DOC: Added docstrings to fixtures defined in array module (#47211)

Author: melissawm

pandas/tests/arrays/boolean/test_arithmetic.py

@@ -9,6 +9,7 @@
 
 @pytest.fixture
 def data():
+    """Fixture returning boolean array with valid and missing values."""
     return pd.array(
         [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
         dtype="boolean",
@@ -17,11 +18,13 @@ def data():
 
 @pytest.fixture
 def left_array():
+    """Fixture returning boolean array with valid and missing values."""
     return pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
 
 
 @pytest.fixture
 def right_array():
+    """Fixture returning boolean array with valid and missing values."""
     return pd.array([True, False, None] * 3, dtype="boolean")
 
 

pandas/tests/arrays/boolean/test_comparison.py

@@ -9,6 +9,7 @@
 
 @pytest.fixture
 def data():
+    """Fixture returning boolean array with valid and missing data"""
     return pd.array(
         [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
         dtype="boolean",
@@ -17,6 +18,7 @@ def data():
 
 @pytest.fixture
 def dtype():
+    """Fixture returning BooleanDtype"""
     return pd.BooleanDtype()
 
 

pandas/tests/arrays/boolean/test_reduction.py

@@ -6,6 +6,7 @@
 
 @pytest.fixture
 def data():
+    """Fixture returning boolean array, with valid and missing values."""
     return pd.array(
         [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
         dtype="boolean",

pandas/tests/arrays/categorical/conftest.py

@@ -11,4 +11,5 @@ def allow_fill(request):
 
 @pytest.fixture
 def factor():
+    """Fixture returning  a Categorical object"""
     return Categorical(["a", "b", "b", "a", "a", "c", "c", "c"], ordered=True)

pandas/tests/arrays/datetimes/test_reductions.py

@@ -12,6 +12,7 @@
 class TestReductions:
     @pytest.fixture
     def arr1d(self, tz_naive_fixture):
+        """Fixture returning DatetimeArray with parametrized timezones"""
         tz = tz_naive_fixture
         dtype = DatetimeTZDtype(tz=tz) if tz is not None else np.dtype("M8[ns]")
         arr = DatetimeArray._from_sequence(

pandas/tests/arrays/floating/conftest.py

@@ -10,11 +10,13 @@
 
 @pytest.fixture(params=[Float32Dtype, Float64Dtype])
 def dtype(request):
+    """Parametrized fixture returning a float 'dtype'"""
     return request.param()
 
 
 @pytest.fixture
 def data(dtype):
+    """Fixture returning 'data' array according to parametrized float 'dtype'"""
     return pd.array(
         list(np.arange(0.1, 0.9, 0.1))
         + [pd.NA]
@@ -27,12 +29,19 @@ def data(dtype):
 
 @pytest.fixture
 def data_missing(dtype):
+    """
+    Fixture returning array with missing data according to parametrized float
+    'dtype'.
+    """
     return pd.array([np.nan, 0.1], dtype=dtype)
 
 
 @pytest.fixture(params=["data", "data_missing"])
 def all_data(request, data, data_missing):
-    """Parametrized fixture giving 'data' and 'data_missing'"""
+    """Parametrized fixture returning 'data' or 'data_missing' float arrays.
+
+    Used to test dtype conversion with and without missing values.
+    """
     if request.param == "data":
         return data
     elif request.param == "data_missing":

pandas/tests/arrays/integer/conftest.py

@@ -27,11 +27,18 @@
     ]
 )
 def dtype(request):
+    """Parametrized fixture returning integer 'dtype'"""
     return request.param()
 
 
 @pytest.fixture
 def data(dtype):
+    """
+    Fixture returning 'data' array with valid and missing values according to
+    parametrized integer 'dtype'.
+
+    Used to test dtype conversion with and without missing values.
+    """
     return pd.array(
         list(range(8)) + [np.nan] + list(range(10, 98)) + [np.nan] + [99, 100],
         dtype=dtype,
@@ -40,12 +47,21 @@ def data(dtype):
 
 @pytest.fixture
 def data_missing(dtype):
+    """
+    Fixture returning array with exactly one NaN and one valid integer,
+    according to parametrized integer 'dtype'.
+
+    Used to test dtype conversion with and without missing values.
+    """
     return pd.array([np.nan, 1], dtype=dtype)
 
 
 @pytest.fixture(params=["data", "data_missing"])
 def all_data(request, data, data_missing):
-    """Parametrized fixture giving 'data' and 'data_missing'"""
+    """Parametrized fixture returning 'data' or 'data_missing' integer arrays.
+
+    Used to test dtype conversion with and without missing values.
+    """
     if request.param == "data":
         return data
     elif request.param == "data_missing":

pandas/tests/arrays/integer/test_construction.py

@@ -14,6 +14,10 @@
 
 @pytest.fixture(params=[pd.array, IntegerArray._from_sequence])
 def constructor(request):
+    """Fixture returning parametrized IntegerArray from given sequence.
+
+    Used to test dtype conversions.
+    """
     return request.param
 
 

pandas/tests/arrays/masked/test_arithmetic.py

@@ -21,6 +21,11 @@
 
 @pytest.fixture(params=zip(arrays, scalars), ids=[a.dtype.name for a in arrays])
 def data(request):
+    """Fixture returning parametrized (array, scalar) tuple.
+
+    Used to test equivalence of scalars, numpy arrays with array ops, and the
+    equivalence of DataFrame and Series ops.
+    """
     return request.param
 
 

pandas/tests/arrays/masked/test_arrow_compat.py

@@ -15,6 +15,10 @@
 
 @pytest.fixture(params=arrays, ids=[a.dtype.name for a in arrays])
 def data(request):
+    """
+    Fixture returning parametrized array from given dtype, including integer,
+    float and boolean
+    """
     return request.param
 
 
@@ -101,6 +105,10 @@ def test_arrow_sliced(data):
 
 @pytest.fixture
 def np_dtype_to_arrays(any_real_numpy_dtype):
+    """
+    Fixture returning actual and expected dtype, pandas and numpy arrays and
+    mask from a given numpy dtype
+    """
     np_dtype = np.dtype(any_real_numpy_dtype)
     pa_type = pa.from_numpy_dtype(np_dtype)