Consistent naming of parameters

Author: h-vetinari

pandas/tests/frame/test_analytics.py

@@ -25,22 +25,22 @@
 import pandas.util._test_decorators as td
 
 
-def _check_stat_op(name, alternative, main_frame, float_frame,
+def _check_stat_op(opname, alternative, main_frame, float_frame,
                    float_string_frame, has_skipna=True,
                    has_numeric_only=False, check_dtype=True,
                    check_dates=False, check_less_precise=False,
                    skipna_alternative=None):
 
-    f = getattr(main_frame, name)
+    f = getattr(main_frame, opname)
 
     if check_dates:
         df = DataFrame({'b': date_range('1/1/2001', periods=2)})
-        _f = getattr(df, name)
+        _f = getattr(df, opname)
         result = _f()
         assert isinstance(result, Series)
 
         df['a'] = lrange(len(df))
-        result = getattr(df, name)()
+        result = getattr(df, opname)()
         assert isinstance(result, Series)
         assert len(result)
 
@@ -67,7 +67,7 @@ def wrapper(x):
     tm.assert_series_equal(result0, main_frame.apply(skipna_wrapper),
                            check_dtype=check_dtype,
                            check_less_precise=check_less_precise)
-    if name in ['sum', 'prod']:
+    if opname in ['sum', 'prod']:
         expected = main_frame.apply(skipna_wrapper, axis=1)
         tm.assert_series_equal(result1, expected, check_dtype=False,
                                check_less_precise=check_less_precise)
@@ -84,30 +84,30 @@ def wrapper(x):
     # all NA case
     if has_skipna:
         all_na = float_frame * np.NaN
-        r0 = getattr(all_na, name)(axis=0)
-        r1 = getattr(all_na, name)(axis=1)
-        if name in ['sum', 'prod']:
-            unit = int(name == 'prod')
+        r0 = getattr(all_na, opname)(axis=0)
+        r1 = getattr(all_na, opname)(axis=1)
+        if opname in ['sum', 'prod']:
+            unit = int(opname == 'prod')
             expected = pd.Series(unit, index=r0.index, dtype=r0.dtype)
             tm.assert_series_equal(r0, expected)
             expected = pd.Series(unit, index=r1.index, dtype=r1.dtype)
             tm.assert_series_equal(r1, expected)
 
     # make sure works on mixed-type frame
-    getattr(float_string_frame, name)(axis=0)
-    getattr(float_string_frame, name)(axis=1)
+    getattr(float_string_frame, opname)(axis=0)
+    getattr(float_string_frame, opname)(axis=1)
 
     if has_numeric_only:
-        getattr(float_string_frame, name)(axis=0, numeric_only=True)
-        getattr(float_string_frame, name)(axis=1, numeric_only=True)
-        getattr(float_frame, name)(axis=0, numeric_only=False)
-        getattr(float_frame, name)(axis=1, numeric_only=False)
+        getattr(float_string_frame, opname)(axis=0, numeric_only=True)
+        getattr(float_string_frame, opname)(axis=1, numeric_only=True)
+        getattr(float_frame, opname)(axis=0, numeric_only=False)
+        getattr(float_frame, opname)(axis=1, numeric_only=False)
 
 
-def _check_bool_op(name, alternative, frame, float_string_frame,
+def _check_bool_op(opname, alternative, main_frame, float_string_frame,
                    has_skipna=True, has_bool_only=False):
 
-    f = getattr(frame, name)
+    f = getattr(main_frame, opname)
 
     if has_skipna:
         def skipna_wrapper(x):
@@ -119,28 +119,28 @@ def wrapper(x):
 
         result0 = f(axis=0, skipna=False)
         result1 = f(axis=1, skipna=False)
-        tm.assert_series_equal(result0, frame.apply(wrapper))
-        tm.assert_series_equal(result1, frame.apply(wrapper, axis=1),
+        tm.assert_series_equal(result0, main_frame.apply(wrapper))
+        tm.assert_series_equal(result1, main_frame.apply(wrapper, axis=1),
                                check_dtype=False)  # HACK: win32
     else:
         skipna_wrapper = alternative
         wrapper = alternative
 
     result0 = f(axis=0)
     result1 = f(axis=1)
-    tm.assert_series_equal(result0, frame.apply(skipna_wrapper))
-    tm.assert_series_equal(result1, frame.apply(skipna_wrapper, axis=1),
+    tm.assert_series_equal(result0, main_frame.apply(skipna_wrapper))
+    tm.assert_series_equal(result1, main_frame.apply(skipna_wrapper, axis=1),
                            check_dtype=False)
 
     # bad axis
     pytest.raises(ValueError, f, axis=2)
 
     # all NA case
     if has_skipna:
-        all_na = frame * np.NaN
-        r0 = getattr(all_na, name)(axis=0)
-        r1 = getattr(all_na, name)(axis=1)
-        if name == 'any':
+        all_na = main_frame * np.NaN
+        r0 = getattr(all_na, opname)(axis=0)
+        r1 = getattr(all_na, opname)(axis=1)
+        if opname == 'any':
             assert not r0.any()
             assert not r1.any()
         else:
@@ -150,8 +150,8 @@ def wrapper(x):
     # make sure works on mixed-type frame
     mixed = float_string_frame
     mixed['_bool_'] = np.random.randn(len(mixed)) > 0
-    getattr(mixed, name)(axis=0)
-    getattr(mixed, name)(axis=1)
+    getattr(mixed, opname)(axis=0)
+    getattr(mixed, opname)(axis=1)
 
     class NonzeroFail(object):
 
@@ -161,10 +161,10 @@ def __nonzero__(self):
     mixed['_nonzero_fail_'] = NonzeroFail()
 
     if has_bool_only:
-        getattr(mixed, name)(axis=0, bool_only=True)
-        getattr(mixed, name)(axis=1, bool_only=True)
-        getattr(frame, name)(axis=0, bool_only=False)
-        getattr(frame, name)(axis=1, bool_only=False)
+        getattr(mixed, opname)(axis=0, bool_only=True)
+        getattr(mixed, opname)(axis=1, bool_only=True)
+        getattr(main_frame, opname)(axis=0, bool_only=False)
+        getattr(main_frame, opname)(axis=1, bool_only=False)
 
 
 class TestDataFrameAnalytics():