Add docstrings to fixtures

Author: h-vetinari

pandas/tests/frame/conftest.py

@@ -14,16 +14,40 @@
 
 @pytest.fixture
 def frame():
+    """
+    Fixture for DataFrame of floats with index of unique strings
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: float_frame_string_index
+
+    Columns are ['A', 'B', 'C', 'D'], see pandas.util.testing.getSeriesData
+    """
     return DataFrame(tm.getSeriesData())
 
 
 @pytest.fixture
 def frame2():
+    """
+    Fixture for DataFrame of floats with index of unique strings
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: float_frame_string_index2
+
+    Columns are ['D', 'C', 'B', 'A']. See pandas.util.testing.getSeriesData
+    """
     return DataFrame(tm.getSeriesData(), columns=['D', 'C', 'B', 'A'])
 
 
 @pytest.fixture
 def intframe():
+    """
+    Fixture for DataFrame of ints with index of unique strings
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: int_frame
+
+    Columns are ['A', 'B', 'C', 'D']. See pandas.util.testing.getSeriesData
+    """
     df = DataFrame({k: v.astype(int)
                    for k, v in compat.iteritems(tm.getSeriesData())})
     # force these all to int64 to avoid platform testing issues
@@ -32,18 +56,43 @@ def intframe():
 
 @pytest.fixture
 def tsframe():
+    """
+    Fixture for DataFrame of floats with DatetimeIndex
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: float_frame_datetime_index
+
+    Columns are ['A', 'B', 'C', 'D']. See pandas.util.testing.getTimeSeriesData
+    """
     return DataFrame(tm.getTimeSeriesData())
 
 
 @pytest.fixture
 def mixed_frame():
+    """
+    Fixture for DataFrame of floats and strings with string index
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: float_string_frame
+
+    Columns are ['A', 'B', 'C', 'D', 'foo'].
+    See pandas.util.testing.getSeriesData
+    """
     df = DataFrame(tm.getSeriesData())
     df['foo'] = 'bar'
     return df
 
 
 @pytest.fixture
 def mixed_float():
+    """
+    Fixture for DataFrame of different float types with string index
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: mixed_float_frame
+
+    Columns are ['A', 'B', 'C', 'D']. See pandas.util.testing.getSeriesData
+    """
     df = DataFrame(tm.getSeriesData())
     df.A = df.A.astype('float16')
     df.B = df.B.astype('float32')
@@ -53,6 +102,14 @@ def mixed_float():
 
 @pytest.fixture
 def mixed_float2():
+    """
+    Fixture for DataFrame of different float types with string index
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: mixed_float_frame2
+
+    Columns are ['A', 'B', 'C', 'D']. See pandas.util.testing.getSeriesData
+    """
     df = DataFrame(tm.getSeriesData())
     df.D = df.D.astype('float16')
     df.C = df.C.astype('float32')
@@ -62,6 +119,14 @@ def mixed_float2():
 
 @pytest.fixture
 def mixed_int():
+    """
+    Fixture for DataFrame of different int types with string index
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: mixed_int_frame
+
+    Columns are ['A', 'B', 'C', 'D']. See pandas.util.testing.getSeriesData
+    """
     df = DataFrame({k: v.astype(int)
                    for k, v in compat.iteritems(tm.getSeriesData())})
     df.A = df.A.astype('uint8')
@@ -73,6 +138,14 @@ def mixed_int():
 
 @pytest.fixture
 def all_mixed():
+    """
+    Fixture for DataFrame of float/int/string columns
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: float_int_string_frame
+
+    Columns are ['a', 'b', 'c', 'float32', 'int32'].
+    """
     return DataFrame({'a': 1., 'b': 2, 'c': 'foo',
                       'float32': np.array([1.] * 10, dtype='float32'),
                       'int32': np.array([1] * 10, dtype='int32')},
@@ -81,6 +154,14 @@ def all_mixed():
 
 @pytest.fixture
 def tzframe():
+    """
+    Fixture for DataFrame of date_range Series with different timezones
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: timezone_frame
+
+    Columns are ['A', 'B', 'C']; some entries are missing
+    """
     df = DataFrame({'A': date_range('20130101', periods=3),
                     'B': date_range('20130101', periods=3,
                                     tz='US/Eastern'),
@@ -93,21 +174,51 @@ def tzframe():
 
 @pytest.fixture
 def empty():
+    """
+    Fixture for empty DataFrame
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: empty_frame
+    """
     return DataFrame({})
 
 
 @pytest.fixture
 def ts1():
+    """
+    Fixture for Series of floats with DatetimeIndex
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: datetime_series
+
+    See pandas.util.testing.makeTimeSeries
+    """
     return tm.makeTimeSeries(nper=30)
 
 
 @pytest.fixture
 def ts2():
+    """
+    Fixture for Series of floats with DatetimeIndex
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: datetime_series_short
+
+    See pandas.util.testing.makeTimeSeries
+    """
     return tm.makeTimeSeries(nper=30)[5:]
 
 
 @pytest.fixture
 def simple():
+    """
+    Fixture for simple 3x3 DataFrame
+
+    After completing the fixturization of the frame tests (GH 22471), this
+    fixture will be renamed to: simple_frame
+
+    Columns are ['one', 'two', 'three'], index is ['a', 'b', 'c'].
+    """
     arr = np.array([[1., 2., 3.],
                     [4., 5., 6.],
                     [7., 8., 9.]])
@@ -118,6 +229,12 @@ def simple():
 
 @pytest.fixture
 def frame_of_index_cols():
+    """
+    Fixture for DataFrame of columns that can be used for indexing
+
+    Columns are ['A', 'B', 'C', 'D', 'E']; 'A' & 'B' contain duplicates,
+    the rest are unique.
+    """
     df = DataFrame({'A': ['foo', 'foo', 'foo', 'bar', 'bar'],
                     'B': ['one', 'two', 'three', 'one', 'two'],
                     'C': ['a', 'b', 'c', 'd', 'e'],