Parameterize all rank methods for pct=True

- Added frame and series tests for all methods
- method='dense' remains the only change method

Author: rouzazari

pandas/tests/frame/test_rank.py

@@ -6,6 +6,8 @@
 
 from pandas import Series, DataFrame
 
+import pytest
+
 from pandas.compat import product
 from pandas.util.testing import assert_frame_equal
 import pandas.util.testing as tm
@@ -218,15 +220,6 @@ def test_rank_methods_frame(self):
                         expected = expected.astype('float64')
                     tm.assert_frame_equal(result, expected)
 
-    def test_rank_dense_method(self):
-        # GH15630, pct should be on 100% basis even when method='dense'
-        df = DataFrame([['2012', 'B', 3], ['2012', 'A', 2], ['2012', 'A', 1]])
-        result = df.rank(method='dense', pct=True)
-        expected = DataFrame([[1., 1., 1.],
-                              [1., 0.5, 2. / 3],
-                              [1., 0.5, 1. / 3]])
-        assert_frame_equal(result, expected)
-
     def test_rank_descending(self):
         dtypes = ['O', 'f8', 'i8']
 
@@ -276,3 +269,56 @@ def _check2d(df, expected, method='average', axis=0):
                 continue
             frame = df if dtype is None else df.astype(dtype)
             _check2d(frame, results[method], method=method, axis=axis)
+
+
+# GH15630, pct should be on 100% basis when method='dense'
+@pytest.mark.parametrize('frame, exp', [
+    ([['2012', 'B', 3], ['2012', 'A', 2], ['2012', 'A', 1]],
+        [[1., 1., 1.], [1., 0.5, 2. / 3], [1., 0.5, 1. / 3]])])
+def test_rank_dense_pct(frame, exp):
+    df = DataFrame(frame)
+    result = df.rank(method='dense', pct=True)
+    expected = DataFrame(exp)
+    assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize('frame, exp', [
+    ([['2012', 'B', 3], ['2012', 'A', 2], ['2012', 'A', 1]],
+        [[1. / 3, 1., 1.], [1. / 3, 1. / 3, 2. / 3],
+         [1. / 3, 1. / 3, 1. / 3]])])
+def test_rank_min_pct(frame, exp):
+    df = DataFrame(frame)
+    result = df.rank(method='min', pct=True)
+    expected = DataFrame(exp)
+    assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize('frame, exp', [
+    ([['2012', 'B', 3], ['2012', 'A', 2], ['2012', 'A', 1]],
+        [[1., 1., 1.], [1., 2. / 3, 2. / 3], [1., 2. / 3, 1. / 3]])])
+def test_rank_max_pct(frame, exp):
+    df = DataFrame(frame)
+    result = df.rank(method='max', pct=True)
+    expected = DataFrame(exp)
+    assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize('frame, exp', [
+    ([['2012', 'B', 3], ['2012', 'A', 2], ['2012', 'A', 1]],
+        [[2. / 3, 1., 1.], [2. / 3, 0.5, 2. / 3], [2. / 3, 0.5, 1. / 3]])])
+def test_rank_average_pct(frame, exp):
+    df = DataFrame(frame)
+    result = df.rank(method='average', pct=True)
+    expected = DataFrame(exp)
+    assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize('frame, exp', [
+    ([[2012, 66, 3], [2012, 65, 2], [2012, 65, 1]],
+        [[1. / 3, 1., 1.], [2. / 3, 1. / 3, 2. / 3],
+         [3. / 3, 2. / 3, 1. / 3]])])
+def test_rank_first_pct(frame, exp):
+    df = DataFrame(frame)
+    result = df.rank(method='first', pct=True)
+    expected = DataFrame(exp)
+    assert_frame_equal(result, expected)

pandas/tests/series/test_rank.py

@@ -324,21 +324,94 @@ def test_rank_object_bug(self):
         Series([np.nan] * 32).astype(object).rank(ascending=False)
 
 
+# GH15630, pct should be on 100% basis when method='dense'
+
 @pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
 @pytest.mark.parametrize('ser, exp', [
     ([1], [1.]),
-    ([2], [1.]),
-    ([0], [1.]),
+    ([1, 2], [1. / 2, 2. / 2]),
     ([2, 2], [1., 1.]),
     ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
+    ([1, 2, 2], [1. / 2, 2. / 2, 2. / 2]),
     ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
     ([1, 1, 5, 5, 3], [1. / 3, 1. / 3, 3. / 3, 3. / 3, 2. / 3]),
+    ([1, 1, 3, 3, 5, 5], [1. / 3, 1. / 3, 2. / 3, 2. / 3, 3. / 3, 3. / 3]),
     ([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
-def test_rank_pct(dtype, ser, exp):
-        # GH15630, pct should be on 100% basis even when method='dense'
-        # TODO: add other methods (i.e. 'average', 'min', 'max', 'first')
-
+def test_rank_dense_pct(dtype, ser, exp):
         s = Series(ser).astype(dtype)
         result = s.rank(method='dense', pct=True)
         expected = Series(exp).astype(result.dtype)
         assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
+@pytest.mark.parametrize('ser, exp', [
+    ([1], [1.]),
+    ([1, 2], [1. / 2, 2. / 2]),
+    ([2, 2], [1. / 2, 1. / 2]),
+    ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
+    ([1, 2, 2], [1. / 3, 2. / 3, 2. / 3]),
+    ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
+    ([1, 1, 5, 5, 3], [1. / 5, 1. / 5, 4. / 5, 4. / 5, 3. / 5]),
+    ([1, 1, 3, 3, 5, 5], [1. / 6, 1. / 6, 3. / 6, 3. / 6, 5. / 6, 5. / 6]),
+    ([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
+def test_rank_min_pct(dtype, ser, exp):
+        s = Series(ser).astype(dtype)
+        result = s.rank(method='min', pct=True)
+        expected = Series(exp).astype(result.dtype)
+        assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
+@pytest.mark.parametrize('ser, exp', [
+    ([1], [1.]),
+    ([1, 2], [1. / 2, 2. / 2]),
+    ([2, 2], [1., 1.]),
+    ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
+    ([1, 2, 2], [1. / 3, 3. / 3, 3. / 3]),
+    ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
+    ([1, 1, 5, 5, 3], [2. / 5, 2. / 5, 5. / 5, 5. / 5, 3. / 5]),
+    ([1, 1, 3, 3, 5, 5], [2. / 6, 2. / 6, 4. / 6, 4. / 6, 6. / 6, 6. / 6]),
+    ([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
+def test_rank_max_pct(dtype, ser, exp):
+        s = Series(ser).astype(dtype)
+        result = s.rank(method='max', pct=True)
+        expected = Series(exp).astype(result.dtype)
+        assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
+@pytest.mark.parametrize('ser, exp', [
+    ([1], [1.]),
+    ([1, 2], [1. / 2, 2. / 2]),
+    ([2, 2], [1.5 / 2, 1.5 / 2]),
+    ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
+    ([1, 2, 2], [1. / 3, 2.5 / 3, 2.5 / 3]),
+    ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
+    ([1, 1, 5, 5, 3], [1.5 / 5, 1.5 / 5, 4.5 / 5, 4.5 / 5, 3. / 5]),
+    ([1, 1, 3, 3, 5, 5],
+     [1.5 / 6, 1.5 / 6, 3.5 / 6, 3.5 / 6, 5.5 / 6, 5.5 / 6]),
+    ([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
+def test_rank_average_pct(dtype, ser, exp):
+        s = Series(ser).astype(dtype)
+        result = s.rank(method='average', pct=True)
+        expected = Series(exp).astype(result.dtype)
+        assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize('dtype', ['f8', 'i8'])
+@pytest.mark.parametrize('ser, exp', [
+    ([1], [1.]),
+    ([1, 2], [1. / 2, 2. / 2]),
+    ([2, 2], [1. / 2, 2. / 2.]),
+    ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
+    ([1, 2, 2], [1. / 3, 2. / 3, 3. / 3]),
+    ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
+    ([1, 1, 5, 5, 3], [1. / 5, 2. / 5, 4. / 5, 5. / 5, 3. / 5]),
+    ([1, 1, 3, 3, 5, 5], [1. / 6, 2. / 6, 3. / 6, 4. / 6, 5. / 6, 6. / 6]),
+    ([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
+def test_rank_first_pct(dtype, ser, exp):
+        s = Series(ser).astype(dtype)
+        result = s.rank(method='first', pct=True)
+        expected = Series(exp).astype(result.dtype)
+        assert_series_equal(result, expected)