Issue #33161 - Use empty_frame fixture

pandas/tests/frame/indexing/test_indexing.py

@@ -22,11 +22,13 @@
 )
 import pandas._testing as tm
 from pandas.arrays import SparseArray
+from pandas.conftest import empty_frame
 import pandas.core.common as com
 from pandas.core.indexing import IndexingError
 
 from pandas.tseries.offsets import BDay
 
+
 # We pass through a TypeError raised by numpy
 _slice_msg = "slice indices must be integers or None or have an __index__ method"
 
@@ -842,7 +844,7 @@ def test_setitem_with_empty_listlike(self):
 
     def test_setitem_scalars_no_index(self):
         # GH16823 / 17894
-        df = DataFrame()
+        df = empty_frame()
         df["foo"] = 1
         expected = DataFrame(columns=["foo"]).astype(np.int64)
         tm.assert_frame_equal(df, expected)
@@ -1669,7 +1671,7 @@ def test_reindex_subclass(self):
         class MyDataFrame(DataFrame):
             pass
 
-        expected = DataFrame()
+        expected = empty_frame()
         df = MyDataFrame()
         result = df.reindex_like(expected)
 

pandas/tests/frame/indexing/test_insert.py

@@ -8,6 +8,7 @@
 
 from pandas import DataFrame, Index
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameInsert:
@@ -58,7 +59,7 @@ def test_insert_column_bug_4032(self):
 
     def test_insert_with_columns_dups(self):
         # GH#14291
-        df = DataFrame()
+        df = empty_frame()
         df.insert(0, "A", ["g", "h", "i"], allow_duplicates=True)
         df.insert(0, "A", ["d", "e", "f"], allow_duplicates=True)
         df.insert(0, "A", ["a", "b", "c"], allow_duplicates=True)

pandas/tests/frame/methods/test_append.py

@@ -4,12 +4,13 @@
 import pandas as pd
 from pandas import DataFrame, Series, Timestamp
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameAppend:
     def test_append_empty_list(self):
         # GH 28769
-        df = DataFrame()
+        df = empty_frame()
         result = df.append([])
         expected = df
         tm.assert_frame_equal(result, expected)
@@ -96,29 +97,29 @@ def test_append_missing_cols(self):
     def test_append_empty_dataframe(self):
 
         # Empty df append empty df
-        df1 = DataFrame()
-        df2 = DataFrame()
+        df1 = empty_frame()
+        df2 = empty_frame()
         result = df1.append(df2)
         expected = df1.copy()
         tm.assert_frame_equal(result, expected)
 
         # Non-empty df append empty df
         df1 = DataFrame(np.random.randn(5, 2))
-        df2 = DataFrame()
+        df2 = empty_frame()
         result = df1.append(df2)
         expected = df1.copy()
         tm.assert_frame_equal(result, expected)
 
         # Empty df with columns append empty df
         df1 = DataFrame(columns=["bar", "foo"])
-        df2 = DataFrame()
+        df2 = empty_frame()
         result = df1.append(df2)
         expected = df1.copy()
         tm.assert_frame_equal(result, expected)
 
         # Non-Empty df with columns append empty df
         df1 = DataFrame(np.random.randn(5, 2), columns=["bar", "foo"])
-        df2 = DataFrame()
+        df2 = empty_frame()
         result = df1.append(df2)
         expected = df1.copy()
         tm.assert_frame_equal(result, expected)
@@ -130,7 +131,7 @@ def test_append_dtypes(self):
         # can sometimes infer the correct type
 
         df1 = DataFrame({"bar": Timestamp("20130101")}, index=range(5))
-        df2 = DataFrame()
+        df2 = empty_frame()
         result = df1.append(df2)
         expected = df1.copy()
         tm.assert_frame_equal(result, expected)

pandas/tests/frame/methods/test_combine_first.py

@@ -6,6 +6,7 @@
 import pandas as pd
 from pandas import DataFrame, Index, Series
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameCombineFirst:
@@ -73,7 +74,7 @@ def test_combine_first(self, float_frame):
         comb = float_frame.combine_first(DataFrame())
         tm.assert_frame_equal(comb, float_frame)
 
-        comb = DataFrame().combine_first(float_frame)
+        comb = empty_frame().combine_first(float_frame)
         tm.assert_frame_equal(comb, float_frame)
 
         comb = float_frame.combine_first(DataFrame(index=["faz", "boo"]))

pandas/tests/frame/methods/test_count.py

@@ -1,11 +1,12 @@
 from pandas import DataFrame, Series
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameCount:
     def test_count(self):
         # corner case
-        frame = DataFrame()
+        frame = empty_frame()
         ct1 = frame.count(1)
         assert isinstance(ct1, Series)
 
@@ -23,7 +24,7 @@ def test_count(self):
         expected = Series(0, index=df.columns)
         tm.assert_series_equal(result, expected)
 
-        df = DataFrame()
+        df = empty_frame()
         result = df.count()
         expected = Series(0, index=[])
         tm.assert_series_equal(result, expected)

pandas/tests/frame/methods/test_filter.py

@@ -4,6 +4,7 @@
 import pandas as pd
 from pandas import DataFrame
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameFilter:
@@ -122,7 +123,7 @@ def test_filter_bytestring(self, name):
         tm.assert_frame_equal(df.filter(regex=name), expected)
 
     def test_filter_corner(self):
-        empty = DataFrame()
+        empty = empty_frame()
 
         result = empty.filter([])
         tm.assert_frame_equal(result, empty)

pandas/tests/frame/methods/test_head_tail.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-from pandas import DataFrame
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 def test_head_tail(float_frame):
@@ -25,6 +25,6 @@ def test_head_tail(float_frame):
     tm.assert_frame_equal(df.head(-1), df.iloc[:-1])
     tm.assert_frame_equal(df.tail(-1), df.iloc[1:])
     # test empty dataframe
-    empty_df = DataFrame()
+    empty_df = empty_frame()
     tm.assert_frame_equal(empty_df.tail(), empty_df)
     tm.assert_frame_equal(empty_df.head(), empty_df)

pandas/tests/frame/methods/test_isin.py

@@ -4,6 +4,7 @@
 import pandas as pd
 from pandas import DataFrame, MultiIndex, Series
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameIsIn:
@@ -176,7 +177,7 @@ def test_isin_empty_datetimelike(self):
         df1_ts = DataFrame({"date": pd.to_datetime(["2014-01-01", "2014-01-02"])})
         df1_td = DataFrame({"date": [pd.Timedelta(1, "s"), pd.Timedelta(2, "s")]})
         df2 = DataFrame({"date": []})
-        df3 = DataFrame()
+        df3 = empty_frame()
 
         expected = DataFrame({"date": [False, False]})
 

pandas/tests/frame/methods/test_round.py

@@ -4,14 +4,15 @@
 import pandas as pd
 from pandas import DataFrame, Series, date_range
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameRound:
     def test_round(self):
         # GH#2665
 
         # Test that rounding an empty DataFrame does nothing
-        df = DataFrame()
+        df = empty_frame()
         tm.assert_frame_equal(df, df.round())
 
         # Here's the test frame we'll be working with

pandas/tests/frame/test_analytics.py

@@ -21,6 +21,7 @@
     to_timedelta,
 )
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 import pandas.core.algorithms as algorithms
 import pandas.core.nanops as nanops
 
@@ -754,10 +755,10 @@ def test_operators_timedelta64(self):
         assert df["off2"].dtype == "timedelta64[ns]"
 
     def test_sum_corner(self):
-        empty_frame = DataFrame()
+        empty_frame_ = empty_frame()
 
-        axis0 = empty_frame.sum(0)
-        axis1 = empty_frame.sum(1)
+        axis0 = empty_frame_.sum(0)
+        axis1 = empty_frame_.sum(1)
         assert isinstance(axis0, Series)
         assert isinstance(axis1, Series)
         assert len(axis0) == 0

pandas/tests/frame/test_api.py

@@ -11,6 +11,7 @@
 import pandas as pd
 from pandas import Categorical, DataFrame, Series, compat, date_range, timedelta_range
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 
 
 class TestDataFrameMisc:
@@ -118,14 +119,14 @@ def test_tab_completion(self):
         assert isinstance(df.__getitem__("A"), pd.DataFrame)
 
     def test_not_hashable(self):
-        empty_frame = DataFrame()
+        empty_frame_ = empty_frame()
 
         df = DataFrame([1])
         msg = "'DataFrame' objects are mutable, thus they cannot be hashed"
         with pytest.raises(TypeError, match=msg):
             hash(df)
         with pytest.raises(TypeError, match=msg):
-            hash(empty_frame)
+            hash(empty_frame_)
 
     def test_column_name_contains_unicode_surrogate(self):
         # GH 25509
@@ -162,8 +163,8 @@ def test_get_agg_axis(self, float_frame):
             float_frame._get_agg_axis(2)
 
     def test_nonzero(self, float_frame, float_string_frame):
-        empty_frame = DataFrame()
-        assert empty_frame.empty
+        empty_frame_ = empty_frame()
+        assert empty_frame_.empty
 
         assert not float_frame.empty
         assert not float_string_frame.empty

pandas/tests/frame/test_apply.py

@@ -12,6 +12,7 @@
 import pandas as pd
 from pandas import DataFrame, MultiIndex, Series, Timestamp, date_range, notna
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 from pandas.core.apply import frame_apply
 from pandas.core.base import SpecificationError
 
@@ -74,12 +75,12 @@ def test_apply_mixed_datetimelike(self):
 
     def test_apply_empty(self, float_frame):
         # empty
-        empty_frame = DataFrame()
+        empty_frame_ = empty_frame()
 
-        applied = empty_frame.apply(np.sqrt)
+        applied = empty_frame_.apply(np.sqrt)
         assert applied.empty
 
-        applied = empty_frame.apply(np.mean)
+        applied = empty_frame_.apply(np.mean)
         assert applied.empty
 
         no_rows = float_frame[:0]
@@ -99,7 +100,7 @@ def test_apply_empty(self, float_frame):
 
     def test_apply_with_reduce_empty(self):
         # reduce with an empty DataFrame
-        empty_frame = DataFrame()
+        empty_frame = empty_frame()
 
         x = []
         result = empty_frame.apply(x.append, axis=1, result_type="expand")
@@ -760,7 +761,7 @@ def test_with_dictlike_columns(self):
         tm.assert_series_equal(result, expected)
 
         # GH 18775
-        df = DataFrame()
+        df = empty_frame()
         df["author"] = ["X", "Y", "Z"]
         df["publisher"] = ["BBC", "NBC", "N24"]
         df["date"] = pd.to_datetime(

pandas/tests/frame/test_arithmetic.py

@@ -10,6 +10,7 @@
 import pandas as pd
 from pandas import DataFrame, MultiIndex, Series
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 import pandas.core.common as com
 from pandas.tests.frame.common import _check_mixed_float, _check_mixed_int
 
@@ -990,13 +991,13 @@ def test_combineFrame(self, float_frame, mixed_float_frame, mixed_int_frame):
         # corner cases
 
         # empty
-        plus_empty = float_frame + DataFrame()
+        plus_empty = float_frame + empty_frame()
         assert np.isnan(plus_empty.values).all()
 
-        empty_plus = DataFrame() + float_frame
+        empty_plus = empty_frame() + float_frame
         assert np.isnan(empty_plus.values).all()
 
-        empty_empty = DataFrame() + DataFrame()
+        empty_empty = empty_frame() + empty_frame()
         assert empty_empty.empty
 
         # out of order
@@ -1116,7 +1117,7 @@ def test_combineFunc(self, float_frame, mixed_float_frame):
             tm.assert_numpy_array_equal(s.values, mixed_float_frame[c].values * 2)
         _check_mixed_float(result, dtype=dict(C=None))
 
-        result = DataFrame() * 2
+        result = empty_frame() * 2
         assert result.index.equals(DataFrame().index)
         assert len(result.columns) == 0
 

pandas/tests/frame/test_block_internals.py

@@ -16,10 +16,12 @@
     option_context,
 )
 import pandas._testing as tm
+from pandas.conftest import empty_frame
 from pandas.core.arrays import IntervalArray, integer_array
 from pandas.core.internals import ObjectBlock
 from pandas.core.internals.blocks import IntBlock
 
+
 # Segregated collection of methods that require the BlockManager internal data
 # structure
 
@@ -345,7 +347,7 @@ def test_copy(self, float_frame, float_string_frame):
         assert copy._data is not float_string_frame._data
 
     def test_pickle(self, float_string_frame, timezone_frame):
-        empty_frame = DataFrame()
+        empty_frame_ = empty_frame()
 
         unpickled = tm.round_trip_pickle(float_string_frame)
         tm.assert_frame_equal(float_string_frame, unpickled)
@@ -354,7 +356,7 @@ def test_pickle(self, float_string_frame, timezone_frame):
         float_string_frame._data.ndim
 
         # empty
-        unpickled = tm.round_trip_pickle(empty_frame)
+        unpickled = tm.round_trip_pickle(empty_frame_)
         repr(unpickled)
 
         # tz frame