Convert more tests

pandas-dev · jreback · Jul 3, 2019 · Jun 30, 2019 · Jun 30, 2019 · Jun 30, 2019
commit 592659f0ce190979e3d16f6814c3b66ffe50190d
diff --git a/pandas/tests/frame/test_missing.py b/pandas/tests/frame/test_missing.py
@@ -407,15 +407,13 @@ def test_fillna_downcast(self):
     def test_fillna_dtype_conversion(self):
         # make sure that fillna on an empty frame works
         df = DataFrame(index=["A", "B", "C"], columns=[1, 2, 3, 4, 5])
-        result = Series(df._data.get_dtype_counts()).sort_values()
-        expected = Series({'object': 5})
+        result = df.dtypes
+        expected = Series([np.dtype('object')] * 5, index=[1, 2, 3, 4, 5])
         assert_series_equal(result, expected)
 
         result = df.fillna(1)
         expected = DataFrame(1, index=["A", "B", "C"], columns=[1, 2, 3, 4, 5])
-        result = Series(result._data.get_dtype_counts()).sort_values()
-        expected = Series({'int64': 5})
-        assert_series_equal(result, expected)
+        assert_frame_equal(result, expected)
 
         # empty block
         df = DataFrame(index=range(3), columns=['A', 'B'], dtype='float64')

diff --git a/pandas/tests/io/pytables/test_pytables.py b/pandas/tests/io/pytables/test_pytables.py
@@ -1985,9 +1985,8 @@ def test_table_values_dtypes_roundtrip(self):
             df1['time2'] = Timestamp('20130102')
 
             store.append('df_mixed_dtypes1', df1)
-            result = Series(
-                store.select('df_mixed_dtypes1')._data.get_dtype_counts()
-            )
+            result = store.select('df_mixed_dtypes1').dtypes.value_counts()
+            result.index = [str(i) for i in result.index]
             expected = Series({'float32': 2, 'float64': 1, 'int32': 1,
                                'bool': 1, 'int16': 1, 'int8': 1,
                                'int64': 1, 'object': 1, 'datetime64[ns]': 2})

diff --git a/pandas/tests/reshape/test_pivot.py b/pandas/tests/reshape/test_pivot.py
@@ -245,8 +245,9 @@ def test_pivot_dtypes(self):
 
         z = pivot_table(f, values='v', index=['a'], columns=[
                         'i'], fill_value=0, aggfunc=np.sum)
-        result = Series(z._data.get_dtype_counts())
-        expected = Series(dict(int64=2))
+        result = z.dtypes
+        expected = Series([np.dtype('int64')] * 2,
+                          index=Index(list('ab'), name='i'))
         tm.assert_series_equal(result, expected)
 
         # cannot convert dtypes
@@ -256,8 +257,9 @@ def test_pivot_dtypes(self):
 
         z = pivot_table(f, values='v', index=['a'], columns=[
                         'i'], fill_value=0, aggfunc=np.mean)
-        result = Series(z._data.get_dtype_counts())
-        expected = Series(dict(float64=2))
+        result = z.dtypes
+        expected = Series([np.dtype('float64')] * 2,
+                          index=Index(list('ab'), name='i'))
         tm.assert_series_equal(result, expected)
 
     @pytest.mark.parametrize('columns,values',

diff --git a/pandas/tests/reshape/test_reshape.py b/pandas/tests/reshape/test_reshape.py
@@ -101,21 +101,20 @@ def test_basic_types(self, sparse, dtype):
             dtype_name = self.effective_dtype(dtype).name
 
         expected = Series({dtype_name: 8})
-        tm.assert_series_equal(Series(result._data.get_dtype_counts()),
-                               expected)
+        result = result.dtypes.value_counts()
+        result.index = [str(i) for i in result.index]
+        tm.assert_series_equal(result, expected)
 
         result = get_dummies(s_df, columns=['a'], sparse=sparse, dtype=dtype)
 
         expected_counts = {'int64': 1, 'object': 1}
         expected_counts[dtype_name] = 3 + expected_counts.get(dtype_name, 0)
 
         expected = Series(expected_counts).sort_index()
-        tm.assert_series_equal(
-            Series(
-                result._data.get_dtype_counts()
-            ).sort_index(),
-            expected
-        )
+        result = result.dtypes.value_counts()
+        result.index = [str(i) for i in result.index]
+        result = result.sort_index()
+        tm.assert_series_equal(result, expected)
 
     def test_just_na(self, sparse):
         just_na_list = [np.nan]