get rid of float_frame_with_na fixture

pandas/tests/frame/conftest.py

@@ -15,20 +15,6 @@ def float_frame():
     return DataFrame(tm.getSeriesData())
 
 
-@pytest.fixture
-def float_frame_with_na():
-    """
-    Fixture for DataFrame of floats with index of unique strings
-
-    Columns are ['A', 'B', 'C', 'D']; some entries are missing
-    """
-    df = DataFrame(tm.getSeriesData())
-    # set some NAs
-    df.loc[5:10] = np.nan
-    df.loc[15:20, -2:] = np.nan
-    return df
-
-
 @pytest.fixture
 def bool_frame_with_na():
     """

pandas/tests/frame/test_analytics.py

@@ -709,7 +709,9 @@ def test_reduce_mixed_frame(self):
                                     np.array([2, 150, 'abcde'], dtype=object))
         tm.assert_series_equal(test, df.T.sum(axis=1))
 
-    def test_count(self, float_frame_with_na, float_frame, float_string_frame):
+    def test_count(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         f = lambda s: notna(s).sum()
         assert_stat_op_calc('count', f, float_frame_with_na, has_skipna=False,
                             check_dtype=False, check_dates=True)
@@ -740,8 +742,9 @@ def test_count(self, float_frame_with_na, float_frame, float_string_frame):
         expected = Series(0, index=[])
         tm.assert_series_equal(result, expected)
 
-    def test_nunique(self, float_frame_with_na, float_frame,
-                     float_string_frame):
+    def test_nunique(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         f = lambda s: len(algorithms.unique1d(s.dropna()))
         assert_stat_op_calc('nunique', f, float_frame_with_na,
                             has_skipna=False, check_dtype=False,
@@ -758,8 +761,9 @@ def test_nunique(self, float_frame_with_na, float_frame,
         tm.assert_series_equal(df.nunique(axis=1, dropna=False),
                                Series({0: 1, 1: 3, 2: 2}))
 
-    def test_sum(self, float_frame_with_na, mixed_float_frame,
-                 float_frame, float_string_frame):
+    def test_sum(self, mixed_float_frame, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         assert_stat_op_api('sum', float_frame, float_string_frame,
                            has_numeric_only=True)
         assert_stat_op_calc('sum', np.sum, float_frame_with_na,
@@ -792,20 +796,24 @@ def test_stat_operators_attempt_obj_array(self, method):
             if method in ['sum', 'prod']:
                 tm.assert_series_equal(result, expected)
 
-    def test_mean(self, float_frame_with_na, float_frame, float_string_frame):
+    def test_mean(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         assert_stat_op_calc('mean', np.mean, float_frame_with_na,
                             check_dates=True)
         assert_stat_op_api('mean', float_frame, float_string_frame)
 
-    def test_product(self, float_frame_with_na, float_frame,
-                     float_string_frame):
+    def test_product(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         assert_stat_op_calc('product', np.prod, float_frame_with_na)
         assert_stat_op_api('product', float_frame, float_string_frame)
 
     # TODO: Ensure warning isn't emitted in the first place
     @pytest.mark.filterwarnings("ignore:All-NaN:RuntimeWarning")
-    def test_median(self, float_frame_with_na, float_frame,
-                    float_string_frame):
+    def test_median(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         def wrapper(x):
             if isna(x).any():
                 return np.nan
@@ -815,8 +823,9 @@ def wrapper(x):
                             check_dates=True)
         assert_stat_op_api('median', float_frame, float_string_frame)
 
-    def test_min(self, float_frame_with_na, int_frame,
-                 float_frame, float_string_frame):
+    def test_min(self, int_frame, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         with warnings.catch_warnings(record=True):
             warnings.simplefilter("ignore", RuntimeWarning)
             assert_stat_op_calc('min', np.min, float_frame_with_na,
@@ -874,8 +883,9 @@ def test_cummax(self):
         cummax_xs = datetime_frame.cummax(axis=1)
         assert np.shape(cummax_xs) == np.shape(datetime_frame)
 
-    def test_max(self, float_frame_with_na, int_frame,
-                 float_frame, float_string_frame):
+    def test_max(self, int_frame, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         with warnings.catch_warnings(record=True):
             warnings.simplefilter("ignore", RuntimeWarning)
             assert_stat_op_calc('max', np.max, float_frame_with_na,
@@ -884,12 +894,14 @@ def test_max(self, float_frame_with_na, int_frame,
         assert_stat_op_api('max', float_frame, float_string_frame)
 
     def test_mad(self, float_frame_with_na, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         f = lambda x: np.abs(x - x.mean()).mean()
         assert_stat_op_calc('mad', f, float_frame_with_na)
         assert_stat_op_api('mad', float_frame, float_string_frame)
 
-    def test_var_std(self, float_frame_with_na, float_frame,
-                     float_string_frame):
+    def test_var_std(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
         datetime_frame = DataFrame(tm.getTimeSeriesData())
 
         alt = lambda x: np.var(x, ddof=1)
@@ -1013,7 +1025,8 @@ def test_cumprod(self):
         df.cumprod(0)
         df.cumprod(1)
 
-    def test_sem(self, float_frame_with_na, float_frame, float_string_frame):
+    def test_sem(self, float_frame, float_string_frame):
+        float_frame_with_na = tm.get_float_frame_with_na()
         datetime_frame = DataFrame(tm.getTimeSeriesData())
 
         alt = lambda x: np.std(x, ddof=1) / np.sqrt(len(x))
@@ -1034,9 +1047,11 @@ def test_sem(self, float_frame_with_na, float_frame, float_string_frame):
             assert not (result < 0).any()
 
     @td.skip_if_no_scipy
-    def test_skew(self, float_frame_with_na, float_frame, float_string_frame):
+    def test_skew(self, float_frame, float_string_frame):
         from scipy.stats import skew
 
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         def alt(x):
             if len(x) < 3:
                 return np.nan
@@ -1046,9 +1061,11 @@ def alt(x):
         assert_stat_op_api('skew', float_frame, float_string_frame)
 
     @td.skip_if_no_scipy
-    def test_kurt(self, float_frame_with_na, float_frame, float_string_frame):
+    def test_kurt(self, float_frame, float_string_frame):
         from scipy.stats import kurtosis
 
+        float_frame_with_na = tm.get_float_frame_with_na()
+
         def alt(x):
             if len(x) < 4:
                 return np.nan