we don't allow
             #   datetime objects to be incorrectly treated as timedelta
             #   objects; NaT is a special case because it plays a double role
@@ -698,7 +699,7 @@ def delete(self, loc):
             if loc in (0, -len(self), -1, len(self) - 1):
                 freq = self.freq
         else:
-            if is_list_like(loc):
+            if is_list_like(loc, strict=False):
                 loc = lib.maybe_indices_to_slice(
                     ensure_int64(np.array(loc)), len(self))
             if isinstance(loc, slice) and loc.step in (1, None):
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index b3c913f21dd86..39cf27e388ce1 100755
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -2528,7 +2528,7 @@ def check_setitem_lengths(indexer, value, values):
     """
     # boolean with truth values == len of the value is ok too
     if isinstance(indexer, (np.ndarray, list)):
-        if is_list_like(value) and len(indexer) != len(value):
+        if is_list_like(value, strict=False) and len(indexer) != len(value):
             if not (isinstance(indexer, np.ndarray) and
                     indexer.dtype == np.bool_ and
                     len(indexer[indexer]) == len(value)):
@@ -2537,7 +2537,7 @@ def check_setitem_lengths(indexer, value, values):
     # slice
     elif isinstance(indexer, slice):
 
-        if is_list_like(value) and len(values):
+        if is_list_like(value, strict=False) and len(values):
             if len(value) != length_of_indexer(indexer, values):
                 raise ValueError("cannot set using a slice indexer with a "
                                  "different length than the value")
@@ -2677,16 +2677,16 @@ def is_nested_tuple(tup, labels):
 
     for i, k in enumerate(tup):
 
-        if is_list_like(k) or isinstance(k, slice):
+        if is_list_like(k, strict=False) or isinstance(k, slice):
             return isinstance(labels, MultiIndex)
 
     return False
 
 
 def is_list_like_indexer(key):
-    # allow a list_like, but exclude NamedTuples which can be indexers
-    return is_list_like(key) and not (isinstance(key, tuple) and
-                                      type(key) is not tuple)
+    # allow a list-like, but exclude NamedTuples which can be indexers
+    return (is_list_like(key, strict=False)
+            and not (isinstance(key, tuple) and type(key) is not tuple))
 
 
 def is_label_like(key):
@@ -2734,9 +2734,9 @@ def _non_reducing_slice(slice_):
 
     def pred(part):
         # true when slice does *not* reduce
-        return isinstance(part, slice) or is_list_like(part)
+        return isinstance(part, slice) or is_list_like(part, strict=False)
 
-    if not is_list_like(slice_):
+    if not is_list_like(slice_, strict=False):
         if not isinstance(slice_, slice):
             # a 1-d slice, like df.loc[1]
             slice_ = [[slice_]]
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index 0e57dd33b1c4e..f24ae14013d93 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -910,7 +910,7 @@ def _is_scalar_indexer(indexer):
         def _is_empty_indexer(indexer):
             # return a boolean if we have an empty indexer
 
-            if is_list_like(indexer) and not len(indexer):
+            if is_list_like(indexer, strict=False) and not len(indexer):
                 return True
             if arr_value.ndim == 1:
                 if not isinstance(indexer, tuple):
@@ -978,7 +978,8 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
         mask = getattr(mask, 'values', mask)
 
         # if we are passed a scalar None, convert it here
-        if not is_list_like(new) and isna(new) and not self.is_object:
+        if (not is_list_like(new, strict=False)
+                and isna(new) and not self.is_object):
             new = self.fill_value
 
         if self._can_hold_element(new):
@@ -1002,7 +1003,7 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
             #
             # TODO: this prob needs some better checking
             # for 2D cases
-            if ((is_list_like(new) and
+            if ((is_list_like(new, strict=False) and
                  np.any(mask[mask]) and
                  getattr(new, 'ndim', 1) == 1)):
 
@@ -1378,7 +1379,8 @@ def get_result(other):
 
             # avoid numpy warning of elementwise comparisons
             elif func.__name__ == 'eq':
-                if is_list_like(other) and not isinstance(other, np.ndarray):
+                if (is_list_like(other, strict=False)
+                        and not isinstance(other, np.ndarray)):
                     other = np.asarray(other)
 
                     # if we can broadcast, then ok
@@ -1434,7 +1436,8 @@ def handle_error():
 
                 # differentiate between an invalid ndarray-ndarray comparison
                 # and an invalid type comparison
-                if isinstance(values, np.ndarray) and is_list_like(other):
+                if (isinstance(values, np.ndarray)
+                        and is_list_like(other, strict=False)):
                     raise ValueError(
                         'Invalid broadcasting comparison [{other!r}] with '
                         'block values'.format(other=other))
@@ -1648,7 +1651,7 @@ def _nanpercentile(values, q, axis, **kw):
 
         from pandas import Float64Index
         is_empty = values.shape[axis] == 0
-        if is_list_like(qs):
+        if is_list_like(qs, strict=False):
             ax = Float64Index(qs)
 
             if is_empty:
@@ -2484,8 +2487,8 @@ def should_store(self, value):
 
     def replace(self, to_replace, value, inplace=False, filter=None,
                 regex=False, convert=True, mgr=None):
-        to_rep_is_list = is_list_like(to_replace)
-        value_is_list = is_list_like(value)
+        to_rep_is_list = is_list_like(to_replace, strict=False)
+        value_is_list = is_list_like(value, strict=False)
         both_lists = to_rep_is_list and value_is_list
         either_list = to_rep_is_list or value_is_list
 
@@ -3473,7 +3476,7 @@ def _putmask_smart(v, m, n):
     # that numpy does when numeric are mixed with strings
 
     # n should be the length of the mask or a scalar here
-    if not is_list_like(n):
+    if not is_list_like(n, strict=False):
         n = np.repeat(n, len(m))
     elif isinstance(n, np.ndarray) and n.ndim == 0:  # numpy scalar
         n = np.repeat(np.array(n, ndmin=1), len(m))
@@ -3505,7 +3508,7 @@ def _putmask_smart(v, m, n):
              is_integer_dtype(nn_at.dtype))):
 
             comp = (nn == nn_at)
-            if is_list_like(comp) and comp.all():
+            if is_list_like(comp, strict=False) and comp.all():
                 nv = v.copy()
                 nv[m] = nn_at
                 return nv
diff --git a/pandas/core/ops.py b/pandas/core/ops.py
index 20559bca9caed..2967b38abda53 100644
--- a/pandas/core/ops.py
+++ b/pandas/core/ops.py
@@ -1613,7 +1613,8 @@ def wrapper(self, other):
         else:
             # scalars, list, tuple, np.array
             is_other_int_dtype = is_integer_dtype(np.asarray(other))
-            if is_list_like(other) and not isinstance(other, np.ndarray):
+            if (is_list_like(other, strict=False)
+                    and not isinstance(other, np.ndarray)):
                 # TODO: Can we do this before the is_integer_dtype check?
                 # could the is_integer_dtype check be checking the wrong
                 # thing?  e.g. other = [[0, 1], [2, 3], [4, 5]]?
@@ -1829,7 +1830,7 @@ def to_series(right):
             raise ValueError('Unable to coerce to Series/DataFrame, dim '
                              'must be <= 2: {dim}'.format(dim=right.shape))
 
-    elif (is_list_like(right) and
+    elif (is_list_like(right, strict=False) and
           not isinstance(right, (ABCSeries, ABCDataFrame))):
         # GH17901
         right = to_series(right)
diff --git a/pandas/core/panel.py b/pandas/core/panel.py
index 1e2d4000413bb..b8b672d8d6009 100644
--- a/pandas/core/panel.py
+++ b/pandas/core/panel.py
@@ -286,7 +286,7 @@ def __getitem__(self, key):
 
         if isinstance(self._info_axis, MultiIndex):
             return self._getitem_multilevel(key)
-        if not (is_list_like(key) or isinstance(key, slice)):
+        if not (is_list_like(key, strict=False) or isinstance(key, slice)):
             return super(Panel, self).__getitem__(key)
         return self.loc[key]
 
@@ -884,7 +884,7 @@ def _ixs(self, i, axis=0):
         # if we have a multi-index and a single tuple, then its a reduction
         # (GH 7516)
         if not (isinstance(ax, MultiIndex) and isinstance(key, tuple)):
-            if is_list_like(key):
+            if is_list_like(key, strict=False):
                 indexer = {self._get_axis_name(axis): key}
                 return self.reindex(**indexer)
 
diff --git a/pandas/core/reshape/melt.py b/pandas/core/reshape/melt.py
index 26221143c0cdf..6b1172a1fb17b 100644
--- a/pandas/core/reshape/melt.py
+++ b/pandas/core/reshape/melt.py
@@ -26,7 +26,7 @@ def melt(frame, id_vars=None, value_vars=None, var_name=None,
          value_name='value', col_level=None):
     # TODO: what about the existing index?
     if id_vars is not None:
-        if not is_list_like(id_vars):
+        if not is_list_like(id_vars, strict=False):
             id_vars = [id_vars]
         elif (isinstance(frame.columns, ABCMultiIndex) and
               not isinstance(id_vars, list)):
@@ -38,7 +38,7 @@ def melt(frame, id_vars=None, value_vars=None, var_name=None,
         id_vars = []
 
     if value_vars is not None:
-        if not is_list_like(value_vars):
+        if not is_list_like(value_vars, strict=False):
             value_vars = [value_vars]
         elif (isinstance(frame.columns, ABCMultiIndex) and
               not isinstance(value_vars, list)):
@@ -409,7 +409,7 @@ def melt_stub(df, stub, i, j, value_vars, sep):
 
         return newdf.set_index(i + [j])
 
-    if not is_list_like(stubnames):
+    if not is_list_like(stubnames, strict=False):
         stubnames = [stubnames]
     else:
         stubnames = list(stubnames)
@@ -417,7 +417,7 @@ def melt_stub(df, stub, i, j, value_vars, sep):
     if any(col in stubnames for col in df.columns):
         raise ValueError("stubname can't be identical to a column name")
 
-    if not is_list_like(i):
+    if not is_list_like(i, strict=False):
         i = [i]
     else:
         i = list(i)
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index d0c7b66978661..ddf51f3154ad8 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -1296,9 +1296,9 @@ def _validate_specification(self):
         # add 'by' to our key-list so we can have it in the
         # output as a key
         if self.left_by is not None:
-            if not is_list_like(self.left_by):
+            if not is_list_like(self.left_by, strict=False):
                 self.left_by = [self.left_by]
-            if not is_list_like(self.right_by):
+            if not is_list_like(self.right_by, strict=False):
                 self.right_by = [self.right_by]
 
             if len(self.left_by) != len(self.right_by):
diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index b525dddeb1ba5..7fe900e339648 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -48,7 +48,7 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
 
     values_passed = values is not None
     if values_passed:
-        if is_list_like(values):
+        if is_list_like(values, strict=False):
             values_multi = True
             values = list(values)
         else:
@@ -383,7 +383,8 @@ def pivot(data, index=None, columns=None, values=None):
             index = data[index]
         index = MultiIndex.from_arrays([index, data[columns]])
 
-        if is_list_like(values) and not isinstance(values, tuple):
+        if (is_list_like(values, strict=False)
+                and not isinstance(values, tuple)):
             # Exclude tuple because it is seen as a single column name
             indexed = data._constructor(data[values].values, index=index,
                                         columns=values)
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 50f6e310705d7..e306f4626a7ed 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -743,7 +743,7 @@ def check_len(item, name):
             len_msg = ("Length of '{name}' ({len_item}) did not match the "
                        "length of the columns being encoded ({len_enc}).")
 
-            if is_list_like(item):
+            if is_list_like(item, strict=False):
                 if not len(item) == data_to_encode.shape[1]:
                     len_msg = \
                         len_msg.format(name=name, len_item=len(item),
diff --git a/pandas/core/reshape/util.py b/pandas/core/reshape/util.py
index 1c2033d90cd8a..af99172b2c65a 100644
--- a/pandas/core/reshape/util.py
+++ b/pandas/core/reshape/util.py
@@ -32,10 +32,10 @@ def cartesian_product(X):
     pandas.compat.product : An alias for itertools.product.
     """
     msg = "Input must be a list-like of list-likes"
-    if not is_list_like(X):
+    if not is_list_like(X, strict=False):
         raise TypeError(msg)
     for x in X:
-        if not is_list_like(x):
+        if not is_list_like(x, strict=False):
             raise TypeError(msg)
 
     if len(X) == 0:
diff --git a/pandas/core/series.py b/pandas/core/series.py
index a613b22ea9046..4cd1745baf990 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -249,10 +249,10 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                     data = data.to_dense()
 
             if index is None:
-                if not is_list_like(data):
+                if not is_list_like(data, strict=False):
                     data = [data]
                 index = ibase.default_index(len(data))
-            elif is_list_like(data):
+            elif is_list_like(data, strict=False):
 
                 # a scalar numpy array is list-like but doesn't
                 # have a proper length
@@ -775,8 +775,8 @@ def __getitem__(self, key):
             result = self.index.get_value(self, key)
 
             if not is_scalar(result):
-                if is_list_like(result) and not isinstance(result, Series):
-
+                if (is_list_like(result, strict=False)
+                        and not isinstance(result, Series)):
                     # we need to box if loc of the key isn't scalar here
                     # otherwise have inline ndarray/lists
                     try:
@@ -1895,7 +1895,7 @@ def quantile(self, q=0.5, interpolation='linear'):
 
         result = self._data.quantile(qs=q, interpolation=interpolation)
 
-        if is_list_like(q):
+        if is_list_like(q, strict=False):
             return self._constructor(result,
                                      index=Float64Index(q),
                                      name=self.name)
@@ -2561,7 +2561,7 @@ def _try_kind_sort(arr):
 
         argsorted = _try_kind_sort(arr[good])
 
-        if is_list_like(ascending):
+        if is_list_like(ascending, strict=False):
             if len(ascending) != 1:
                 raise ValueError('Length of ascending (%d) must be 1 '
                                  'for Series' % (len(ascending)))
@@ -3494,8 +3494,8 @@ def rename(self, index=None, **kwargs):
         kwargs['inplace'] = validate_bool_kwarg(kwargs.get('inplace', False),
                                                 'inplace')
 
-        non_mapping = is_scalar(index) or (is_list_like(index) and
-                                           not is_dict_like(index))
+        non_mapping = is_scalar(index) or (is_list_like(index, strict=False)
+                                           and not is_dict_like(index))
         if non_mapping:
             return self._set_name(index, inplace=kwargs.get('inplace'))
         return super(Series, self).rename(index=index, **kwargs)
@@ -4234,9 +4234,10 @@ def _try_cast(arr, take_fast_path):
             subarr = maybe_cast_to_datetime(arr, dtype)
             # Take care in creating object arrays (but iterators are not
             # supported):
-            if is_object_dtype(dtype) and (is_list_like(subarr) and
-                                           not (is_iterator(subarr) or
-                                           isinstance(subarr, np.ndarray))):
+            if (is_object_dtype(dtype)
+                and (is_list_like(subarr, strict=False)
+                     and not (is_iterator(subarr)
+                              or isinstance(subarr, np.ndarray)))):
                 subarr = construct_1d_object_array_from_listlike(subarr)
             elif not is_extension_type(subarr):
                 subarr = construct_1d_ndarray_preserving_na(subarr, dtype,
diff --git a/pandas/core/sorting.py b/pandas/core/sorting.py
index 5aa9ea658482b..fe8bdb4d32c67 100644
--- a/pandas/core/sorting.py
+++ b/pandas/core/sorting.py
@@ -424,7 +424,7 @@ def safe_sort(values, labels=None, na_sentinel=-1, assume_unique=False):
     ValueError
         * If ``labels`` is not None and ``values`` contain duplicates.
     """
-    if not is_list_like(values):
+    if not is_list_like(values, strict=False):
         raise TypeError("Only list-like objects are allowed to be passed to"
                         "safe_sort as values")
 
@@ -459,7 +459,7 @@ def sort_mixed(values):
     if labels is None:
         return ordered
 
-    if not is_list_like(labels):
+    if not is_list_like(labels, strict=False):
         raise TypeError("Only list-like objects or None are allowed to be"
                         "passed to safe_sort as labels")
     labels = ensure_platform_int(np.asarray(labels))
diff --git a/pandas/core/sparse/array.py b/pandas/core/sparse/array.py
index 186a2490a5f2e..47ffdd3539bd4 100644
--- a/pandas/core/sparse/array.py
+++ b/pandas/core/sparse/array.py
@@ -776,7 +776,7 @@ def _sanitize_values(arr):
         if isinstance(arr, np.ndarray):
             pass
 
-        elif is_list_like(arr) and len(arr) > 0:
+        elif is_list_like(arr, strict=False) and len(arr) > 0:
             arr = maybe_convert_platform(arr)
 
         else:
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 5a23951145cb4..27bfc58bc5dc5 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -1973,7 +1973,7 @@ def _wrap_result(self, result, use_codes=True,
             # not needed when inferred
 
             def cons_row(x):
-                if is_list_like(x):
+                if is_list_like(x, strict=False):
                     return x
                 else:
                     return [x]
@@ -2083,12 +2083,12 @@ def _get_series_list(self, others, ignore_index=False):
         elif isinstance(others, np.ndarray) and others.ndim == 2:
             others = DataFrame(others, index=idx)
             return ([others[x] for x in others], False)
-        elif is_list_like(others):
+        elif is_list_like(others, strict=True):
             others = list(others)  # ensure iterators do not get read twice etc
 
             # in case of list-like `others`, all elements must be
             # either one-dimensional list-likes or scalars
-            if all(is_list_like(x) for x in others):
+            if all(is_list_like(x, strict=True) for x in others):
                 los = []
                 join_warn = False
                 depr_warn = False
@@ -2116,7 +2116,8 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_list_like(x) for x in nxt))
+                                or all(not is_list_like(x, strict=True)
+                                       for x in nxt))
 
                     # DataFrame is false positive of is_legal
                     # because "x in df" returns column names
@@ -2134,7 +2135,7 @@ def _get_series_list(self, others, ignore_index=False):
                                   'deprecated and will be removed in a future '
                                   'version.', FutureWarning, stacklevel=3)
                 return (los, join_warn)
-            elif all(not is_list_like(x) for x in others):
+            elif all(not is_list_like(x, strict=True) for x in others):
                 return ([Series(others, index=idx)], False)
         raise TypeError(err_msg)
 
diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
index eb8d2b0b6c809..ac851b8ee3cdf 100644
--- a/pandas/core/tools/datetimes.py
+++ b/pandas/core/tools/datetimes.py
@@ -375,7 +375,7 @@ def _adjust_to_origin(arg, origin, unit):
         offset = offset // tslibs.Timedelta(1, unit=unit)
 
         # scalars & ndarray-like can handle the addition
-        if is_list_like(arg) and not isinstance(
+        if is_list_like(arg, strict=False) and not isinstance(
                 arg, (ABCSeries, ABCIndexClass, np.ndarray)):
             arg = np.asarray(arg)
         arg = arg + offset
@@ -580,7 +580,7 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
         else:
             convert_listlike = partial(convert_listlike, name=arg.name)
             result = convert_listlike(arg, box, format)
-    elif is_list_like(arg):
+    elif is_list_like(arg, strict=False):
         cache_array = _maybe_cache(arg, format, cache, convert_listlike)
         if not cache_array.empty:
             result = _convert_and_box_cache(arg, cache_array, box, errors)
@@ -868,7 +868,7 @@ def _convert_listlike(arg, format):
         return Series(values, index=arg.index, name=arg.name)
     elif isinstance(arg, ABCIndexClass):
         return _convert_listlike(arg, format)
-    elif is_list_like(arg):
+    elif is_list_like(arg, strict=False):
         return _convert_listlike(arg, format)
 
     return _convert_listlike(np.array([arg]), format)[0]
diff --git a/pandas/core/tools/timedeltas.py b/pandas/core/tools/timedeltas.py
index 4dc4fcb00d84d..f1e64dc04af3b 100644
--- a/pandas/core/tools/timedeltas.py
+++ b/pandas/core/tools/timedeltas.py
@@ -88,7 +88,7 @@ def to_timedelta(arg, unit='ns', box=True, errors='raise'):
     elif isinstance(arg, np.ndarray) and arg.ndim == 0:
         # extract array scalar and process below
         arg = arg.item()
-    elif is_list_like(arg) and getattr(arg, 'ndim', 1) == 1:
+    elif is_list_like(arg, strict=False) and getattr(arg, 'ndim', 1) == 1:
         return _convert_listlike(arg, unit=unit, box=box, errors=errors)
     elif getattr(arg, 'ndim', 1) > 1:
         raise TypeError('arg must be a string, timedelta, list, tuple, '
diff --git a/pandas/core/util/hashing.py b/pandas/core/util/hashing.py
index e62d70847437c..a873d49af1e9c 100644
--- a/pandas/core/util/hashing.py
+++ b/pandas/core/util/hashing.py
@@ -140,7 +140,7 @@ def hash_tuples(vals, encoding='utf8', hash_key=None):
     if isinstance(vals, tuple):
         vals = [vals]
         is_tuple = True
-    elif not is_list_like(vals):
+    elif not is_list_like(vals, strict=False):
         raise TypeError("must be convertible to a list-of-tuples")
 
     from pandas import Categorical, MultiIndex
diff --git a/pandas/core/window.py b/pandas/core/window.py
index ea0ec79d655fb..650860195b76f 100644
--- a/pandas/core/window.py
+++ b/pandas/core/window.py
@@ -149,7 +149,8 @@ def _gotitem(self, key, ndim, subset=None):
         self = self._shallow_copy(subset)
         self._reset_cache()
         if subset.ndim == 2:
-            if is_scalar(key) and key in subset or is_list_like(key):
+            if (is_scalar(key) and key in subset
+                    or is_list_like(key, strict=False)):
                 self._selection = key
         return self
 
diff --git a/pandas/io/excel.py b/pandas/io/excel.py
index 00b4c704c681b..a538b567fbdc4 100644
--- a/pandas/io/excel.py
+++ b/pandas/io/excel.py
@@ -639,13 +639,13 @@ def _parse_cell(cell_contents, cell_typ):
                 output[asheetname] = DataFrame()
                 continue
 
-            if is_list_like(header) and len(header) == 1:
+            if is_list_like(header, strict=False) and len(header) == 1:
                 header = header[0]
 
             # forward fill and pull out names for MultiIndex column
             header_names = None
             if header is not None:
-                if is_list_like(header):
+                if is_list_like(header, strict=False):
                     header_names = []
                     control_row = [True] * len(data[0])
                     for row in header:
@@ -660,9 +660,9 @@ def _parse_cell(cell_contents, cell_typ):
                 else:
                     data[header] = _trim_excel_header(data[header])
 
-            if is_list_like(index_col):
+            if is_list_like(index_col, strict=False):
                 # forward fill values for MultiIndex index
-                if not is_list_like(header):
+                if not is_list_like(header, strict=False):
                     offset = 1 + header
                 else:
                     offset = 1 + max(header)
@@ -675,7 +675,8 @@ def _parse_cell(cell_contents, cell_typ):
                         else:
                             last = data[row][col]
 
-            has_index_names = is_list_like(header) and len(header) > 1
+            has_index_names = (is_list_like(header, strict=False)
+                               and len(header) > 1)
 
             # GH 12292 : error when read one empty column from excel file
             try:
@@ -794,7 +795,7 @@ def _pop_header_name(row, index_col):
         return none_fill(row[0]), row[1:]
     else:
         # pop out header name and fill w/ blank
-        i = index_col if not is_list_like(index_col) else max(index_col)
+        i = index_col if not is_list_like(index_col, strict=False) else max(index_col)
         return none_fill(row[i]), row[:i] + [''] + row[i + 1:]
 
 
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index db86409adc2b0..a74559a6966a1 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -517,7 +517,7 @@ def _to_str_columns(self):
 
         str_index = self._get_formatted_index(frame)
 
-        if not is_list_like(self.header) and not self.header:
+        if not is_list_like(self.header, strict=False) and not self.header:
             stringified = []
             for i, c in enumerate(frame):
                 fmt_values = self._format_col(i)
@@ -526,7 +526,7 @@ def _to_str_columns(self):
                                                adj=self.adj)
                 stringified.append(fmt_values)
         else:
-            if is_list_like(self.header):
+            if is_list_like(self.header, strict=False):
                 if len(self.header) != len(self.columns):
                     raise ValueError(('Writing {ncols} cols but got {nalias} '
                                       'aliases'
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index f4bb53ba4f218..7d9bcbb456fa8 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -1104,7 +1104,7 @@ def bar(self, subset=None, axis=0, color='#d65f5f', width=100,
         if align not in ('left', 'zero', 'mid'):
             raise ValueError("`align` must be one of {'left', 'zero',' mid'}")
 
-        if not (is_list_like(color)):
+        if not (is_list_like(color, strict=False)):
             color = [color, color]
         elif len(color) == 1:
             color = [color[0], color[0]]
diff --git a/pandas/io/html.py b/pandas/io/html.py
index 04534ff591a2c..ec29957b53913 100644
--- a/pandas/io/html.py
+++ b/pandas/io/html.py
@@ -105,7 +105,8 @@ def _get_skiprows(skiprows):
     """
     if isinstance(skiprows, slice):
         return lrange(skiprows.start or 0, skiprows.stop, skiprows.step or 1)
-    elif isinstance(skiprows, numbers.Integral) or is_list_like(skiprows):
+    elif (isinstance(skiprows, numbers.Integral)
+          or is_list_like(skiprows, strict=False)):
         return skiprows
     elif skiprows is None:
         return 0
diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py
index a4f1155117b12..b3a2eee64b5dd 100755
--- a/pandas/io/parsers.py
+++ b/pandas/io/parsers.py
@@ -1225,7 +1225,7 @@ def _validate_usecols_arg(usecols):
         if callable(usecols):
             return usecols, None
         # GH20529, ensure is iterable container but not string.
-        elif not is_list_like(usecols):
+        elif not is_list_like(usecols, strict=False):
             raise ValueError(msg)
         else:
             usecols_dtype = lib.infer_dtype(usecols)
@@ -3157,7 +3157,7 @@ def _clean_na_values(na_values, keep_default_na=True):
         # where we append the default NaN values, provided
         # that `keep_default_na=True`.
         for k, v in compat.iteritems(old_na_values):
-            if not is_list_like(v):
+            if not is_list_like(v, strict=False):
                 v = [v]
 
             if keep_default_na:
@@ -3166,7 +3166,7 @@ def _clean_na_values(na_values, keep_default_na=True):
             na_values[k] = v
         na_fvalues = {k: _floatify_na_values(v) for k, v in na_values.items()}
     else:
-        if not is_list_like(na_values):
+        if not is_list_like(na_values, strict=False):
             na_values = [na_values]
         na_values = _stringify_na_values(na_values)
         if keep_default_na:
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index ff37036533b4f..3a03f020e9fe5 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -4758,7 +4758,7 @@ def __init__(self, table, where=None, start=None, stop=None, **kwargs):
         self.terms = None
         self.coordinates = None
 
-        if is_list_like(where):
+        if is_list_like(where, strict=False):
 
             # see if we have a passed coordinate like
             try:
diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index a582d32741ae9..54d2de1c90abe 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -748,7 +748,7 @@ def _create_table_setup(self):
                    for name, typ, is_index in column_names_and_types]
 
         if self.keys is not None:
-            if not is_list_like(self.keys):
+            if not is_list_like(self.keys, strict=False):
                 keys = [self.keys]
             else:
                 keys = self.keys
@@ -1289,7 +1289,7 @@ def _create_table_setup(self):
                             for cname, ctype, _ in column_names_and_types]
 
         if self.keys is not None and len(self.keys):
-            if not is_list_like(self.keys):
+            if not is_list_like(self.keys, strict=False):
                 keys = [self.keys]
             else:
                 keys = self.keys
diff --git a/pandas/tests/computation/test_eval.py b/pandas/tests/computation/test_eval.py
index eef8646e4d6d2..68c852d50c596 100644
--- a/pandas/tests/computation/test_eval.py
+++ b/pandas/tests/computation/test_eval.py
@@ -268,7 +268,7 @@ def check_operands(left, right, cmp_op):
 
     def check_simple_cmp_op(self, lhs, cmp1, rhs):
         ex = 'lhs {0} rhs'.format(cmp1)
-        if cmp1 in ('in', 'not in') and not is_list_like(rhs):
+        if cmp1 in ('in', 'not in') and not is_list_like(rhs, strict=False):
             pytest.raises(TypeError, pd.eval, ex, engine=self.engine,
                           parser=self.parser, local_dict={'lhs': lhs,
                                                           'rhs': rhs})
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 76cd6aabb93ae..7b866ff357ad9 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -67,17 +67,24 @@ def __getitem__(self):
     "ll",
     [
         [], [1], (1, ), (1, 2), {'a': 1},
-        {1, 'a'}, Series([1]),
+        Series([1]),
         Series([]), Series(['a']).str,
-        np.array([2])])
+        np.array([2])
+    ])
 def test_is_list_like_passes(ll):
-    assert inference.is_list_like(ll)
+    assert inference.is_list_like(ll, strict=False)
+
+
+def test_is_list_like_strict():
+    ll = {1, 'a'}
+    assert inference.is_list_like(ll, strict=False)
+    assert not inference.is_list_like(ll, strict=True)
 
 
 @pytest.mark.parametrize(
     "ll", [1, '2', object(), str, np.array(2)])
 def test_is_list_like_fails(ll):
-    assert not inference.is_list_like(ll)
+    assert not inference.is_list_like(ll, strict=False)
 
 
 def test_is_array_like():
@@ -106,7 +113,7 @@ class DtypeList(list):
 ])
 def test_is_nested_list_like_passes(inner, outer):
     result = outer([inner for _ in range(5)])
-    assert inference.is_list_like(result)
+    assert inference.is_list_like(result, strict=False)
 
 
 @pytest.mark.parametrize('obj', [
diff --git a/pandas/tests/extension/decimal/array.py b/pandas/tests/extension/decimal/array.py
index a1ee3a4fefef2..31a320b272ec0 100644
--- a/pandas/tests/extension/decimal/array.py
+++ b/pandas/tests/extension/decimal/array.py
@@ -104,7 +104,7 @@ def astype(self, dtype, copy=True):
         return super(DecimalArray, self).astype(dtype, copy)
 
     def __setitem__(self, key, value):
-        if pd.api.types.is_list_like(value):
+        if pd.api.types.is_list_like(value, strict=False):
             value = [decimal.Decimal(v) for v in value]
         else:
             value = decimal.Decimal(value)
diff --git a/pandas/tests/plotting/common.py b/pandas/tests/plotting/common.py
index 5c88926828fa6..b48f65e7a89d3 100644
--- a/pandas/tests/plotting/common.py
+++ b/pandas/tests/plotting/common.py
@@ -163,8 +163,8 @@ def _check_visible(self, collections, visible=True):
             expected visibility
         """
         from matplotlib.collections import Collection
-        if not isinstance(collections,
-                          Collection) and not is_list_like(collections):
+        if (not isinstance(collections, Collection)
+                and not is_list_like(collections, strict=False)):
             collections = [collections]
 
         for patch in collections:
@@ -251,7 +251,7 @@ def _check_text_labels(self, texts, expected):
         expected : str or list-like which has the same length as texts
             expected text label, or its list
         """
-        if not is_list_like(texts):
+        if not is_list_like(texts, strict=False):
             assert texts.get_text() == expected
         else:
             labels = [t.get_text() for t in texts]
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index cd297c356d60e..acd3070c9077d 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -2644,7 +2644,7 @@ def _check_errorbar_color(containers, expected, has_err='has_xerr'):
             errs = [c.lines
                     for c in ax.containers if getattr(c, has_err, False)][0]
             for el in errs:
-                if is_list_like(el):
+                if is_list_like(el, strict=False):
                     lines.extend(el)
                 else:
                     lines.append(el)

From 544b7ec510be34ad29fe0d204ff708b80a09e751 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Tue, 9 Oct 2018 23:38:13 +0200
Subject: [PATCH 02/17] Tiny fix

---
 pandas/core/dtypes/inference.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 2dd1e3f217ecf..50e830229b1e6 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -289,7 +289,7 @@ def is_list_like(obj, strict=None):
         # only raise warning if necessary
         warnings.warn('is_list_like will in the future return False for sets. '
                       'To keep the previous behavior, pass `strict=False`. To '
-                      'adapt the future behavior and silence this warning, '
+                      'adopt the future behavior and silence this warning, '
                       'pass `strict=True`', FutureWarning)
     strict = False if strict is None else strict
 

From ae9a45bf69cd234586ca8b18836ba98891408bc6 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 10 Oct 2018 01:19:42 +0200
Subject: [PATCH 03/17] Lint

---
 pandas/io/excel.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pandas/io/excel.py b/pandas/io/excel.py
index a538b567fbdc4..a864bd1da89f9 100644
--- a/pandas/io/excel.py
+++ b/pandas/io/excel.py
@@ -795,7 +795,8 @@ def _pop_header_name(row, index_col):
         return none_fill(row[0]), row[1:]
     else:
         # pop out header name and fill w/ blank
-        i = index_col if not is_list_like(index_col, strict=False) else max(index_col)
+        i = (index_col if not is_list_like(index_col, strict=False)
+             else max(index_col))
         return none_fill(row[i]), row[:i] + [''] + row[i + 1:]
 
 

From 15e3265524fa8a45331844d1dff9a2b6e989943b Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 10 Oct 2018 17:57:03 +0200
Subject: [PATCH 04/17] Review (jreback & jschendel)

---
 doc/source/whatsnew/v0.24.0.txt         |  1 -
 pandas/core/algorithms.py               |  6 +--
 pandas/core/apply.py                    |  2 +-
 pandas/core/arrays/base.py              |  3 +-
 pandas/core/arrays/categorical.py       | 10 ++---
 pandas/core/arrays/datetimelike.py      |  2 +-
 pandas/core/arrays/integer.py           |  4 +-
 pandas/core/arrays/timedeltas.py        |  2 +-
 pandas/core/base.py                     |  3 +-
 pandas/core/computation/ops.py          |  4 +-
 pandas/core/computation/pytables.py     |  5 +--
 pandas/core/dtypes/cast.py              |  6 +--
 pandas/core/dtypes/common.py            |  4 +-
 pandas/core/dtypes/inference.py         | 60 +++++++++++++++----------
 pandas/core/dtypes/missing.py           |  2 +-
 pandas/core/frame.py                    | 19 ++++----
 pandas/core/generic.py                  | 38 +++++++---------
 pandas/core/groupby/base.py             |  3 +-
 pandas/core/groupby/grouper.py          |  4 +-
 pandas/core/indexes/accessors.py        |  4 +-
 pandas/core/indexes/base.py             | 21 +++++----
 pandas/core/indexes/category.py         |  2 +-
 pandas/core/indexes/datetimelike.py     |  2 +-
 pandas/core/indexes/datetimes.py        |  2 +-
 pandas/core/indexes/interval.py         |  4 +-
 pandas/core/indexes/multi.py            | 36 +++++++--------
 pandas/core/indexes/timedeltas.py       |  5 +--
 pandas/core/indexing.py                 | 16 +++----
 pandas/core/internals/blocks.py         | 23 +++++-----
 pandas/core/ops.py                      |  5 +--
 pandas/core/panel.py                    |  4 +-
 pandas/core/reshape/melt.py             |  8 ++--
 pandas/core/reshape/merge.py            |  4 +-
 pandas/core/reshape/pivot.py            |  5 +--
 pandas/core/reshape/reshape.py          |  2 +-
 pandas/core/reshape/util.py             |  4 +-
 pandas/core/series.py                   | 23 +++++-----
 pandas/core/sorting.py                  |  4 +-
 pandas/core/sparse/array.py             |  2 +-
 pandas/core/strings.py                  | 10 ++---
 pandas/core/tools/datetimes.py          |  6 +--
 pandas/core/tools/timedeltas.py         |  2 +-
 pandas/core/util/hashing.py             |  2 +-
 pandas/core/window.py                   |  3 +-
 pandas/io/excel.py                      | 14 +++---
 pandas/io/formats/format.py             |  4 +-
 pandas/io/formats/style.py              |  2 +-
 pandas/io/html.py                       |  3 +-
 pandas/io/parsers.py                    |  6 +--
 pandas/io/pytables.py                   |  2 +-
 pandas/io/sql.py                        |  4 +-
 pandas/tests/computation/test_eval.py   |  2 +-
 pandas/tests/dtypes/test_inference.py   | 47 ++++++++++++-------
 pandas/tests/extension/decimal/array.py |  2 +-
 pandas/tests/plotting/common.py         |  6 +--
 pandas/tests/plotting/test_frame.py     |  2 +-
 56 files changed, 237 insertions(+), 234 deletions(-)

diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
index d93562ce4c0b9..40dd48880e0eb 100644
--- a/doc/source/whatsnew/v0.24.0.txt
+++ b/doc/source/whatsnew/v0.24.0.txt
@@ -629,7 +629,6 @@ Other API Changes
 - :class:`Index` subtraction will attempt to operate element-wise instead of raising ``TypeError`` (:issue:`19369`)
 - :class:`pandas.io.formats.style.Styler` supports a ``number-format`` property when using :meth:`~pandas.io.formats.style.Styler.to_excel` (:issue:`22015`)
 - :meth:`DataFrame.corr` and :meth:`Series.corr` now raise a ``ValueError`` along with a helpful error message instead of a ``KeyError`` when supplied with an invalid method (:issue:`22298`)
-- :meth:`dtypes.common.is_list_like` has gained a ``strict``-kwarg, which is ``False`` by default. If set to ``True``, sets are not considered list-like. (:issue:`22397`)
 - :meth:`shift` will now always return a copy, instead of the previous behaviour of returning self when shifting by 0 (:issue:`22397`)
 
 .. _whatsnew_0240.deprecations:
diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index f5e8ebe210863..e91cc8ec1e996 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -396,11 +396,11 @@ def isin(comps, values):
     boolean array same length as comps
     """
 
-    if not is_list_like(comps, strict=False):
+    if not is_list_like(comps):
         raise TypeError("only list-like objects are allowed to be passed"
                         " to isin(), you passed a [{comps_type}]"
                         .format(comps_type=type(comps).__name__))
-    if not is_list_like(values, strict=False):
+    if not is_list_like(values):
         raise TypeError("only list-like objects are allowed to be passed"
                         " to isin(), you passed a [{values_type}]"
                         .format(values_type=type(values).__name__))
@@ -1178,7 +1178,7 @@ class SelectNFrame(SelectN):
 
     def __init__(self, obj, n, keep, columns):
         super(SelectNFrame, self).__init__(obj, n, keep)
-        if not is_list_like(columns, strict=False):
+        if not is_list_like(columns):
             columns = [columns]
         columns = list(columns)
         self.columns = columns
diff --git a/pandas/core/apply.py b/pandas/core/apply.py
index 2b3fe0ef891f5..40cd952a62138 100644
--- a/pandas/core/apply.py
+++ b/pandas/core/apply.py
@@ -110,7 +110,7 @@ def get_result(self):
         """ compute the results """
 
         # dispatch to agg
-        if is_list_like(self.f, strict=False) or is_dict_like(self.f):
+        if is_list_like(self.f) or is_dict_like(self.f):
             return self.obj.aggregate(self.f, axis=self.axis,
                                       *self.args, **self.kwds)
 
diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index 53f72624e8d87..efe587c6aaaad 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -769,8 +769,7 @@ def _create_method(cls, op, coerce_to_dtype=True):
 
         def _binop(self, other):
             def convert_values(param):
-                if (isinstance(param, ExtensionArray)
-                        or is_list_like(param, strict=False)):
+                if isinstance(param, ExtensionArray) or is_list_like(param):
                     ovalues = param
                 else:  # Assume its an object
                     ovalues = [param] * len(self)
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 3d6034ba1c541..216bccf7d6309 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -1017,7 +1017,7 @@ def add_categories(self, new_categories, inplace=False):
         set_categories
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        if not is_list_like(new_categories, strict=False):
+        if not is_list_like(new_categories):
             new_categories = [new_categories]
         already_included = set(new_categories) & set(self.dtype.categories)
         if len(already_included) != 0:
@@ -1065,7 +1065,7 @@ def remove_categories(self, removals, inplace=False):
         set_categories
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        if not is_list_like(removals, strict=False):
+        if not is_list_like(removals):
             removals = [removals]
 
         removal_set = set(list(removals))
@@ -1981,7 +1981,7 @@ def __setitem__(self, key, value):
                 raise ValueError("Cannot set a Categorical with another, "
                                  "without identical categories")
 
-        rvalue = value if is_list_like(value, strict=False) else [value]
+        rvalue = value if is_list_like(value) else [value]
 
         from pandas import Index
         to_add = Index(rvalue).difference(self.categories)
@@ -2350,7 +2350,7 @@ def isin(self, values):
         array([ True, False,  True, False,  True, False])
         """
         from pandas.core.series import _sanitize_array
-        if not is_list_like(values, strict=False):
+        if not is_list_like(values):
             raise TypeError("only list-like objects are allowed to be passed"
                             " to isin(), you passed a [{values_type}]"
                             .format(values_type=type(values).__name__))
@@ -2523,7 +2523,7 @@ def _factorize_from_iterable(values):
     """
     from pandas.core.indexes.category import CategoricalIndex
 
-    if not is_list_like(values, strict=False):
+    if not is_list_like(values):
         raise TypeError("Input must be list-like")
 
     if is_categorical(values):
diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
index 0b0b24f410384..e4ace2bfe1509 100644
--- a/pandas/core/arrays/datetimelike.py
+++ b/pandas/core/arrays/datetimelike.py
@@ -751,7 +751,7 @@ def _evaluate_compare(self, other, op):
 
         if not isinstance(other, type(self)):
             # coerce to a similar object
-            if not is_list_like(other, strict=False):
+            if not is_list_like(other):
                 # scalar
                 other = [other]
             elif lib.is_scalar(lib.item_from_zerodim(other)):
diff --git a/pandas/core/arrays/integer.py b/pandas/core/arrays/integer.py
index a6f098f7a3c70..e58109a25e1a5 100644
--- a/pandas/core/arrays/integer.py
+++ b/pandas/core/arrays/integer.py
@@ -505,7 +505,7 @@ def cmp_method(self, other):
             mask = None
             if isinstance(other, IntegerArray):
                 other, mask = other._data, other._mask
-            elif is_list_like(other, strict=False):
+            elif is_list_like(other):
                 other = np.asarray(other)
                 if other.ndim > 0 and len(self) != len(other):
                     raise ValueError('Lengths must match to compare')
@@ -568,7 +568,7 @@ def integer_arithmetic_method(self, other):
             elif getattr(other, 'ndim', 0) > 1:
                 raise NotImplementedError(
                     "can only perform ops with 1-d structures")
-            elif is_list_like(other, strict=False):
+            elif is_list_like(other):
                 other = np.asarray(other)
                 if not other.ndim:
                     other = other.item()
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 25d6c7f4c10a6..df9e57cb5f0e1 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -76,7 +76,7 @@ def wrapper(self, other):
             if isna(other):
                 result.fill(nat_result)
 
-        elif not is_list_like(other, strict=False):
+        elif not is_list_like(other):
             raise TypeError(msg.format(cls=type(self).__name__,
                                        typ=type(other).__name__))
         else:
diff --git a/pandas/core/base.py b/pandas/core/base.py
index dc493cc71c3fd..00c049497c0d8 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -543,8 +543,7 @@ def is_any_frame():
                                 name=getattr(self, 'name', None))
 
             return result, True
-        elif (is_list_like(arg, strict=False)
-              and arg not in compat.string_types):
+        elif is_list_like(arg) and arg not in compat.string_types:
             # we require a list, but not an 'str'
             return self._aggregate_multiple_funcs(arg,
                                                   _level=_level,
diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
index 4c16d59d7c44d..ca0c4db4947c4 100644
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -234,7 +234,7 @@ def _in(x, y):
     try:
         return x.isin(y)
     except AttributeError:
-        if is_list_like(x, strict=False):
+        if is_list_like(x):
             try:
                 return y.isin(x)
             except AttributeError:
@@ -249,7 +249,7 @@ def _not_in(x, y):
     try:
         return ~x.isin(y)
     except AttributeError:
-        if is_list_like(x, strict=False):
+        if is_list_like(x):
             try:
                 return ~y.isin(x)
             except AttributeError:
diff --git a/pandas/core/computation/pytables.py b/pandas/core/computation/pytables.py
index a7ae037b24f38..e08df3e340138 100644
--- a/pandas/core/computation/pytables.py
+++ b/pandas/core/computation/pytables.py
@@ -127,7 +127,7 @@ def pr(left, right):
 
     def conform(self, rhs):
         """ inplace conform rhs """
-        if not is_list_like(rhs, strict=False):
+        if not is_list_like(rhs):
             rhs = [rhs]
         if isinstance(rhs, np.ndarray):
             rhs = rhs.ravel()
@@ -472,8 +472,7 @@ def _validate_where(w):
     TypeError : An invalid data type was passed in for w (e.g. dict).
     """
 
-    if not (isinstance(w, (Expr, string_types))
-            or is_list_like(w, strict=False)):
+    if not (isinstance(w, (Expr, string_types)) or is_list_like(w)):
         raise TypeError("where must be passed as a string, Expr, "
                         "or list-like of Exprs")
 
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 5cde4c4fdc69a..a95a45d5f9ae4 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -472,7 +472,7 @@ def infer_dtype_from_array(arr, pandas_dtype=False):
     if isinstance(arr, np.ndarray):
         return arr.dtype, arr
 
-    if not is_list_like(arr, strict=False):
+    if not is_list_like(arr):
         arr = [arr]
 
     if pandas_dtype and is_extension_type(arr):
@@ -518,7 +518,7 @@ def maybe_infer_dtype_type(element):
     tipo = None
     if hasattr(element, 'dtype'):
         tipo = element.dtype
-    elif is_list_like(element, strict=False):
+    elif is_list_like(element):
         element = np.asarray(element)
         tipo = element.dtype
     return tipo
@@ -914,7 +914,7 @@ def maybe_infer_to_datetimelike(value, convert_dates=False):
 
     v = value
 
-    if not is_list_like(v, strict=False):
+    if not is_list_like(v):
         v = [v]
     v = np.array(v, copy=False)
 
diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index 227a0b457bcdd..a9fc9d13d4ab3 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -327,8 +327,8 @@ def is_offsetlike(arr_or_obj):
     """
     if isinstance(arr_or_obj, ABCDateOffset):
         return True
-    elif (is_list_like(arr_or_obj, strict=False) and len(arr_or_obj)
-          and is_object_dtype(arr_or_obj)):
+    elif (is_list_like(arr_or_obj) and len(arr_or_obj) and
+          is_object_dtype(arr_or_obj)):
         return all(isinstance(x, ABCDateOffset) for x in arr_or_obj)
     return False
 
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 50e830229b1e6..9df7a78c1c3b2 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -4,10 +4,10 @@
 import numpy as np
 from numbers import Number
 from pandas import compat
-from pandas.compat import (PY2, string_types, text_type,
+from pandas.compat import (PY2, PY36, string_types, text_type,
                            string_and_binary_types, re_type)
 from pandas._libs import lib
-import warnings
+from collections import abc, OrderedDict
 
 is_bool = lib.is_bool
 
@@ -248,7 +248,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj, strict=None):
+def is_list_like(obj):
     """
     Check if the object is list-like.
 
@@ -260,8 +260,6 @@ def is_list_like(obj, strict=None):
     Parameters
     ----------
     obj : The object to check.
-    strict : boolean, default None
-        Whether `set` should be counted as list-like
 
     Returns
     -------
@@ -285,21 +283,38 @@ def is_list_like(obj, strict=None):
     >>> is_list_like(np.array(2)))
     False
     """
-    if strict is None and isinstance(obj, set):
-        # only raise warning if necessary
-        warnings.warn('is_list_like will in the future return False for sets. '
-                      'To keep the previous behavior, pass `strict=False`. To '
-                      'adopt the future behavior and silence this warning, '
-                      'pass `strict=True`', FutureWarning)
-    strict = False if strict is None else strict
-
-    list_like = (isinstance(obj, compat.Iterable)
-                 # we do not count strings/unicode/bytes as set-like
-                 and not isinstance(obj, string_and_binary_types)
-                 # exclude zero-dimensional numpy arrays, effectively scalars
-                 and not (isinstance(obj, np.ndarray) and obj.ndim == 0))
-    return list_like and (not strict or not isinstance(obj, set))
 
+    return (isinstance(obj, compat.Iterable) and
+            # we do not count strings/unicode/bytes as list-like
+            not isinstance(obj, string_and_binary_types) and
+            # exclude zero-dimensional numpy arrays, effectively scalars
+            not (isinstance(obj, np.ndarray) and obj.ndim == 0))
+
+
+def is_ordered_list_like(obj):
+    """
+    Check if the object is list-like and has a defined order
+
+    Works like :meth:`is_list_like` but excludes sets (as well as unordered
+    `dict` before Python 3.6)
+
+    Note that iterators can not be inspected for order - this check will return
+    True but it is up to the user to make sure that their iterators are
+    generated in an ordered way.
+
+    Parameters
+    ----------
+    obj : The object to check.
+
+    Returns
+    -------
+    is_ordered_list_like : bool
+        Whether `obj` is an ordered list-like
+    """
+    list_like = is_list_like(obj)
+    unordered_dict = not PY36 and (isinstance(obj, dict)
+                                   and not isinstance(obj, OrderedDict))
+    return list_like and not unordered_dict and not isinstance(obj, abc.Set)
 
 def is_array_like(obj):
     """
@@ -331,7 +346,7 @@ def is_array_like(obj):
     False
     """
 
-    return is_list_like(obj, strict=False) and hasattr(obj, "dtype")
+    return is_list_like(obj) and hasattr(obj, "dtype")
 
 
 def is_nested_list_like(obj):
@@ -374,9 +389,8 @@ def is_nested_list_like(obj):
     --------
     is_list_like
     """
-    return (is_list_like(obj, strict=False) and hasattr(obj, '__len__')
-            and len(obj) > 0 and all(is_list_like(item, strict=False)
-                                     for item in obj))
+    return (is_list_like(obj) and hasattr(obj, '__len__') and
+            len(obj) > 0 and all(is_list_like(item) for item in obj))
 
 
 def is_dict_like(obj):
diff --git a/pandas/core/dtypes/missing.py b/pandas/core/dtypes/missing.py
index b04bae77faf1a..66998aa6866f6 100644
--- a/pandas/core/dtypes/missing.py
+++ b/pandas/core/dtypes/missing.py
@@ -464,7 +464,7 @@ def _infer_fill_value(val):
     element to provide proper block construction
     """
 
-    if not is_list_like(val, strict=False):
+    if not is_list_like(val):
         val = [val]
     val = np.array(val, copy=False)
     if is_datetimelike(val):
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 8f1082fb16f80..35c476f3539ee 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -421,8 +421,7 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,
             if not isinstance(data, compat.Sequence):
                 data = list(data)
             if len(data) > 0:
-                if (is_list_like(data[0], strict=False)
-                        and getattr(data[0], 'ndim', 1) == 1):
+                if is_list_like(data[0]) and getattr(data[0], 'ndim', 1) == 1:
                     if is_named_tuple(data[0]) and columns is None:
                         columns = data[0]._fields
                     arrays, columns = _to_arrays(data, columns, dtype=dtype)
@@ -2791,8 +2790,7 @@ def __getitem__(self, key):
 
         # We are left with two options: a single key, and a collection of keys,
         # We interpret tuples as collections only for non-MultiIndex
-        is_single_key = (isinstance(key, tuple)
-                         or not is_list_like(key, strict=False))
+        is_single_key = isinstance(key, tuple) or not is_list_like(key)
 
         if is_single_key:
             if self.columns.nlevels > 1:
@@ -3154,9 +3152,9 @@ def select_dtypes(self, include=None, exclude=None):
         5  False  2.0
         """
 
-        if not is_list_like(include, strict=False):
+        if not is_list_like(include):
             include = (include,) if include is not None else ()
-        if not is_list_like(exclude, strict=False):
+        if not is_list_like(exclude):
             exclude = (exclude,) if exclude is not None else ()
 
         selection = tuple(map(frozenset, (include, exclude)))
@@ -3281,7 +3279,7 @@ def _ensure_valid_index(self, value):
         passed value
         """
         # GH5632, make sure that we are a Series convertible
-        if not len(self.index) and is_list_like(value, strict=False):
+        if not len(self.index) and is_list_like(value):
             try:
                 value = Series(value)
             except (ValueError, NotImplementedError, TypeError):
@@ -7663,7 +7661,7 @@ def isin(self, values):
                                  "a duplicate axis.")
             return self.eq(values.reindex_like(self))
         else:
-            if not is_list_like(values, strict=False):
+            if not is_list_like(values):
                 raise TypeError("only list-like or dict-like objects are "
                                 "allowed to be passed to DataFrame.isin(), "
                                 "you passed a "
@@ -7733,7 +7731,7 @@ def extract_index(data):
             elif isinstance(v, dict):
                 have_dicts = True
                 indexes.append(list(v.keys()))
-            elif is_list_like(v, strict=False) and getattr(v, 'ndim', 1) == 1:
+            elif is_list_like(v) and getattr(v, 'ndim', 1) == 1:
                 have_raw_arrays = True
                 raw_lengths.append(len(v))
 
@@ -7776,8 +7774,7 @@ def convert(v):
         # this is equiv of np.asarray, but does object conversion
         # and platform dtype preservation
         try:
-            if (is_list_like(values[0], strict=False)
-                    or hasattr(values[0], 'len')):
+            if is_list_like(values[0]) or hasattr(values[0], 'len'):
                 values = np.array([convert(v) for v in values])
             elif isinstance(values[0], np.ndarray) and values[0].ndim == 0:
                 # GH#21861
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index caf9ea028df2e..bb82c531b698e 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -1179,8 +1179,8 @@ def rename_axis(self, mapper, axis=0, copy=True, inplace=False):
         2    3  6
         """
         inplace = validate_bool_kwarg(inplace, 'inplace')
-        non_mapper = is_scalar(mapper) or (is_list_like(mapper, strict=False)
-                                           and not is_dict_like(mapper))
+        non_mapper = is_scalar(mapper) or (is_list_like(mapper) and not
+                                           is_dict_like(mapper))
         if non_mapper:
             return self._set_axis_name(mapper, axis=axis, inplace=inplace)
         else:
@@ -3263,7 +3263,7 @@ def xs(self, key, axis=0, level=None, drop_level=True):
             # if we encounter an array-like and we only have 1 dim
             # that means that their are list/ndarrays inside the Series!
             # so just return them (GH 6394)
-            if not is_list_like(new_values, strict=False) or self.ndim == 1:
+            if not is_list_like(new_values) or self.ndim == 1:
                 return com.maybe_box_datetimelike(new_values)
 
             result = self._constructor_sliced(
@@ -4674,8 +4674,7 @@ def __setattr__(self, name, value):
                 else:
                     object.__setattr__(self, name, value)
             except (AttributeError, TypeError):
-                if (isinstance(self, ABCDataFrame)
-                        and is_list_like(value, strict=False)):
+                if isinstance(self, ABCDataFrame) and (is_list_like(value)):
                     warnings.warn("Pandas doesn't allow columns to be "
                                   "created via a new attribute name - see "
                                   "https://pandas.pydata.org/pandas-docs/"
@@ -5670,7 +5669,7 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
                 if isinstance(value, (dict, ABCSeries)):
                     from pandas import Series
                     value = Series(value)
-                elif not is_list_like(value, strict=False):
+                elif not is_list_like(value):
                     pass
                 else:
                     raise TypeError('"value" parameter must be a scalar, dict '
@@ -5695,7 +5694,7 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
                     obj.fillna(v, limit=limit, inplace=True, downcast=downcast)
                 return result if not inplace else None
 
-            elif not is_list_like(value, strict=False):
+            elif not is_list_like(value):
                 new_data = self._data.fillna(value=value, limit=limit,
                                              inplace=inplace,
                                              downcast=downcast)
@@ -6096,7 +6095,7 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                     return None if inplace else res
 
                 # {'A': NA} -> 0
-                elif not is_list_like(value, strict=False):
+                elif not is_list_like(value):
                     keys = [(k, src) for k, src in compat.iteritems(to_replace)
                             if k in self]
                     keys_len = len(keys) - 1
@@ -6112,9 +6111,8 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                     raise TypeError('value argument must be scalar, dict, or '
                                     'Series')
 
-            elif is_list_like(to_replace, strict=False):
-                # [NA, ''] -> [0, 'missing']
-                if is_list_like(value, strict=False):
+            elif is_list_like(to_replace):  # [NA, ''] -> [0, 'missing']
+                if is_list_like(value):
                     if len(to_replace) != len(value):
                         raise ValueError('Replacement lists must match '
                                          'in length. Expecting %d got %d ' %
@@ -6130,9 +6128,8 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                                                   value=value, inplace=inplace,
                                                   regex=regex)
             elif to_replace is None:
-                if not (is_re_compilable(regex)
-                        or is_list_like(regex, strict=False)
-                        or is_dict_like(regex)):
+                if not (is_re_compilable(regex) or
+                        is_list_like(regex) or is_dict_like(regex)):
                     raise TypeError("'regex' must be a string or a compiled "
                                     "regular expression or a list or dict of "
                                     "strings or regular expressions, you "
@@ -6153,7 +6150,7 @@ def replace(self, to_replace=None, value=None, inplace=False, limit=None,
                                                         inplace=inplace,
                                                         regex=regex)
 
-                elif not is_list_like(value, strict=False):  # NA -> 0
+                elif not is_list_like(value):  # NA -> 0
                     new_data = self._data.replace(to_replace=to_replace,
                                                   value=value, inplace=inplace,
                                                   regex=regex)
@@ -6480,10 +6477,10 @@ def asof(self, where, subset=None):
         else:
             if subset is None:
                 subset = self.columns
-            if not is_list_like(subset, strict=False):
+            if not is_list_like(subset):
                 subset = [subset]
 
-        is_list = is_list_like(where, strict=False)
+        is_list = is_list_like(where)
         if not is_list:
             start = self.index[0]
             if isinstance(self.index, PeriodIndex):
@@ -6715,8 +6712,7 @@ def _clip_with_one_bound(self, threshold, method, axis, inplace):
         # GH #15390
         # In order for where method to work, the threshold must
         # be transformed to NDFrame from other array like structure.
-        if (not isinstance(threshold, ABCSeries)
-                and is_list_like(threshold, strict=False)):
+        if (not isinstance(threshold, ABCSeries)) and is_list_like(threshold):
             if isinstance(self, ABCSeries):
                 threshold = pd.Series(threshold, index=self.index)
             else:
@@ -6817,9 +6813,9 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         # so ignore
         # GH 19992
         # numpy doesn't drop a list-like bound containing NaN
-        if not is_list_like(lower, strict=False) and np.any(pd.isnull(lower)):
+        if not is_list_like(lower) and np.any(pd.isnull(lower)):
             lower = None
-        if not is_list_like(upper, strict=False) and np.any(pd.isnull(upper)):
+        if not is_list_like(upper) and np.any(pd.isnull(upper)):
             upper = None
 
         # GH 2747 (arguments were reversed)
diff --git a/pandas/core/groupby/base.py b/pandas/core/groupby/base.py
index 228e2434ebb2c..ac84971de08d8 100644
--- a/pandas/core/groupby/base.py
+++ b/pandas/core/groupby/base.py
@@ -57,8 +57,7 @@ def _gotitem(self, key, ndim, subset=None):
                               **kwargs)
         self._reset_cache()
         if subset.ndim == 2:
-            if (is_scalar(key) and key in subset
-                    or is_list_like(key, strict=False)):
+            if is_scalar(key) and key in subset or is_list_like(key):
                 self._selection = key
         return self
 
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index d23acea6f168e..e7144fb1d2932 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -440,7 +440,7 @@ def _get_grouper(obj, key=None, axis=0, level=None, sort=True,
         # on the outside of this condition.
         # (GH 17621)
         if isinstance(group_axis, MultiIndex):
-            if is_list_like(level, strict=False) and len(level) == 1:
+            if is_list_like(level) and len(level) == 1:
                 level = level[0]
 
             if key is None and is_scalar(level):
@@ -452,7 +452,7 @@ def _get_grouper(obj, key=None, axis=0, level=None, sort=True,
             # allow level to be a length-one list-like object
             # (e.g., level=[0])
             # GH 13901
-            if is_list_like(level, strict=False):
+            if is_list_like(level):
                 nlevels = len(level)
                 if nlevels == 1:
                     level = level[0]
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index 594770294a3cd..a1868980faed3 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -63,7 +63,7 @@ def _delegate_property_get(self, name):
         if isinstance(result, np.ndarray):
             if is_integer_dtype(result):
                 result = result.astype('int64')
-        elif not is_list_like(result, strict=False):
+        elif not is_list_like(result):
             return result
 
         result = np.asarray(result)
@@ -97,7 +97,7 @@ def _delegate_method(self, name, *args, **kwargs):
         method = getattr(values, name)
         result = method(*args, **kwargs)
 
-        if not is_list_like(result, strict=False):
+        if not is_list_like(result):
             return result
 
         result = Series(result, index=self.index, name=self.name)
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 4fb92ca6fb266..51c84d6e28cb4 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -445,7 +445,7 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
         elif data is None or is_scalar(data):
             cls._scalar_data_error(data)
         else:
-            if tupleize_cols and is_list_like(data, strict=False):
+            if tupleize_cols and is_list_like(data):
                 # GH21470: convert iterable to list before determining if empty
                 if is_iterator(data):
                     data = list(data)
@@ -1020,11 +1020,11 @@ def _validate_names(self, name=None, names=None, deep=False):
         elif names is None and name is None:
             return deepcopy(self.names) if deep else self.names
         elif names is not None:
-            if not is_list_like(names, strict=False):
+            if not is_list_like(names):
                 raise TypeError("Must pass list-like as `names`.")
             return names
         else:
-            if not is_list_like(name, strict=False):
+            if not is_list_like(name):
                 return [name]
             return name
 
@@ -1222,7 +1222,7 @@ def _to_safe_for_reshape(self):
         return self
 
     def _assert_can_do_setop(self, other):
-        if not is_list_like(other, strict=False):
+        if not is_list_like(other):
             raise TypeError('Input must be Index or array-like')
         return True
 
@@ -1267,7 +1267,7 @@ def _set_names(self, values, level=None):
         ------
         TypeError if each name is not hashable.
         """
-        if not is_list_like(values, strict=False):
+        if not is_list_like(values):
             raise ValueError('Names must be a list-like')
         if len(values) != 1:
             raise ValueError('Length of new names must be 1, got %d' %
@@ -1337,18 +1337,17 @@ def set_names(self, names, level=None, inplace=False):
         if level is not None and not isinstance(self, MultiIndex):
             raise ValueError('Level must be None for non-MultiIndex')
 
-        if (level is not None and not is_list_like(level, strict=False)
-                and is_list_like(names, strict=False)):
+        if level is not None and not is_list_like(level) and is_list_like(
+                names):
             msg = "Names must be a string when a single level is provided."
             raise TypeError(msg)
 
-        if (not is_list_like(names, strict=False)
-                and level is None and self.nlevels > 1):
+        if not is_list_like(names) and level is None and self.nlevels > 1:
             raise TypeError("Must pass list-like as `names`.")
 
-        if not is_list_like(names, strict=False):
+        if not is_list_like(names):
             names = [names]
-        if level is not None and not is_list_like(level, strict=False):
+        if level is not None and not is_list_like(level):
             level = [level]
 
         if inplace:
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 4d2aaaa3ddaad..45703c220a4be 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -244,7 +244,7 @@ def _is_dtype_compat(self, other):
                                 "when appending")
         else:
             values = other
-            if not is_list_like(values, strict=False):
+            if not is_list_like(values):
                 values = [values]
             other = CategoricalIndex(self._create_categorical(
                 other, dtype=self.dtype))
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index ed896e55270b6..1ec30ecbb3a3b 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -322,7 +322,7 @@ def __contains__(self, key):
         try:
             res = self.get_loc(key)
             return (is_scalar(res) or isinstance(res, slice) or
-                    (is_list_like(res, strict=False) and len(res)))
+                    (is_list_like(res) and len(res)))
         except (KeyError, TypeError, ValueError):
             return False
 
diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
index 616f5336a7899..e40ceadc1a083 100644
--- a/pandas/core/indexes/datetimes.py
+++ b/pandas/core/indexes/datetimes.py
@@ -1396,7 +1396,7 @@ def delete(self, loc):
             if loc in (0, -len(self), -1, len(self) - 1):
                 freq = self.freq
         else:
-            if is_list_like(loc, strict=False):
+            if is_list_like(loc):
                 loc = lib.maybe_indices_to_slice(
                     ensure_int64(np.array(loc)), len(self))
             if isinstance(loc, slice) and loc.step in (1, None):
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index b9760f3b8d683..25d4dd0cbcc81 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -560,7 +560,7 @@ def _maybe_convert_i8(self, key):
             Int64Index if converted list-like.
         """
         original = key
-        if is_list_like(key, strict=False):
+        if is_list_like(key):
             key = ensure_index(key)
 
         if not self._needs_i8_conversion(key):
@@ -734,7 +734,7 @@ def get_loc(self, key, method=None):
     def get_value(self, series, key):
         if com.is_bool_indexer(key):
             loc = key
-        elif is_list_like(key, strict=False):
+        elif is_list_like(key):
             loc = self.get_indexer(key)
         elif isinstance(key, slice):
 
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 367f25b21889d..3cccb65503378 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -389,16 +389,15 @@ def set_levels(self, levels, level=None, inplace=False,
                    labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
                    names=[u'foo', u'bar'])
         """
-        if level is not None and not is_list_like(level, strict=False):
-            if not is_list_like(levels, strict=False):
+        if level is not None and not is_list_like(level):
+            if not is_list_like(levels):
                 raise TypeError("Levels must be list-like")
-            if is_list_like(levels[0], strict=False):
+            if is_list_like(levels[0]):
                 raise TypeError("Levels must be list-like")
             level = [level]
             levels = [levels]
-        elif level is None or is_list_like(level, strict=False):
-            if (not is_list_like(levels, strict=False)
-                    or not is_list_like(levels[0], strict=False)):
+        elif level is None or is_list_like(level):
+            if not is_list_like(levels) or not is_list_like(levels[0]):
                 raise TypeError("Levels must be list of lists-like")
 
         if inplace:
@@ -486,16 +485,15 @@ def set_labels(self, labels, level=None, inplace=False,
                    labels=[[1, 0, 1, 0], [0, 0, 1, 1]],
                    names=[u'foo', u'bar'])
         """
-        if level is not None and not is_list_like(level, strict=False):
-            if not is_list_like(labels, strict=False):
+        if level is not None and not is_list_like(level):
+            if not is_list_like(labels):
                 raise TypeError("Labels must be list-like")
-            if is_list_like(labels[0], strict=False):
+            if is_list_like(labels[0]):
                 raise TypeError("Labels must be list-like")
             level = [level]
             labels = [labels]
-        elif level is None or is_list_like(level, strict=False):
-            if (not is_list_like(labels, strict=False)
-                    or not is_list_like(labels[0], strict=False)):
+        elif level is None or is_list_like(level):
+            if not is_list_like(labels) or not is_list_like(labels[0]):
                 raise TypeError("Labels must be list of lists-like")
 
         if inplace:
@@ -687,7 +685,7 @@ def _set_names(self, names, level=None, validate=True):
         """
         # GH 15110
         # Don't allow a single string for names in a MultiIndex
-        if names is not None and not is_list_like(names, strict=False):
+        if names is not None and not is_list_like(names):
             raise ValueError('Names should be list-like for a MultiIndex')
         names = list(names)
 
@@ -1180,7 +1178,7 @@ def to_frame(self, index=True, name=None):
 
         from pandas import DataFrame
         if name is not None:
-            if not is_list_like(name, strict=False):
+            if not is_list_like(name):
                 raise TypeError("'name' must be a list / sequence "
                                 "of column names.")
 
@@ -1297,7 +1295,7 @@ def from_arrays(cls, arrays, sortorder=None, names=None):
         MultiIndex.from_product : Make a MultiIndex from cartesian product
                                   of iterables
         """
-        if not is_list_like(arrays, strict=False):
+        if not is_list_like(arrays):
             raise TypeError("Input must be a list / sequence of array-likes.")
         elif is_iterator(arrays):
             arrays = list(arrays)
@@ -1346,7 +1344,7 @@ def from_tuples(cls, tuples, sortorder=None, names=None):
         MultiIndex.from_product : Make a MultiIndex from cartesian product
                                   of iterables
         """
-        if not is_list_like(tuples, strict=False):
+        if not is_list_like(tuples):
             raise TypeError('Input must be a list / sequence of tuple-likes.')
         elif is_iterator(tuples):
             tuples = list(tuples)
@@ -1405,7 +1403,7 @@ def from_product(cls, iterables, sortorder=None, names=None):
         from pandas.core.arrays.categorical import _factorize_from_iterables
         from pandas.core.reshape.util import cartesian_product
 
-        if not is_list_like(iterables, strict=False):
+        if not is_list_like(iterables):
             raise TypeError("Input must be a list / sequence of iterables.")
         elif is_iterator(iterables):
             iterables = list(iterables)
@@ -1978,7 +1976,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
         target = ensure_index(target)
 
         # empty indexer
-        if is_list_like(target, strict=False) and not len(target):
+        if is_list_like(target) and not len(target):
             return ensure_platform_int(np.array([]))
 
         if not isinstance(target, MultiIndex):
@@ -2576,7 +2574,7 @@ def _update_indexer(idxr, indexer=indexer):
                 indexer = _update_indexer(_convert_to_indexer(k),
                                           indexer=indexer)
 
-            elif is_list_like(k, strict=False):
+            elif is_list_like(k):
                 # a collection of labels to include from this level (these
                 # are or'd)
                 indexers = None
diff --git a/pandas/core/indexes/timedeltas.py b/pandas/core/indexes/timedeltas.py
index a0a683106bef2..ee604f44b98e0 100644
--- a/pandas/core/indexes/timedeltas.py
+++ b/pandas/core/indexes/timedeltas.py
@@ -488,8 +488,7 @@ def get_loc(self, key, method=None, tolerance=None):
         -------
         loc : int
         """
-        if (is_list_like(key, strict=False)
-                or (isinstance(key, datetime) and key is not NaT)):
+        if is_list_like(key) or (isinstance(key, datetime) and key is not NaT):
             # GH#20464 datetime check here is to ensure we don't allow
             #   datetime objects to be incorrectly treated as timedelta
             #   objects; NaT is a special case because it plays a double role
@@ -699,7 +698,7 @@ def delete(self, loc):
             if loc in (0, -len(self), -1, len(self) - 1):
                 freq = self.freq
         else:
-            if is_list_like(loc, strict=False):
+            if is_list_like(loc):
                 loc = lib.maybe_indices_to_slice(
                     ensure_int64(np.array(loc)), len(self))
             if isinstance(loc, slice) and loc.step in (1, None):
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 39cf27e388ce1..b3c913f21dd86 100755
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -2528,7 +2528,7 @@ def check_setitem_lengths(indexer, value, values):
     """
     # boolean with truth values == len of the value is ok too
     if isinstance(indexer, (np.ndarray, list)):
-        if is_list_like(value, strict=False) and len(indexer) != len(value):
+        if is_list_like(value) and len(indexer) != len(value):
             if not (isinstance(indexer, np.ndarray) and
                     indexer.dtype == np.bool_ and
                     len(indexer[indexer]) == len(value)):
@@ -2537,7 +2537,7 @@ def check_setitem_lengths(indexer, value, values):
     # slice
     elif isinstance(indexer, slice):
 
-        if is_list_like(value, strict=False) and len(values):
+        if is_list_like(value) and len(values):
             if len(value) != length_of_indexer(indexer, values):
                 raise ValueError("cannot set using a slice indexer with a "
                                  "different length than the value")
@@ -2677,16 +2677,16 @@ def is_nested_tuple(tup, labels):
 
     for i, k in enumerate(tup):
 
-        if is_list_like(k, strict=False) or isinstance(k, slice):
+        if is_list_like(k) or isinstance(k, slice):
             return isinstance(labels, MultiIndex)
 
     return False
 
 
 def is_list_like_indexer(key):
-    # allow a list-like, but exclude NamedTuples which can be indexers
-    return (is_list_like(key, strict=False)
-            and not (isinstance(key, tuple) and type(key) is not tuple))
+    # allow a list_like, but exclude NamedTuples which can be indexers
+    return is_list_like(key) and not (isinstance(key, tuple) and
+                                      type(key) is not tuple)
 
 
 def is_label_like(key):
@@ -2734,9 +2734,9 @@ def _non_reducing_slice(slice_):
 
     def pred(part):
         # true when slice does *not* reduce
-        return isinstance(part, slice) or is_list_like(part, strict=False)
+        return isinstance(part, slice) or is_list_like(part)
 
-    if not is_list_like(slice_, strict=False):
+    if not is_list_like(slice_):
         if not isinstance(slice_, slice):
             # a 1-d slice, like df.loc[1]
             slice_ = [[slice_]]
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index b39544d8b9c09..93930fd844b95 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -910,7 +910,7 @@ def _is_scalar_indexer(indexer):
         def _is_empty_indexer(indexer):
             # return a boolean if we have an empty indexer
 
-            if is_list_like(indexer, strict=False) and not len(indexer):
+            if is_list_like(indexer) and not len(indexer):
                 return True
             if arr_value.ndim == 1:
                 if not isinstance(indexer, tuple):
@@ -978,8 +978,7 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
         mask = getattr(mask, 'values', mask)
 
         # if we are passed a scalar None, convert it here
-        if (not is_list_like(new, strict=False)
-                and isna(new) and not self.is_object):
+        if not is_list_like(new) and isna(new) and not self.is_object:
             new = self.fill_value
 
         if self._can_hold_element(new):
@@ -1003,7 +1002,7 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
             #
             # TODO: this prob needs some better checking
             # for 2D cases
-            if ((is_list_like(new, strict=False) and
+            if ((is_list_like(new) and
                  np.any(mask[mask]) and
                  getattr(new, 'ndim', 1) == 1)):
 
@@ -1379,8 +1378,7 @@ def get_result(other):
 
             # avoid numpy warning of elementwise comparisons
             elif func.__name__ == 'eq':
-                if (is_list_like(other, strict=False)
-                        and not isinstance(other, np.ndarray)):
+                if is_list_like(other) and not isinstance(other, np.ndarray):
                     other = np.asarray(other)
 
                     # if we can broadcast, then ok
@@ -1436,8 +1434,7 @@ def handle_error():
 
                 # differentiate between an invalid ndarray-ndarray comparison
                 # and an invalid type comparison
-                if (isinstance(values, np.ndarray)
-                        and is_list_like(other, strict=False)):
+                if isinstance(values, np.ndarray) and is_list_like(other):
                     raise ValueError(
                         'Invalid broadcasting comparison [{other!r}] with '
                         'block values'.format(other=other))
@@ -1651,7 +1648,7 @@ def _nanpercentile(values, q, axis, **kw):
 
         from pandas import Float64Index
         is_empty = values.shape[axis] == 0
-        if is_list_like(qs, strict=False):
+        if is_list_like(qs):
             ax = Float64Index(qs)
 
             if is_empty:
@@ -2487,8 +2484,8 @@ def should_store(self, value):
 
     def replace(self, to_replace, value, inplace=False, filter=None,
                 regex=False, convert=True, mgr=None):
-        to_rep_is_list = is_list_like(to_replace, strict=False)
-        value_is_list = is_list_like(value, strict=False)
+        to_rep_is_list = is_list_like(to_replace)
+        value_is_list = is_list_like(value)
         both_lists = to_rep_is_list and value_is_list
         either_list = to_rep_is_list or value_is_list
 
@@ -3476,7 +3473,7 @@ def _putmask_smart(v, m, n):
     # that numpy does when numeric are mixed with strings
 
     # n should be the length of the mask or a scalar here
-    if not is_list_like(n, strict=False):
+    if not is_list_like(n):
         n = np.repeat(n, len(m))
     elif isinstance(n, np.ndarray) and n.ndim == 0:  # numpy scalar
         n = np.repeat(np.array(n, ndmin=1), len(m))
@@ -3508,7 +3505,7 @@ def _putmask_smart(v, m, n):
              is_integer_dtype(nn_at.dtype))):
 
             comp = (nn == nn_at)
-            if is_list_like(comp, strict=False) and comp.all():
+            if is_list_like(comp) and comp.all():
                 nv = v.copy()
                 nv[m] = nn_at
                 return nv
diff --git a/pandas/core/ops.py b/pandas/core/ops.py
index 2967b38abda53..20559bca9caed 100644
--- a/pandas/core/ops.py
+++ b/pandas/core/ops.py
@@ -1613,8 +1613,7 @@ def wrapper(self, other):
         else:
             # scalars, list, tuple, np.array
             is_other_int_dtype = is_integer_dtype(np.asarray(other))
-            if (is_list_like(other, strict=False)
-                    and not isinstance(other, np.ndarray)):
+            if is_list_like(other) and not isinstance(other, np.ndarray):
                 # TODO: Can we do this before the is_integer_dtype check?
                 # could the is_integer_dtype check be checking the wrong
                 # thing?  e.g. other = [[0, 1], [2, 3], [4, 5]]?
@@ -1830,7 +1829,7 @@ def to_series(right):
             raise ValueError('Unable to coerce to Series/DataFrame, dim '
                              'must be <= 2: {dim}'.format(dim=right.shape))
 
-    elif (is_list_like(right, strict=False) and
+    elif (is_list_like(right) and
           not isinstance(right, (ABCSeries, ABCDataFrame))):
         # GH17901
         right = to_series(right)
diff --git a/pandas/core/panel.py b/pandas/core/panel.py
index b8b672d8d6009..1e2d4000413bb 100644
--- a/pandas/core/panel.py
+++ b/pandas/core/panel.py
@@ -286,7 +286,7 @@ def __getitem__(self, key):
 
         if isinstance(self._info_axis, MultiIndex):
             return self._getitem_multilevel(key)
-        if not (is_list_like(key, strict=False) or isinstance(key, slice)):
+        if not (is_list_like(key) or isinstance(key, slice)):
             return super(Panel, self).__getitem__(key)
         return self.loc[key]
 
@@ -884,7 +884,7 @@ def _ixs(self, i, axis=0):
         # if we have a multi-index and a single tuple, then its a reduction
         # (GH 7516)
         if not (isinstance(ax, MultiIndex) and isinstance(key, tuple)):
-            if is_list_like(key, strict=False):
+            if is_list_like(key):
                 indexer = {self._get_axis_name(axis): key}
                 return self.reindex(**indexer)
 
diff --git a/pandas/core/reshape/melt.py b/pandas/core/reshape/melt.py
index 6b1172a1fb17b..26221143c0cdf 100644
--- a/pandas/core/reshape/melt.py
+++ b/pandas/core/reshape/melt.py
@@ -26,7 +26,7 @@ def melt(frame, id_vars=None, value_vars=None, var_name=None,
          value_name='value', col_level=None):
     # TODO: what about the existing index?
     if id_vars is not None:
-        if not is_list_like(id_vars, strict=False):
+        if not is_list_like(id_vars):
             id_vars = [id_vars]
         elif (isinstance(frame.columns, ABCMultiIndex) and
               not isinstance(id_vars, list)):
@@ -38,7 +38,7 @@ def melt(frame, id_vars=None, value_vars=None, var_name=None,
         id_vars = []
 
     if value_vars is not None:
-        if not is_list_like(value_vars, strict=False):
+        if not is_list_like(value_vars):
             value_vars = [value_vars]
         elif (isinstance(frame.columns, ABCMultiIndex) and
               not isinstance(value_vars, list)):
@@ -409,7 +409,7 @@ def melt_stub(df, stub, i, j, value_vars, sep):
 
         return newdf.set_index(i + [j])
 
-    if not is_list_like(stubnames, strict=False):
+    if not is_list_like(stubnames):
         stubnames = [stubnames]
     else:
         stubnames = list(stubnames)
@@ -417,7 +417,7 @@ def melt_stub(df, stub, i, j, value_vars, sep):
     if any(col in stubnames for col in df.columns):
         raise ValueError("stubname can't be identical to a column name")
 
-    if not is_list_like(i, strict=False):
+    if not is_list_like(i):
         i = [i]
     else:
         i = list(i)
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index ddf51f3154ad8..d0c7b66978661 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -1296,9 +1296,9 @@ def _validate_specification(self):
         # add 'by' to our key-list so we can have it in the
         # output as a key
         if self.left_by is not None:
-            if not is_list_like(self.left_by, strict=False):
+            if not is_list_like(self.left_by):
                 self.left_by = [self.left_by]
-            if not is_list_like(self.right_by, strict=False):
+            if not is_list_like(self.right_by):
                 self.right_by = [self.right_by]
 
             if len(self.left_by) != len(self.right_by):
diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index 7fe900e339648..b525dddeb1ba5 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -48,7 +48,7 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
 
     values_passed = values is not None
     if values_passed:
-        if is_list_like(values, strict=False):
+        if is_list_like(values):
             values_multi = True
             values = list(values)
         else:
@@ -383,8 +383,7 @@ def pivot(data, index=None, columns=None, values=None):
             index = data[index]
         index = MultiIndex.from_arrays([index, data[columns]])
 
-        if (is_list_like(values, strict=False)
-                and not isinstance(values, tuple)):
+        if is_list_like(values) and not isinstance(values, tuple):
             # Exclude tuple because it is seen as a single column name
             indexed = data._constructor(data[values].values, index=index,
                                         columns=values)
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index e306f4626a7ed..50f6e310705d7 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -743,7 +743,7 @@ def check_len(item, name):
             len_msg = ("Length of '{name}' ({len_item}) did not match the "
                        "length of the columns being encoded ({len_enc}).")
 
-            if is_list_like(item, strict=False):
+            if is_list_like(item):
                 if not len(item) == data_to_encode.shape[1]:
                     len_msg = \
                         len_msg.format(name=name, len_item=len(item),
diff --git a/pandas/core/reshape/util.py b/pandas/core/reshape/util.py
index af99172b2c65a..1c2033d90cd8a 100644
--- a/pandas/core/reshape/util.py
+++ b/pandas/core/reshape/util.py
@@ -32,10 +32,10 @@ def cartesian_product(X):
     pandas.compat.product : An alias for itertools.product.
     """
     msg = "Input must be a list-like of list-likes"
-    if not is_list_like(X, strict=False):
+    if not is_list_like(X):
         raise TypeError(msg)
     for x in X:
-        if not is_list_like(x, strict=False):
+        if not is_list_like(x):
             raise TypeError(msg)
 
     if len(X) == 0:
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 4cd1745baf990..a613b22ea9046 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -249,10 +249,10 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                     data = data.to_dense()
 
             if index is None:
-                if not is_list_like(data, strict=False):
+                if not is_list_like(data):
                     data = [data]
                 index = ibase.default_index(len(data))
-            elif is_list_like(data, strict=False):
+            elif is_list_like(data):
 
                 # a scalar numpy array is list-like but doesn't
                 # have a proper length
@@ -775,8 +775,8 @@ def __getitem__(self, key):
             result = self.index.get_value(self, key)
 
             if not is_scalar(result):
-                if (is_list_like(result, strict=False)
-                        and not isinstance(result, Series)):
+                if is_list_like(result) and not isinstance(result, Series):
+
                     # we need to box if loc of the key isn't scalar here
                     # otherwise have inline ndarray/lists
                     try:
@@ -1895,7 +1895,7 @@ def quantile(self, q=0.5, interpolation='linear'):
 
         result = self._data.quantile(qs=q, interpolation=interpolation)
 
-        if is_list_like(q, strict=False):
+        if is_list_like(q):
             return self._constructor(result,
                                      index=Float64Index(q),
                                      name=self.name)
@@ -2561,7 +2561,7 @@ def _try_kind_sort(arr):
 
         argsorted = _try_kind_sort(arr[good])
 
-        if is_list_like(ascending, strict=False):
+        if is_list_like(ascending):
             if len(ascending) != 1:
                 raise ValueError('Length of ascending (%d) must be 1 '
                                  'for Series' % (len(ascending)))
@@ -3494,8 +3494,8 @@ def rename(self, index=None, **kwargs):
         kwargs['inplace'] = validate_bool_kwarg(kwargs.get('inplace', False),
                                                 'inplace')
 
-        non_mapping = is_scalar(index) or (is_list_like(index, strict=False)
-                                           and not is_dict_like(index))
+        non_mapping = is_scalar(index) or (is_list_like(index) and
+                                           not is_dict_like(index))
         if non_mapping:
             return self._set_name(index, inplace=kwargs.get('inplace'))
         return super(Series, self).rename(index=index, **kwargs)
@@ -4234,10 +4234,9 @@ def _try_cast(arr, take_fast_path):
             subarr = maybe_cast_to_datetime(arr, dtype)
             # Take care in creating object arrays (but iterators are not
             # supported):
-            if (is_object_dtype(dtype)
-                and (is_list_like(subarr, strict=False)
-                     and not (is_iterator(subarr)
-                              or isinstance(subarr, np.ndarray)))):
+            if is_object_dtype(dtype) and (is_list_like(subarr) and
+                                           not (is_iterator(subarr) or
+                                           isinstance(subarr, np.ndarray))):
                 subarr = construct_1d_object_array_from_listlike(subarr)
             elif not is_extension_type(subarr):
                 subarr = construct_1d_ndarray_preserving_na(subarr, dtype,
diff --git a/pandas/core/sorting.py b/pandas/core/sorting.py
index fe8bdb4d32c67..5aa9ea658482b 100644
--- a/pandas/core/sorting.py
+++ b/pandas/core/sorting.py
@@ -424,7 +424,7 @@ def safe_sort(values, labels=None, na_sentinel=-1, assume_unique=False):
     ValueError
         * If ``labels`` is not None and ``values`` contain duplicates.
     """
-    if not is_list_like(values, strict=False):
+    if not is_list_like(values):
         raise TypeError("Only list-like objects are allowed to be passed to"
                         "safe_sort as values")
 
@@ -459,7 +459,7 @@ def sort_mixed(values):
     if labels is None:
         return ordered
 
-    if not is_list_like(labels, strict=False):
+    if not is_list_like(labels):
         raise TypeError("Only list-like objects or None are allowed to be"
                         "passed to safe_sort as labels")
     labels = ensure_platform_int(np.asarray(labels))
diff --git a/pandas/core/sparse/array.py b/pandas/core/sparse/array.py
index 47ffdd3539bd4..186a2490a5f2e 100644
--- a/pandas/core/sparse/array.py
+++ b/pandas/core/sparse/array.py
@@ -776,7 +776,7 @@ def _sanitize_values(arr):
         if isinstance(arr, np.ndarray):
             pass
 
-        elif is_list_like(arr, strict=False) and len(arr) > 0:
+        elif is_list_like(arr) and len(arr) > 0:
             arr = maybe_convert_platform(arr)
 
         else:
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 27bfc58bc5dc5..1f15e643302d4 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -1973,7 +1973,7 @@ def _wrap_result(self, result, use_codes=True,
             # not needed when inferred
 
             def cons_row(x):
-                if is_list_like(x, strict=False):
+                if is_list_like(x):
                     return x
                 else:
                     return [x]
@@ -2083,12 +2083,12 @@ def _get_series_list(self, others, ignore_index=False):
         elif isinstance(others, np.ndarray) and others.ndim == 2:
             others = DataFrame(others, index=idx)
             return ([others[x] for x in others], False)
-        elif is_list_like(others, strict=True):
+        elif is_ordered_list_like(others):
             others = list(others)  # ensure iterators do not get read twice etc
 
             # in case of list-like `others`, all elements must be
             # either one-dimensional list-likes or scalars
-            if all(is_list_like(x, strict=True) for x in others):
+            if all(is_ordered_list_like(x) for x in others):
                 los = []
                 join_warn = False
                 depr_warn = False
@@ -2116,7 +2116,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_list_like(x, strict=True)
+                                or all(not is_ordered_list_like(x)
                                        for x in nxt))
 
                     # DataFrame is false positive of is_legal
@@ -2135,7 +2135,7 @@ def _get_series_list(self, others, ignore_index=False):
                                   'deprecated and will be removed in a future '
                                   'version.', FutureWarning, stacklevel=3)
                 return (los, join_warn)
-            elif all(not is_list_like(x, strict=True) for x in others):
+            elif all(not is_ordered_list_like(x) for x in others):
                 return ([Series(others, index=idx)], False)
         raise TypeError(err_msg)
 
diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
index ac851b8ee3cdf..eb8d2b0b6c809 100644
--- a/pandas/core/tools/datetimes.py
+++ b/pandas/core/tools/datetimes.py
@@ -375,7 +375,7 @@ def _adjust_to_origin(arg, origin, unit):
         offset = offset // tslibs.Timedelta(1, unit=unit)
 
         # scalars & ndarray-like can handle the addition
-        if is_list_like(arg, strict=False) and not isinstance(
+        if is_list_like(arg) and not isinstance(
                 arg, (ABCSeries, ABCIndexClass, np.ndarray)):
             arg = np.asarray(arg)
         arg = arg + offset
@@ -580,7 +580,7 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
         else:
             convert_listlike = partial(convert_listlike, name=arg.name)
             result = convert_listlike(arg, box, format)
-    elif is_list_like(arg, strict=False):
+    elif is_list_like(arg):
         cache_array = _maybe_cache(arg, format, cache, convert_listlike)
         if not cache_array.empty:
             result = _convert_and_box_cache(arg, cache_array, box, errors)
@@ -868,7 +868,7 @@ def _convert_listlike(arg, format):
         return Series(values, index=arg.index, name=arg.name)
     elif isinstance(arg, ABCIndexClass):
         return _convert_listlike(arg, format)
-    elif is_list_like(arg, strict=False):
+    elif is_list_like(arg):
         return _convert_listlike(arg, format)
 
     return _convert_listlike(np.array([arg]), format)[0]
diff --git a/pandas/core/tools/timedeltas.py b/pandas/core/tools/timedeltas.py
index f1e64dc04af3b..4dc4fcb00d84d 100644
--- a/pandas/core/tools/timedeltas.py
+++ b/pandas/core/tools/timedeltas.py
@@ -88,7 +88,7 @@ def to_timedelta(arg, unit='ns', box=True, errors='raise'):
     elif isinstance(arg, np.ndarray) and arg.ndim == 0:
         # extract array scalar and process below
         arg = arg.item()
-    elif is_list_like(arg, strict=False) and getattr(arg, 'ndim', 1) == 1:
+    elif is_list_like(arg) and getattr(arg, 'ndim', 1) == 1:
         return _convert_listlike(arg, unit=unit, box=box, errors=errors)
     elif getattr(arg, 'ndim', 1) > 1:
         raise TypeError('arg must be a string, timedelta, list, tuple, '
diff --git a/pandas/core/util/hashing.py b/pandas/core/util/hashing.py
index a873d49af1e9c..e62d70847437c 100644
--- a/pandas/core/util/hashing.py
+++ b/pandas/core/util/hashing.py
@@ -140,7 +140,7 @@ def hash_tuples(vals, encoding='utf8', hash_key=None):
     if isinstance(vals, tuple):
         vals = [vals]
         is_tuple = True
-    elif not is_list_like(vals, strict=False):
+    elif not is_list_like(vals):
         raise TypeError("must be convertible to a list-of-tuples")
 
     from pandas import Categorical, MultiIndex
diff --git a/pandas/core/window.py b/pandas/core/window.py
index 650860195b76f..ea0ec79d655fb 100644
--- a/pandas/core/window.py
+++ b/pandas/core/window.py
@@ -149,8 +149,7 @@ def _gotitem(self, key, ndim, subset=None):
         self = self._shallow_copy(subset)
         self._reset_cache()
         if subset.ndim == 2:
-            if (is_scalar(key) and key in subset
-                    or is_list_like(key, strict=False)):
+            if is_scalar(key) and key in subset or is_list_like(key):
                 self._selection = key
         return self
 
diff --git a/pandas/io/excel.py b/pandas/io/excel.py
index a864bd1da89f9..00b4c704c681b 100644
--- a/pandas/io/excel.py
+++ b/pandas/io/excel.py
@@ -639,13 +639,13 @@ def _parse_cell(cell_contents, cell_typ):
                 output[asheetname] = DataFrame()
                 continue
 
-            if is_list_like(header, strict=False) and len(header) == 1:
+            if is_list_like(header) and len(header) == 1:
                 header = header[0]
 
             # forward fill and pull out names for MultiIndex column
             header_names = None
             if header is not None:
-                if is_list_like(header, strict=False):
+                if is_list_like(header):
                     header_names = []
                     control_row = [True] * len(data[0])
                     for row in header:
@@ -660,9 +660,9 @@ def _parse_cell(cell_contents, cell_typ):
                 else:
                     data[header] = _trim_excel_header(data[header])
 
-            if is_list_like(index_col, strict=False):
+            if is_list_like(index_col):
                 # forward fill values for MultiIndex index
-                if not is_list_like(header, strict=False):
+                if not is_list_like(header):
                     offset = 1 + header
                 else:
                     offset = 1 + max(header)
@@ -675,8 +675,7 @@ def _parse_cell(cell_contents, cell_typ):
                         else:
                             last = data[row][col]
 
-            has_index_names = (is_list_like(header, strict=False)
-                               and len(header) > 1)
+            has_index_names = is_list_like(header) and len(header) > 1
 
             # GH 12292 : error when read one empty column from excel file
             try:
@@ -795,8 +794,7 @@ def _pop_header_name(row, index_col):
         return none_fill(row[0]), row[1:]
     else:
         # pop out header name and fill w/ blank
-        i = (index_col if not is_list_like(index_col, strict=False)
-             else max(index_col))
+        i = index_col if not is_list_like(index_col) else max(index_col)
         return none_fill(row[i]), row[:i] + [''] + row[i + 1:]
 
 
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index a74559a6966a1..db86409adc2b0 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -517,7 +517,7 @@ def _to_str_columns(self):
 
         str_index = self._get_formatted_index(frame)
 
-        if not is_list_like(self.header, strict=False) and not self.header:
+        if not is_list_like(self.header) and not self.header:
             stringified = []
             for i, c in enumerate(frame):
                 fmt_values = self._format_col(i)
@@ -526,7 +526,7 @@ def _to_str_columns(self):
                                                adj=self.adj)
                 stringified.append(fmt_values)
         else:
-            if is_list_like(self.header, strict=False):
+            if is_list_like(self.header):
                 if len(self.header) != len(self.columns):
                     raise ValueError(('Writing {ncols} cols but got {nalias} '
                                       'aliases'
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index 7d9bcbb456fa8..f4bb53ba4f218 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -1104,7 +1104,7 @@ def bar(self, subset=None, axis=0, color='#d65f5f', width=100,
         if align not in ('left', 'zero', 'mid'):
             raise ValueError("`align` must be one of {'left', 'zero',' mid'}")
 
-        if not (is_list_like(color, strict=False)):
+        if not (is_list_like(color)):
             color = [color, color]
         elif len(color) == 1:
             color = [color[0], color[0]]
diff --git a/pandas/io/html.py b/pandas/io/html.py
index ec29957b53913..04534ff591a2c 100644
--- a/pandas/io/html.py
+++ b/pandas/io/html.py
@@ -105,8 +105,7 @@ def _get_skiprows(skiprows):
     """
     if isinstance(skiprows, slice):
         return lrange(skiprows.start or 0, skiprows.stop, skiprows.step or 1)
-    elif (isinstance(skiprows, numbers.Integral)
-          or is_list_like(skiprows, strict=False)):
+    elif isinstance(skiprows, numbers.Integral) or is_list_like(skiprows):
         return skiprows
     elif skiprows is None:
         return 0
diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py
index 7b5a5591f2d6d..2def3b81c9518 100755
--- a/pandas/io/parsers.py
+++ b/pandas/io/parsers.py
@@ -1225,7 +1225,7 @@ def _validate_usecols_arg(usecols):
         if callable(usecols):
             return usecols, None
         # GH20529, ensure is iterable container but not string.
-        elif not is_list_like(usecols, strict=False):
+        elif not is_list_like(usecols):
             raise ValueError(msg)
         else:
             usecols_dtype = lib.infer_dtype(usecols)
@@ -3157,7 +3157,7 @@ def _clean_na_values(na_values, keep_default_na=True):
         # where we append the default NaN values, provided
         # that `keep_default_na=True`.
         for k, v in compat.iteritems(old_na_values):
-            if not is_list_like(v, strict=False):
+            if not is_list_like(v):
                 v = [v]
 
             if keep_default_na:
@@ -3166,7 +3166,7 @@ def _clean_na_values(na_values, keep_default_na=True):
             na_values[k] = v
         na_fvalues = {k: _floatify_na_values(v) for k, v in na_values.items()}
     else:
-        if not is_list_like(na_values, strict=False):
+        if not is_list_like(na_values):
             na_values = [na_values]
         na_values = _stringify_na_values(na_values)
         if keep_default_na:
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 3a03f020e9fe5..ff37036533b4f 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -4758,7 +4758,7 @@ def __init__(self, table, where=None, start=None, stop=None, **kwargs):
         self.terms = None
         self.coordinates = None
 
-        if is_list_like(where, strict=False):
+        if is_list_like(where):
 
             # see if we have a passed coordinate like
             try:
diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index a0d3413e6d858..882fa0092b2cf 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -748,7 +748,7 @@ def _create_table_setup(self):
                    for name, typ, is_index in column_names_and_types]
 
         if self.keys is not None:
-            if not is_list_like(self.keys, strict=False):
+            if not is_list_like(self.keys):
                 keys = [self.keys]
             else:
                 keys = self.keys
@@ -1289,7 +1289,7 @@ def _create_table_setup(self):
                             for cname, ctype, _ in column_names_and_types]
 
         if self.keys is not None and len(self.keys):
-            if not is_list_like(self.keys, strict=False):
+            if not is_list_like(self.keys):
                 keys = [self.keys]
             else:
                 keys = self.keys
diff --git a/pandas/tests/computation/test_eval.py b/pandas/tests/computation/test_eval.py
index 68c852d50c596..eef8646e4d6d2 100644
--- a/pandas/tests/computation/test_eval.py
+++ b/pandas/tests/computation/test_eval.py
@@ -268,7 +268,7 @@ def check_operands(left, right, cmp_op):
 
     def check_simple_cmp_op(self, lhs, cmp1, rhs):
         ex = 'lhs {0} rhs'.format(cmp1)
-        if cmp1 in ('in', 'not in') and not is_list_like(rhs, strict=False):
+        if cmp1 in ('in', 'not in') and not is_list_like(rhs):
             pytest.raises(TypeError, pd.eval, ex, engine=self.engine,
                           parser=self.parser, local_dict={'lhs': lhs,
                                                           'rhs': rhs})
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 7b866ff357ad9..e4ec5a61b5052 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -6,7 +6,7 @@
 
 """
 from warnings import catch_warnings, simplefilter
-import collections
+from collections import namedtuple, OrderedDict
 import re
 from datetime import datetime, date, timedelta, time
 from decimal import Decimal
@@ -21,7 +21,7 @@
                     Panel, Period, Categorical, isna, Interval,
                     DateOffset)
 from pandas import compat
-from pandas.compat import u, PY2, StringIO, lrange
+from pandas.compat import u, PY2, PY36, StringIO, lrange
 from pandas.core.dtypes import inference
 from pandas.core.dtypes.common import (
     is_timedelta64_dtype,
@@ -66,25 +66,40 @@ def __getitem__(self):
 @pytest.mark.parametrize(
     "ll",
     [
-        [], [1], (1, ), (1, 2), {'a': 1},
-        Series([1]),
-        Series([]), Series(['a']).str,
-        np.array([2])
+        [], [1], tuple(), (1, ), (1, 2), {'a': 1}, {1, 'a'}, np.array([2]),
+        Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
+        DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
+        np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
     ])
 def test_is_list_like_passes(ll):
-    assert inference.is_list_like(ll, strict=False)
+    assert inference.is_list_like(ll)
 
 
-def test_is_list_like_strict():
-    ll = {1, 'a'}
-    assert inference.is_list_like(ll, strict=False)
-    assert not inference.is_list_like(ll, strict=True)
+@pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2)])
+def test_is_list_like_fails(ll):
+    assert not inference.is_list_like(ll)
 
 
 @pytest.mark.parametrize(
-    "ll", [1, '2', object(), str, np.array(2)])
-def test_is_list_like_fails(ll):
-    assert not inference.is_list_like(ll, strict=False)
+    "ll",
+    [
+        [], [1], tuple(), (1, ), (1, 2), np.array([2]), OrderedDict({'a': 1}),
+        Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
+        DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
+        np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
+    ])
+def test_is_ordered_list_like_passes(ll):
+    assert inference.is_list_like(ll)
+
+
+@pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
+                                {1, 'a'}, frozenset({1, 'a'}), {1, 'a'}])
+def test_is_ordered_like_fails(ll):
+    # GH 23061
+    if PY36 and isinstance(ll, dict):
+        assert inference.is_ordered_list_like(ll)
+    else:
+        assert not inference.is_ordered_list_like(ll)
 
 
 def test_is_array_like():
@@ -113,7 +128,7 @@ class DtypeList(list):
 ])
 def test_is_nested_list_like_passes(inner, outer):
     result = outer([inner for _ in range(5)])
-    assert inference.is_list_like(result, strict=False)
+    assert inference.is_list_like(result)
 
 
 @pytest.mark.parametrize('obj', [
@@ -179,7 +194,7 @@ class MockFile(object):
 
 
 @pytest.mark.parametrize(
-    "ll", [collections.namedtuple('Test', list('abc'))(1, 2, 3)])
+    "ll", [namedtuple('Test', list('abc'))(1, 2, 3)])
 def test_is_names_tuple_passes(ll):
     assert inference.is_named_tuple(ll)
 
diff --git a/pandas/tests/extension/decimal/array.py b/pandas/tests/extension/decimal/array.py
index 31a320b272ec0..a1ee3a4fefef2 100644
--- a/pandas/tests/extension/decimal/array.py
+++ b/pandas/tests/extension/decimal/array.py
@@ -104,7 +104,7 @@ def astype(self, dtype, copy=True):
         return super(DecimalArray, self).astype(dtype, copy)
 
     def __setitem__(self, key, value):
-        if pd.api.types.is_list_like(value, strict=False):
+        if pd.api.types.is_list_like(value):
             value = [decimal.Decimal(v) for v in value]
         else:
             value = decimal.Decimal(value)
diff --git a/pandas/tests/plotting/common.py b/pandas/tests/plotting/common.py
index b48f65e7a89d3..5c88926828fa6 100644
--- a/pandas/tests/plotting/common.py
+++ b/pandas/tests/plotting/common.py
@@ -163,8 +163,8 @@ def _check_visible(self, collections, visible=True):
             expected visibility
         """
         from matplotlib.collections import Collection
-        if (not isinstance(collections, Collection)
-                and not is_list_like(collections, strict=False)):
+        if not isinstance(collections,
+                          Collection) and not is_list_like(collections):
             collections = [collections]
 
         for patch in collections:
@@ -251,7 +251,7 @@ def _check_text_labels(self, texts, expected):
         expected : str or list-like which has the same length as texts
             expected text label, or its list
         """
-        if not is_list_like(texts, strict=False):
+        if not is_list_like(texts):
             assert texts.get_text() == expected
         else:
             labels = [t.get_text() for t in texts]
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index acd3070c9077d..cd297c356d60e 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -2644,7 +2644,7 @@ def _check_errorbar_color(containers, expected, has_err='has_xerr'):
             errs = [c.lines
                     for c in ax.containers if getattr(c, has_err, False)][0]
             for el in errs:
-                if is_list_like(el, strict=False):
+                if is_list_like(el):
                     lines.extend(el)
                 else:
                     lines.append(el)

From 1941376b5e47e885b55810ee1fa85da4f4bcefd8 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 10 Oct 2018 23:36:01 +0200
Subject: [PATCH 05/17] abc-compat

---
 pandas/compat/__init__.py       | 2 ++
 pandas/core/dtypes/inference.py | 6 +++---
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/pandas/compat/__init__.py b/pandas/compat/__init__.py
index 1453725225e7d..5108e23c53b5a 100644
--- a/pandas/compat/__init__.py
+++ b/pandas/compat/__init__.py
@@ -141,6 +141,7 @@ def lfilter(*args, **kwargs):
     Mapping = collections.abc.Mapping
     Sequence = collections.abc.Sequence
     Sized = collections.abc.Sized
+    Set = collections.abc.Set
 
 else:
     # Python 2
@@ -201,6 +202,7 @@ def get_range_parameters(data):
     Mapping = collections.Mapping
     Sequence = collections.Sequence
     Sized = collections.Sized
+    Set = collections.Set
 
 if PY2:
     def iteritems(obj, **kw):
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 9df7a78c1c3b2..60771d964770d 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -5,9 +5,9 @@
 from numbers import Number
 from pandas import compat
 from pandas.compat import (PY2, PY36, string_types, text_type,
-                           string_and_binary_types, re_type)
+                           string_and_binary_types, re_type, Set)
 from pandas._libs import lib
-from collections import abc, OrderedDict
+from collections import OrderedDict
 
 is_bool = lib.is_bool
 
@@ -314,7 +314,7 @@ def is_ordered_list_like(obj):
     list_like = is_list_like(obj)
     unordered_dict = not PY36 and (isinstance(obj, dict)
                                    and not isinstance(obj, OrderedDict))
-    return list_like and not unordered_dict and not isinstance(obj, abc.Set)
+    return list_like and not unordered_dict and not isinstance(obj, Set)
 
 def is_array_like(obj):
     """

From 787139717616a2e03b6f392d237805a542581d58 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 10 Oct 2018 23:42:44 +0200
Subject: [PATCH 06/17] Add import in pandas.core.dtypes.common

---
 pandas/core/dtypes/common.py | 8 ++++----
 pandas/core/strings.py       | 1 +
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index a9fc9d13d4ab3..e7c2a1cc48c44 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -17,10 +17,10 @@
     ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex, ABCIndexClass,
     ABCDateOffset)
 from pandas.core.dtypes.inference import (  # noqa:F401
-    is_bool, is_integer, is_hashable, is_iterator, is_float,
-    is_dict_like, is_scalar, is_string_like, is_list_like, is_number,
-    is_file_like, is_re, is_re_compilable, is_sequence, is_nested_list_like,
-    is_named_tuple, is_array_like, is_decimal, is_complex, is_interval)
+    is_bool, is_integer, is_float, is_number, is_decimal, is_complex, is_re,
+    is_re_compilable, is_dict_like, is_string_like, is_file_like, is_list_like,
+    is_ordered_list_like, is_nested_list_like, is_sequence, is_named_tuple,
+    is_array_like, is_hashable, is_iterator, is_scalar, is_interval)
 
 
 _POSSIBLY_CAST_DTYPES = {np.dtype(t).name
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 1f15e643302d4..6ddf9135b5f5e 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -10,6 +10,7 @@
     is_object_dtype,
     is_string_like,
     is_list_like,
+    is_ordered_list_like,
     is_scalar,
     is_integer,
     is_re)

From 8efee57c4503ba42cb3e0ae1f70e6b3958964deb Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Thu, 11 Oct 2018 00:22:45 +0200
Subject: [PATCH 07/17] Review (jorisvandenbossche)

---
 pandas/core/dtypes/common.py          |  8 +++---
 pandas/core/dtypes/inference.py       | 37 ++++++---------------------
 pandas/core/strings.py                |  9 +++----
 pandas/tests/dtypes/test_inference.py | 15 +++++------
 4 files changed, 22 insertions(+), 47 deletions(-)

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index e7c2a1cc48c44..6bbfff9914a0d 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -17,10 +17,10 @@
     ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex, ABCIndexClass,
     ABCDateOffset)
 from pandas.core.dtypes.inference import (  # noqa:F401
-    is_bool, is_integer, is_float, is_number, is_decimal, is_complex, is_re,
-    is_re_compilable, is_dict_like, is_string_like, is_file_like, is_list_like,
-    is_ordered_list_like, is_nested_list_like, is_sequence, is_named_tuple,
-    is_array_like, is_hashable, is_iterator, is_scalar, is_interval)
+    is_bool, is_integer, is_float, is_number, is_decimal, is_complex,
+    is_re, is_re_compilable, is_dict_like, is_string_like, is_file_like,
+    is_list_like, is_nested_list_like, is_sequence, is_named_tuple,
+    is_hashable, is_iterator, is_array_like, is_scalar, is_interval)
 
 
 _POSSIBLY_CAST_DTYPES = {np.dtype(t).name
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 60771d964770d..f087682fc50d0 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -248,7 +248,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj):
+def is_list_like(obj, strict=False):
     """
     Check if the object is list-like.
 
@@ -260,6 +260,8 @@ def is_list_like(obj):
     Parameters
     ----------
     obj : The object to check.
+    strict : boolean, default False
+        If this parameter is True, sets will not be considered list-like
 
     Returns
     -------
@@ -284,37 +286,14 @@ def is_list_like(obj):
     False
     """
 
-    return (isinstance(obj, compat.Iterable) and
+    return (isinstance(obj, compat.Iterable)
             # we do not count strings/unicode/bytes as list-like
-            not isinstance(obj, string_and_binary_types) and
+            and not isinstance(obj, string_and_binary_types)
             # exclude zero-dimensional numpy arrays, effectively scalars
-            not (isinstance(obj, np.ndarray) and obj.ndim == 0))
-
-
-def is_ordered_list_like(obj):
-    """
-    Check if the object is list-like and has a defined order
+            and not (isinstance(obj, np.ndarray) and obj.ndim == 0)
+            # exclude sets if ordered_only
+            and not (strict and isinstance(obj, Set)))
 
-    Works like :meth:`is_list_like` but excludes sets (as well as unordered
-    `dict` before Python 3.6)
-
-    Note that iterators can not be inspected for order - this check will return
-    True but it is up to the user to make sure that their iterators are
-    generated in an ordered way.
-
-    Parameters
-    ----------
-    obj : The object to check.
-
-    Returns
-    -------
-    is_ordered_list_like : bool
-        Whether `obj` is an ordered list-like
-    """
-    list_like = is_list_like(obj)
-    unordered_dict = not PY36 and (isinstance(obj, dict)
-                                   and not isinstance(obj, OrderedDict))
-    return list_like and not unordered_dict and not isinstance(obj, Set)
 
 def is_array_like(obj):
     """
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 6ddf9135b5f5e..d3f64b0100e40 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -10,7 +10,6 @@
     is_object_dtype,
     is_string_like,
     is_list_like,
-    is_ordered_list_like,
     is_scalar,
     is_integer,
     is_re)
@@ -2084,12 +2083,12 @@ def _get_series_list(self, others, ignore_index=False):
         elif isinstance(others, np.ndarray) and others.ndim == 2:
             others = DataFrame(others, index=idx)
             return ([others[x] for x in others], False)
-        elif is_ordered_list_like(others):
+        elif is_list_like(others, strict=True):
             others = list(others)  # ensure iterators do not get read twice etc
 
             # in case of list-like `others`, all elements must be
             # either one-dimensional list-likes or scalars
-            if all(is_ordered_list_like(x) for x in others):
+            if all(is_list_like(x, strict=True) for x in others):
                 los = []
                 join_warn = False
                 depr_warn = False
@@ -2117,7 +2116,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_ordered_list_like(x)
+                                or all(not is_list_like(x, strict=True)
                                        for x in nxt))
 
                     # DataFrame is false positive of is_legal
@@ -2136,7 +2135,7 @@ def _get_series_list(self, others, ignore_index=False):
                                   'deprecated and will be removed in a future '
                                   'version.', FutureWarning, stacklevel=3)
                 return (los, join_warn)
-            elif all(not is_ordered_list_like(x) for x in others):
+            elif all(not is_list_like(x, strict=True) for x in others):
                 return ([Series(others, index=idx)], False)
         raise TypeError(err_msg)
 
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index e4ec5a61b5052..5aa2d2b27defe 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -83,23 +83,20 @@ def test_is_list_like_fails(ll):
 @pytest.mark.parametrize(
     "ll",
     [
-        [], [1], tuple(), (1, ), (1, 2), np.array([2]), OrderedDict({'a': 1}),
+        [], [1], tuple(), (1, ), (1, 2), {'a': 1}, np.array([2]),
         Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
     ])
-def test_is_ordered_list_like_passes(ll):
-    assert inference.is_list_like(ll)
+def test_is_list_like_strict_passes(ll):
+    assert inference.is_list_like(ll, strict=True)
 
 
 @pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
-                                {1, 'a'}, frozenset({1, 'a'}), {1, 'a'}])
-def test_is_ordered_like_fails(ll):
+                                {1, 'a'}, frozenset({1, 'a'})])
+def test_is_list_like_strict_fails(ll):
     # GH 23061
-    if PY36 and isinstance(ll, dict):
-        assert inference.is_ordered_list_like(ll)
-    else:
-        assert not inference.is_ordered_list_like(ll)
+    assert not inference.is_list_like(ll, strict=True)
 
 
 def test_is_array_like():

From 0826f34db2b9617919ac0a3ca833524b462d17da Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Thu, 11 Oct 2018 00:39:52 +0200
Subject: [PATCH 08/17] Lint

---
 pandas/core/dtypes/inference.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index f087682fc50d0..12eff1130d8a3 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -4,10 +4,9 @@
 import numpy as np
 from numbers import Number
 from pandas import compat
-from pandas.compat import (PY2, PY36, string_types, text_type,
+from pandas.compat import (PY2, string_types, text_type,
                            string_and_binary_types, re_type, Set)
 from pandas._libs import lib
-from collections import OrderedDict
 
 is_bool = lib.is_bool
 

From 5686c7701347a6703fb7b98376648fd68b5b4524 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Thu, 11 Oct 2018 00:42:02 +0200
Subject: [PATCH 09/17] More lint

---
 pandas/tests/dtypes/test_inference.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 5aa2d2b27defe..66a403a69f731 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -6,7 +6,7 @@
 
 """
 from warnings import catch_warnings, simplefilter
-from collections import namedtuple, OrderedDict
+import collections
 import re
 from datetime import datetime, date, timedelta, time
 from decimal import Decimal
@@ -21,7 +21,7 @@
                     Panel, Period, Categorical, isna, Interval,
                     DateOffset)
 from pandas import compat
-from pandas.compat import u, PY2, PY36, StringIO, lrange
+from pandas.compat import u, PY2, StringIO, lrange
 from pandas.core.dtypes import inference
 from pandas.core.dtypes.common import (
     is_timedelta64_dtype,
@@ -191,7 +191,7 @@ class MockFile(object):
 
 
 @pytest.mark.parametrize(
-    "ll", [namedtuple('Test', list('abc'))(1, 2, 3)])
+    "ll", [collections.namedtuple('Test', list('abc'))(1, 2, 3)])
 def test_is_names_tuple_passes(ll):
     assert inference.is_named_tuple(ll)
 

From 3796080a463f718d89ca13a5953afcdda1ae1c5e Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Mon, 15 Oct 2018 20:23:20 +0200
Subject: [PATCH 10/17] Back to is_ordered_list_like

---
 pandas/core/dtypes/common.py          |  6 +++---
 pandas/core/dtypes/inference.py       | 29 +++++++++++++++++++++------
 pandas/core/strings.py                |  9 +++++----
 pandas/tests/dtypes/test_inference.py |  8 ++++----
 4 files changed, 35 insertions(+), 17 deletions(-)

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index bf22025761426..5f8c7a807bc50 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -18,9 +18,9 @@
     ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex, ABCIndexClass,
     ABCDateOffset)
 from pandas.core.dtypes.inference import (  # noqa:F401
-    is_bool, is_integer, is_float, is_number, is_decimal, is_complex,
-    is_re, is_re_compilable, is_dict_like, is_string_like, is_file_like,
-    is_list_like, is_nested_list_like, is_sequence, is_named_tuple,
+    is_bool, is_integer, is_float, is_number, is_decimal, is_complex, is_re,
+    is_re_compilable, is_dict_like, is_string_like, is_file_like, is_list_like,
+    is_ordered_list_like, is_nested_list_like, is_sequence, is_named_tuple,
     is_hashable, is_iterator, is_array_like, is_scalar, is_interval)
 
 
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 12eff1130d8a3..c80eb6edba606 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -247,7 +247,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj, strict=False):
+def is_list_like(obj):
     """
     Check if the object is list-like.
 
@@ -259,8 +259,6 @@ def is_list_like(obj, strict=False):
     Parameters
     ----------
     obj : The object to check.
-    strict : boolean, default False
-        If this parameter is True, sets will not be considered list-like
 
     Returns
     -------
@@ -289,9 +287,28 @@ def is_list_like(obj, strict=False):
             # we do not count strings/unicode/bytes as list-like
             and not isinstance(obj, string_and_binary_types)
             # exclude zero-dimensional numpy arrays, effectively scalars
-            and not (isinstance(obj, np.ndarray) and obj.ndim == 0)
-            # exclude sets if ordered_only
-            and not (strict and isinstance(obj, Set)))
+            and not (isinstance(obj, np.ndarray) and obj.ndim == 0))
+
+
+def is_ordered_list_like(obj):
+    """
+    Check if the object is list-like and has a defined order
+
+    Works like :meth:`is_list_like` but excludes sets. Note that iterators can
+    not be inspected for order - this check will return True but it is up to
+    the user to make sure that their iterators are generated in an ordered way.
+
+    Parameters
+    ----------
+    obj : The object to check.
+
+    Returns
+    -------
+    is_ordered_list_like : bool
+        Whether `obj` is an ordered list-like
+    """
+    list_like = is_list_like(obj)
+    return list_like and not isinstance(obj, Set)
 
 
 def is_array_like(obj):
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 9ab18b0577b6c..3fb7795a89185 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -11,6 +11,7 @@
     is_object_dtype,
     is_string_like,
     is_list_like,
+    is_ordered_list_like,
     is_scalar,
     is_integer,
     is_re)
@@ -1996,12 +1997,12 @@ def _get_series_list(self, others, ignore_index=False):
         elif isinstance(others, np.ndarray) and others.ndim == 2:
             others = DataFrame(others, index=idx)
             return ([others[x] for x in others], False)
-        elif is_list_like(others, strict=True):
+        elif is_ordered_list_like(others):
             others = list(others)  # ensure iterators do not get read twice etc
 
             # in case of list-like `others`, all elements must be
             # either one-dimensional list-likes or scalars
-            if all(is_list_like(x, strict=True) for x in others):
+            if all(is_ordered_list_like(x) for x in others):
                 los = []
                 join_warn = False
                 depr_warn = False
@@ -2029,7 +2030,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_list_like(x, strict=True)
+                                or all(not is_ordered_list_like(x)
                                        for x in nxt))
 
                     # DataFrame is false positive of is_legal
@@ -2048,7 +2049,7 @@ def _get_series_list(self, others, ignore_index=False):
                                   'deprecated and will be removed in a future '
                                   'version.', FutureWarning, stacklevel=3)
                 return (los, join_warn)
-            elif all(not is_list_like(x, strict=True) for x in others):
+            elif all(not is_ordered_list_like(x) for x in others):
                 return ([Series(others, index=idx)], False)
         raise TypeError(err_msg)
 
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 66a403a69f731..3791fe9f81b26 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -88,15 +88,15 @@ def test_is_list_like_fails(ll):
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
     ])
-def test_is_list_like_strict_passes(ll):
-    assert inference.is_list_like(ll, strict=True)
+def test_is_ordered_list_like_strict_passes(ll):
+    assert inference.is_ordered_list_like(ll)
 
 
 @pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
                                 {1, 'a'}, frozenset({1, 'a'})])
-def test_is_list_like_strict_fails(ll):
+def test_is_ordered_list_like_fails(ll):
     # GH 23061
-    assert not inference.is_list_like(ll, strict=True)
+    assert not inference.is_ordered_list_like(ll)
 
 
 def test_is_array_like():

From 3647bdd68b66c16fd5ec95cb78c758fd3ed2e523 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Tue, 16 Oct 2018 07:41:06 +0200
Subject: [PATCH 11/17] Split off changes in strings.py

---
 pandas/core/strings.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 3fb7795a89185..10bd616929c8f 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -11,7 +11,6 @@
     is_object_dtype,
     is_string_like,
     is_list_like,
-    is_ordered_list_like,
     is_scalar,
     is_integer,
     is_re)
@@ -1997,12 +1996,12 @@ def _get_series_list(self, others, ignore_index=False):
         elif isinstance(others, np.ndarray) and others.ndim == 2:
             others = DataFrame(others, index=idx)
             return ([others[x] for x in others], False)
-        elif is_ordered_list_like(others):
+        elif is_list_like(others):
             others = list(others)  # ensure iterators do not get read twice etc
 
             # in case of list-like `others`, all elements must be
             # either one-dimensional list-likes or scalars
-            if all(is_ordered_list_like(x) for x in others):
+            if all(is_list_like(x) for x in others):
                 los = []
                 join_warn = False
                 depr_warn = False
@@ -2030,7 +2029,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_ordered_list_like(x)
+                                or all(not is_list_like(x)
                                        for x in nxt))
 
                     # DataFrame is false positive of is_legal
@@ -2049,7 +2048,7 @@ def _get_series_list(self, others, ignore_index=False):
                                   'deprecated and will be removed in a future '
                                   'version.', FutureWarning, stacklevel=3)
                 return (los, join_warn)
-            elif all(not is_ordered_list_like(x) for x in others):
+            elif all(not is_list_like(x) for x in others):
                 return ([Series(others, index=idx)], False)
         raise TypeError(err_msg)
 

From d5ef14fb853218220c4d534135295d09d01981d5 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Tue, 16 Oct 2018 08:51:43 +0200
Subject: [PATCH 12/17] Tiny fix

---
 pandas/core/strings.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 10bd616929c8f..4086021bc61a6 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -2029,8 +2029,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # nested list-likes are forbidden:
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
-                                or all(not is_list_like(x)
-                                       for x in nxt))
+                                or all(not is_list_like(x) for x in nxt))
 
                     # DataFrame is false positive of is_legal
                     # because "x in df" returns column names

From 4b91d2e5558d725eaa65f74c2bead41e432be61f Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 17 Oct 2018 00:10:04 +0200
Subject: [PATCH 13/17] Revert "Back to is_ordered_list_like"

This reverts commit 3796080a463f718d89ca13a5953afcdda1ae1c5e.
---
 pandas/core/dtypes/common.py          |  6 +++---
 pandas/core/dtypes/inference.py       | 29 ++++++---------------------
 pandas/core/strings.py                |  1 -
 pandas/tests/dtypes/test_inference.py |  8 ++++----
 4 files changed, 13 insertions(+), 31 deletions(-)

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index 5f8c7a807bc50..bf22025761426 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -18,9 +18,9 @@
     ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex, ABCIndexClass,
     ABCDateOffset)
 from pandas.core.dtypes.inference import (  # noqa:F401
-    is_bool, is_integer, is_float, is_number, is_decimal, is_complex, is_re,
-    is_re_compilable, is_dict_like, is_string_like, is_file_like, is_list_like,
-    is_ordered_list_like, is_nested_list_like, is_sequence, is_named_tuple,
+    is_bool, is_integer, is_float, is_number, is_decimal, is_complex,
+    is_re, is_re_compilable, is_dict_like, is_string_like, is_file_like,
+    is_list_like, is_nested_list_like, is_sequence, is_named_tuple,
     is_hashable, is_iterator, is_array_like, is_scalar, is_interval)
 
 
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index c80eb6edba606..12eff1130d8a3 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -247,7 +247,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj):
+def is_list_like(obj, strict=False):
     """
     Check if the object is list-like.
 
@@ -259,6 +259,8 @@ def is_list_like(obj):
     Parameters
     ----------
     obj : The object to check.
+    strict : boolean, default False
+        If this parameter is True, sets will not be considered list-like
 
     Returns
     -------
@@ -287,28 +289,9 @@ def is_list_like(obj):
             # we do not count strings/unicode/bytes as list-like
             and not isinstance(obj, string_and_binary_types)
             # exclude zero-dimensional numpy arrays, effectively scalars
-            and not (isinstance(obj, np.ndarray) and obj.ndim == 0))
-
-
-def is_ordered_list_like(obj):
-    """
-    Check if the object is list-like and has a defined order
-
-    Works like :meth:`is_list_like` but excludes sets. Note that iterators can
-    not be inspected for order - this check will return True but it is up to
-    the user to make sure that their iterators are generated in an ordered way.
-
-    Parameters
-    ----------
-    obj : The object to check.
-
-    Returns
-    -------
-    is_ordered_list_like : bool
-        Whether `obj` is an ordered list-like
-    """
-    list_like = is_list_like(obj)
-    return list_like and not isinstance(obj, Set)
+            and not (isinstance(obj, np.ndarray) and obj.ndim == 0)
+            # exclude sets if ordered_only
+            and not (strict and isinstance(obj, Set)))
 
 
 def is_array_like(obj):
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 4086021bc61a6..e9eaa110eec1b 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -2030,7 +2030,6 @@ def _get_series_list(self, others, ignore_index=False):
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
                                 or all(not is_list_like(x) for x in nxt))
-
                     # DataFrame is false positive of is_legal
                     # because "x in df" returns column names
                     if not is_legal or isinstance(nxt, DataFrame):
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 3791fe9f81b26..66a403a69f731 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -88,15 +88,15 @@ def test_is_list_like_fails(ll):
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
     ])
-def test_is_ordered_list_like_strict_passes(ll):
-    assert inference.is_ordered_list_like(ll)
+def test_is_list_like_strict_passes(ll):
+    assert inference.is_list_like(ll, strict=True)
 
 
 @pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
                                 {1, 'a'}, frozenset({1, 'a'})])
-def test_is_ordered_list_like_fails(ll):
+def test_is_list_like_strict_fails(ll):
     # GH 23061
-    assert not inference.is_ordered_list_like(ll)
+    assert not inference.is_list_like(ll, strict=True)
 
 
 def test_is_array_like():

From d1ff6ab9637fb3cb360a314a604d9ed3d6bc1d58 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 17 Oct 2018 00:14:47 +0200
Subject: [PATCH 14/17] Change kwarg to "allow_sets"

---
 pandas/core/dtypes/inference.py       | 10 +++++-----
 pandas/tests/dtypes/test_inference.py |  8 ++++----
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 12eff1130d8a3..2eac42ccc6b68 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -247,7 +247,7 @@ def is_re_compilable(obj):
         return True
 
 
-def is_list_like(obj, strict=False):
+def is_list_like(obj, allow_sets=True):
     """
     Check if the object is list-like.
 
@@ -259,8 +259,8 @@ def is_list_like(obj, strict=False):
     Parameters
     ----------
     obj : The object to check.
-    strict : boolean, default False
-        If this parameter is True, sets will not be considered list-like
+    allow_sets : boolean, default True
+        If this parameter is False, sets will not be considered list-like
 
     Returns
     -------
@@ -290,8 +290,8 @@ def is_list_like(obj, strict=False):
             and not isinstance(obj, string_and_binary_types)
             # exclude zero-dimensional numpy arrays, effectively scalars
             and not (isinstance(obj, np.ndarray) and obj.ndim == 0)
-            # exclude sets if ordered_only
-            and not (strict and isinstance(obj, Set)))
+            # exclude sets if allow_sets is False
+            and not (allow_sets is False and isinstance(obj, Set)))
 
 
 def is_array_like(obj):
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 66a403a69f731..de9f9257f8fbd 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -88,15 +88,15 @@ def test_is_list_like_fails(ll):
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
     ])
-def test_is_list_like_strict_passes(ll):
-    assert inference.is_list_like(ll, strict=True)
+def test_is_list_like_disallow_sets_passes(ll):
+    assert inference.is_list_like(ll, allow_sets=False)
 
 
 @pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
                                 {1, 'a'}, frozenset({1, 'a'})])
-def test_is_list_like_strict_fails(ll):
+def test_is_list_like_disallow_sets_fails(ll):
     # GH 23061
-    assert not inference.is_list_like(ll, strict=True)
+    assert not inference.is_list_like(ll, allow_sets=False)
 
 
 def test_is_array_like():

From ece9deb63b02250d2b00d55593bf478f327fa8c8 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 17 Oct 2018 00:18:13 +0200
Subject: [PATCH 15/17] Tiny fix

---
 pandas/core/strings.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index e9eaa110eec1b..4086021bc61a6 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -2030,6 +2030,7 @@ def _get_series_list(self, others, ignore_index=False):
                     # -> elements of nxt must not be list-like
                     is_legal = ((no_deep and nxt.dtype == object)
                                 or all(not is_list_like(x) for x in nxt))
+
                     # DataFrame is false positive of is_legal
                     # because "x in df" returns column names
                     if not is_legal or isinstance(nxt, DataFrame):

From 13e098375b4907032e55ec11ebfc9da538732b00 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 17 Oct 2018 08:06:04 +0200
Subject: [PATCH 16/17] Review (jreback)

---
 doc/source/whatsnew/v0.24.0.txt       |  2 ++
 pandas/core/dtypes/inference.py       |  4 +++
 pandas/tests/dtypes/test_inference.py | 35 ++++++++++-----------------
 3 files changed, 19 insertions(+), 22 deletions(-)

diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
index 3053625721560..b46d3d7522bc5 100644
--- a/doc/source/whatsnew/v0.24.0.txt
+++ b/doc/source/whatsnew/v0.24.0.txt
@@ -198,6 +198,8 @@ Other Enhancements
 - :meth:`round`, :meth:`ceil`, and meth:`floor` for :class:`DatetimeIndex` and :class:`Timestamp` now support an ``ambiguous`` argument for handling datetimes that are rounded to ambiguous times (:issue:`18946`)
 - :class:`Resampler` now is iterable like :class:`GroupBy` (:issue:`15314`).
 - :meth:`Series.resample` and :meth:`DataFrame.resample` have gained the :meth:`Resampler.quantile` (:issue:`15023`).
+- :meth:`pandas.core.dtypes.is_list_like` has gained a keyword ``allow_sets`` which is ``True`` by default; if ``False``,
+  all instances of ``set`` will not be considered "list-like" anymore (:issue:`23061`)
 - :meth:`Index.to_frame` now supports overriding column name(s) (:issue:`22580`).
 - New attribute :attr:`__git_version__` will return git commit sha of current build (:issue:`21295`).
 - Compatibility with Matplotlib 3.0 (:issue:`22790`).
diff --git a/pandas/core/dtypes/inference.py b/pandas/core/dtypes/inference.py
index 2eac42ccc6b68..7470497383064 100644
--- a/pandas/core/dtypes/inference.py
+++ b/pandas/core/dtypes/inference.py
@@ -262,6 +262,8 @@ def is_list_like(obj, allow_sets=True):
     allow_sets : boolean, default True
         If this parameter is False, sets will not be considered list-like
 
+        .. versionadded:: 0.24.0
+
     Returns
     -------
     is_list_like : bool
@@ -288,8 +290,10 @@ def is_list_like(obj, allow_sets=True):
     return (isinstance(obj, compat.Iterable)
             # we do not count strings/unicode/bytes as list-like
             and not isinstance(obj, string_and_binary_types)
+
             # exclude zero-dimensional numpy arrays, effectively scalars
             and not (isinstance(obj, np.ndarray) and obj.ndim == 0)
+
             # exclude sets if allow_sets is False
             and not (allow_sets is False and isinstance(obj, Set)))
 
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index de9f9257f8fbd..fa2b5d6eaf685 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -64,39 +64,30 @@ def __getitem__(self):
 
 
 @pytest.mark.parametrize(
-    "ll",
-    [
+    "obj, expected",
+    list(zip([
         [], [1], tuple(), (1, ), (1, 2), {'a': 1}, {1, 'a'}, np.array([2]),
         Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
-    ])
-def test_is_list_like_passes(ll):
-    assert inference.is_list_like(ll)
-
-
-@pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2)])
-def test_is_list_like_fails(ll):
-    assert not inference.is_list_like(ll)
+    ], [True] * 30))
+    + list(zip([1, '2', object(), str, np.array(2)], [False] * 10)))
+def test_is_list_like(obj, expected):
+    assert inference.is_list_like(obj) == expected
 
 
 @pytest.mark.parametrize(
-    "ll",
-    [
+    "obj, expected",
+    list(zip([
         [], [1], tuple(), (1, ), (1, 2), {'a': 1}, np.array([2]),
         Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
         DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
         np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
-    ])
-def test_is_list_like_disallow_sets_passes(ll):
-    assert inference.is_list_like(ll, allow_sets=False)
-
-
-@pytest.mark.parametrize("ll", [1, '2', object(), str, np.array(2),
-                                {1, 'a'}, frozenset({1, 'a'})])
-def test_is_list_like_disallow_sets_fails(ll):
-    # GH 23061
-    assert not inference.is_list_like(ll, allow_sets=False)
+    ], [True] * 30))
+    + list(zip([1, '2', object(), str, np.array(2),
+                {1, 'a'}, frozenset({1, 'a'})], [False] * 10)))
+def test_is_list_like_disallow_sets(obj, expected):
+    assert inference.is_list_like(obj, allow_sets=False) == expected
 
 
 def test_is_array_like():

From 2f5e927bdaea3e0abb2d06c4cbbbc806fffade24 Mon Sep 17 00:00:00 2001
From: "H. Vetinari" <h.vetinari@gmx.com>
Date: Wed, 17 Oct 2018 18:18:03 +0200
Subject: [PATCH 17/17] Review (TomAugspurger & jreback)

---
 pandas/tests/dtypes/test_inference.py | 91 +++++++++++++++++++--------
 1 file changed, 64 insertions(+), 27 deletions(-)

diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index fa2b5d6eaf685..d0dd03d6eb8df 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -47,6 +47,70 @@ def coerce(request):
     return request.param
 
 
+# collect all objects to be tested for list-like-ness; use tuples of objects,
+# whether they are list-like or not (special casing for sets), and their ID
+ll_params = [
+    ([1],                       True,  'list'),                 # noqa: E241
+    ([],                        True,  'list-empty'),           # noqa: E241
+    ((1, ),                     True,  'tuple'),                # noqa: E241
+    (tuple(),                   True,  'tuple-empty'),          # noqa: E241
+    ({'a': 1},                  True,  'dict'),                 # noqa: E241
+    (dict(),                    True,  'dict-empty'),           # noqa: E241
+    ({'a', 1},                  'set', 'set'),                  # noqa: E241
+    (set(),                     'set', 'set-empty'),            # noqa: E241
+    (frozenset({'a', 1}),       'set', 'frozenset'),            # noqa: E241
+    (frozenset([]),             'set', 'frozenset-empty'),      # noqa: E241
+    (iter([1, 2]),              True,  'iterator'),             # noqa: E241
+    (iter([]),                  True,  'iterator-empty'),       # noqa: E241
+    ((x for x in [1, 2]),       True,  'generator'),            # noqa: E241
+    ((x for x in []),           True,  'generator-empty'),      # noqa: E241
+    (Series([1]),               True,  'Series'),               # noqa: E241
+    (Series([]),                True,  'Series-empty'),         # noqa: E241
+    (Series(['a']).str,         True,  'StringMethods'),        # noqa: E241
+    (Series([], dtype='O').str, True,  'StringMethods-empty'),  # noqa: E241
+    (Index([1]),                True,  'Index'),                # noqa: E241
+    (Index([]),                 True,  'Index-empty'),          # noqa: E241
+    (DataFrame([[1]]),          True,  'DataFrame'),            # noqa: E241
+    (DataFrame(),               True,  'DataFrame-empty'),      # noqa: E241
+    (np.ndarray((2,) * 1),      True,  'ndarray-1d'),           # noqa: E241
+    (np.array([]),              True,  'ndarray-1d-empty'),     # noqa: E241
+    (np.ndarray((2,) * 2),      True,  'ndarray-2d'),           # noqa: E241
+    (np.array([[]]),            True,  'ndarray-2d-empty'),     # noqa: E241
+    (np.ndarray((2,) * 3),      True,  'ndarray-3d'),           # noqa: E241
+    (np.array([[[]]]),          True,  'ndarray-3d-empty'),     # noqa: E241
+    (np.ndarray((2,) * 4),      True,  'ndarray-4d'),           # noqa: E241
+    (np.array([[[[]]]]),        True,  'ndarray-4d-empty'),     # noqa: E241
+    (np.array(2),               False, 'ndarray-0d'),           # noqa: E241
+    (1,                         False, 'int'),                  # noqa: E241
+    (b'123',                    False, 'bytes'),                # noqa: E241
+    (b'',                       False, 'bytes-empty'),          # noqa: E241
+    ('123',                     False, 'string'),               # noqa: E241
+    ('',                        False, 'string-empty'),         # noqa: E241
+    (str,                       False, 'string-type'),          # noqa: E241
+    (object(),                  False, 'object'),               # noqa: E241
+    (np.nan,                    False, 'NaN'),                  # noqa: E241
+    (None,                      False, 'None')                  # noqa: E241
+]
+objs, expected, ids = zip(*ll_params)
+
+
+@pytest.fixture(params=zip(objs, expected), ids=ids)
+def maybe_list_like(request):
+    return request.param
+
+
+def test_is_list_like(maybe_list_like):
+    obj, expected = maybe_list_like
+    expected = True if expected == 'set' else expected
+    assert inference.is_list_like(obj) == expected
+
+
+def test_is_list_like_disallow_sets(maybe_list_like):
+    obj, expected = maybe_list_like
+    expected = False if expected == 'set' else expected
+    assert inference.is_list_like(obj, allow_sets=False) == expected
+
+
 def test_is_sequence():
     is_seq = inference.is_sequence
     assert (is_seq((1, 2)))
@@ -63,33 +127,6 @@ def __getitem__(self):
     assert (not is_seq(A()))
 
 
-@pytest.mark.parametrize(
-    "obj, expected",
-    list(zip([
-        [], [1], tuple(), (1, ), (1, 2), {'a': 1}, {1, 'a'}, np.array([2]),
-        Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
-        DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
-        np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
-    ], [True] * 30))
-    + list(zip([1, '2', object(), str, np.array(2)], [False] * 10)))
-def test_is_list_like(obj, expected):
-    assert inference.is_list_like(obj) == expected
-
-
-@pytest.mark.parametrize(
-    "obj, expected",
-    list(zip([
-        [], [1], tuple(), (1, ), (1, 2), {'a': 1}, np.array([2]),
-        Series([1]), Series([]), Series(['a']).str, Index([]), Index([1]),
-        DataFrame(), DataFrame([[1]]), iter([1, 2]), (x for x in [1, 2]),
-        np.ndarray((2,) * 2), np.ndarray((2,) * 3), np.ndarray((2,) * 4)
-    ], [True] * 30))
-    + list(zip([1, '2', object(), str, np.array(2),
-                {1, 'a'}, frozenset({1, 'a'})], [False] * 10)))
-def test_is_list_like_disallow_sets(obj, expected):
-    assert inference.is_list_like(obj, allow_sets=False) == expected
-
-
 def test_is_array_like():
     assert inference.is_array_like(Series([]))
     assert inference.is_array_like(Series([1, 2]))