TST/REF: collect tests by method

pandas/conftest.py

@@ -34,7 +34,7 @@
 import pandas.util._test_decorators as td
 
 import pandas as pd
-from pandas import DataFrame
+from pandas import DataFrame, Series
 import pandas._testing as tm
 from pandas.core import ops
 from pandas.core.indexes.api import Index, MultiIndex
@@ -529,6 +529,23 @@ def series_with_simple_index(index):
     return _create_series(index)
 
 
+@pytest.fixture
+def series_with_multilevel_index():
+    """
+    Fixture with a Series with a 2-level MultiIndex.
+    """
+    arrays = [
+        ["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"],
+        ["one", "two", "one", "two", "one", "two", "one", "two"],
+    ]
+    tuples = zip(*arrays)
+    index = MultiIndex.from_tuples(tuples)
+    data = np.random.randn(8)
+    ser = Series(data, index=index)
+    ser[3] = np.NaN
+    return ser
+
+
 _narrow_dtypes = [
     np.float16,
     np.float32,

pandas/tests/frame/methods/test_count.py

@@ -6,6 +6,24 @@
 
 
 class TestDataFrameCount:
+    def test_count_multiindex(self, multiindex_dataframe_random_data):
+        frame = multiindex_dataframe_random_data
+
+        frame = frame.copy()
+        frame.index.names = ["a", "b"]
+
+        result = frame.count(level="b")
+        expected = frame.count(level=1)
+        tm.assert_frame_equal(result, expected, check_names=False)
+
+        result = frame.count(level="a")
+        expected = frame.count(level=0)
+        tm.assert_frame_equal(result, expected, check_names=False)
+
+        msg = "Level x not found"
+        with pytest.raises(KeyError, match=msg):
+            frame.count(level="x")
+
     def test_count(self):
         # corner case
         frame = DataFrame()

pandas/tests/frame/methods/test_reset_index.py

@@ -1,8 +1,11 @@
 from datetime import datetime
+from itertools import product
 
 import numpy as np
 import pytest
 
+from pandas.core.dtypes.common import is_float_dtype, is_integer_dtype
+
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -301,6 +304,194 @@ def test_reset_index_range(self):
         )
         tm.assert_frame_equal(result, expected)
 
+    def test_reset_index_multiindex_columns(self):
+        levels = [["A", ""], ["B", "b"]]
+        df = DataFrame([[0, 2], [1, 3]], columns=MultiIndex.from_tuples(levels))
+        result = df[["B"]].rename_axis("A").reset_index()
+        tm.assert_frame_equal(result, df)
+
+        # GH#16120: already existing column
+        msg = r"cannot insert \('A', ''\), already exists"
+        with pytest.raises(ValueError, match=msg):
+            df.rename_axis("A").reset_index()
+
+        # GH#16164: multiindex (tuple) full key
+        result = df.set_index([("A", "")]).reset_index()
+        tm.assert_frame_equal(result, df)
+
+        # with additional (unnamed) index level
+        idx_col = DataFrame(
+            [[0], [1]], columns=MultiIndex.from_tuples([("level_0", "")])
+        )
+        expected = pd.concat([idx_col, df[[("B", "b"), ("A", "")]]], axis=1)
+        result = df.set_index([("B", "b")], append=True).reset_index()
+        tm.assert_frame_equal(result, expected)
+
+        # with index name which is a too long tuple...
+        msg = "Item must have length equal to number of levels."
+        with pytest.raises(ValueError, match=msg):
+            df.rename_axis([("C", "c", "i")]).reset_index()
+
+        # or too short...
+        levels = [["A", "a", ""], ["B", "b", "i"]]
+        df2 = DataFrame([[0, 2], [1, 3]], columns=MultiIndex.from_tuples(levels))
+        idx_col = DataFrame(
+            [[0], [1]], columns=MultiIndex.from_tuples([("C", "c", "ii")])
+        )
+        expected = pd.concat([idx_col, df2], axis=1)
+        result = df2.rename_axis([("C", "c")]).reset_index(col_fill="ii")
+        tm.assert_frame_equal(result, expected)
+
+        # ... which is incompatible with col_fill=None
+        with pytest.raises(
+            ValueError,
+            match=(
+                "col_fill=None is incompatible with "
+                r"incomplete column name \('C', 'c'\)"
+            ),
+        ):
+            df2.rename_axis([("C", "c")]).reset_index(col_fill=None)
+
+        # with col_level != 0
+        result = df2.rename_axis([("c", "ii")]).reset_index(col_level=1, col_fill="C")
+        tm.assert_frame_equal(result, expected)
+
+    def test_reset_index_datetime(self, tz_naive_fixture):
+        # GH#3950
+        tz = tz_naive_fixture
+        idx1 = pd.date_range("1/1/2011", periods=5, freq="D", tz=tz, name="idx1")
+        idx2 = Index(range(5), name="idx2", dtype="int64")
+        idx = MultiIndex.from_arrays([idx1, idx2])
+        df = DataFrame(
+            {"a": np.arange(5, dtype="int64"), "b": ["A", "B", "C", "D", "E"]},
+            index=idx,
+        )
+
+        expected = DataFrame(
+            {
+                "idx1": [
+                    datetime(2011, 1, 1),
+                    datetime(2011, 1, 2),
+                    datetime(2011, 1, 3),
+                    datetime(2011, 1, 4),
+                    datetime(2011, 1, 5),
+                ],
+                "idx2": np.arange(5, dtype="int64"),
+                "a": np.arange(5, dtype="int64"),
+                "b": ["A", "B", "C", "D", "E"],
+            },
+            columns=["idx1", "idx2", "a", "b"],
+        )
+        expected["idx1"] = expected["idx1"].apply(lambda d: Timestamp(d, tz=tz))
+
+        tm.assert_frame_equal(df.reset_index(), expected)
+
+        idx3 = pd.date_range(
+            "1/1/2012", periods=5, freq="MS", tz="Europe/Paris", name="idx3"
+        )
+        idx = MultiIndex.from_arrays([idx1, idx2, idx3])
+        df = DataFrame(
+            {"a": np.arange(5, dtype="int64"), "b": ["A", "B", "C", "D", "E"]},
+            index=idx,
+        )
+
+        expected = DataFrame(
+            {
+                "idx1": [
+                    datetime(2011, 1, 1),
+                    datetime(2011, 1, 2),
+                    datetime(2011, 1, 3),
+                    datetime(2011, 1, 4),
+                    datetime(2011, 1, 5),
+                ],
+                "idx2": np.arange(5, dtype="int64"),
+                "idx3": [
+                    datetime(2012, 1, 1),
+                    datetime(2012, 2, 1),
+                    datetime(2012, 3, 1),
+                    datetime(2012, 4, 1),
+                    datetime(2012, 5, 1),
+                ],
+                "a": np.arange(5, dtype="int64"),
+                "b": ["A", "B", "C", "D", "E"],
+            },
+            columns=["idx1", "idx2", "idx3", "a", "b"],
+        )
+        expected["idx1"] = expected["idx1"].apply(lambda d: Timestamp(d, tz=tz))
+        expected["idx3"] = expected["idx3"].apply(
+            lambda d: Timestamp(d, tz="Europe/Paris")
+        )
+        tm.assert_frame_equal(df.reset_index(), expected)
+
+        # GH#7793
+        idx = MultiIndex.from_product(
+            [["a", "b"], pd.date_range("20130101", periods=3, tz=tz)]
+        )
+        df = DataFrame(
+            np.arange(6, dtype="int64").reshape(6, 1), columns=["a"], index=idx
+        )
+
+        expected = DataFrame(
+            {
+                "level_0": "a a a b b b".split(),
+                "level_1": [
+                    datetime(2013, 1, 1),
+                    datetime(2013, 1, 2),
+                    datetime(2013, 1, 3),
+                ]
+                * 2,
+                "a": np.arange(6, dtype="int64"),
+            },
+            columns=["level_0", "level_1", "a"],
+        )
+        expected["level_1"] = expected["level_1"].apply(
+            lambda d: Timestamp(d, freq="D", tz=tz)
+        )
+        result = df.reset_index()
+        tm.assert_frame_equal(result, expected)
+
+    def test_reset_index_period(self):
+        # GH#7746
+        idx = MultiIndex.from_product(
+            [pd.period_range("20130101", periods=3, freq="M"), list("abc")],
+            names=["month", "feature"],
+        )
+
+        df = DataFrame(
+            np.arange(9, dtype="int64").reshape(-1, 1), index=idx, columns=["a"]
+        )
+        expected = DataFrame(
+            {
+                "month": (
+                    [pd.Period("2013-01", freq="M")] * 3
+                    + [pd.Period("2013-02", freq="M")] * 3
+                    + [pd.Period("2013-03", freq="M")] * 3
+                ),
+                "feature": ["a", "b", "c"] * 3,
+                "a": np.arange(9, dtype="int64"),
+            },
+            columns=["month", "feature", "a"],
+        )
+        result = df.reset_index()
+        tm.assert_frame_equal(result, expected)
+
+    def test_reset_index_delevel_infer_dtype(self):
+        tuples = list(product(["foo", "bar"], [10, 20], [1.0, 1.1]))
+        index = MultiIndex.from_tuples(tuples, names=["prm0", "prm1", "prm2"])
+        df = DataFrame(np.random.randn(8, 3), columns=["A", "B", "C"], index=index)
+        deleveled = df.reset_index()
+        assert is_integer_dtype(deleveled["prm1"])
+        assert is_float_dtype(deleveled["prm2"])
+
+    def test_reset_index_with_drop(
+        self, multiindex_year_month_day_dataframe_random_data
+    ):
+        ymd = multiindex_year_month_day_dataframe_random_data
+
+        deleveled = ymd.reset_index(drop=True)
+        assert len(deleveled.columns) == len(ymd.columns)
+        assert deleveled.index.name == ymd.index.name
+
 
 @pytest.mark.parametrize(
     "array, dtype",

pandas/tests/frame/methods/test_set_index.py

@@ -17,6 +17,17 @@
 
 
 class TestSetIndex:
+    def test_set_index_multiindex(self):
+        # segfault in GH#3308
+        d = {"t1": [2, 2.5, 3], "t2": [4, 5, 6]}
+        df = DataFrame(d)
+        tuples = [(0, 1), (0, 2), (1, 2)]
+        df["tuples"] = tuples
+
+        index = MultiIndex.from_tuples(df["tuples"])
+        # it works!
+        df.set_index(index)
+
     def test_set_index_empty_column(self):
         # GH#1971
         df = DataFrame(

pandas/tests/frame/methods/test_sort_index.py

@@ -2,7 +2,15 @@
 import pytest
 
 import pandas as pd
-from pandas import CategoricalDtype, DataFrame, Index, IntervalIndex, MultiIndex, Series
+from pandas import (
+    CategoricalDtype,
+    DataFrame,
+    Index,
+    IntervalIndex,
+    MultiIndex,
+    Series,
+    Timestamp,
+)
 import pandas._testing as tm
 
 
@@ -668,6 +676,66 @@ def test_sort_index_preserve_levels(self, multiindex_dataframe_random_data):
         result = frame.sort_index()
         assert result.index.names == frame.index.names
 
+    @pytest.mark.parametrize(
+        "gen,extra",
+        [
+            ([1.0, 3.0, 2.0, 5.0], 4.0),
+            ([1, 3, 2, 5], 4),
+            (
+                [
+                    Timestamp("20130101"),
+                    Timestamp("20130103"),
+                    Timestamp("20130102"),
+                    Timestamp("20130105"),
+                ],
+                Timestamp("20130104"),
+            ),
+            (["1one", "3one", "2one", "5one"], "4one"),
+        ],
+    )
+    def test_sort_index_multilevel_repr_8017(self, gen, extra):
+
+        np.random.seed(0)
+        data = np.random.randn(3, 4)
+
+        columns = MultiIndex.from_tuples([("red", i) for i in gen])
+        df = DataFrame(data, index=list("def"), columns=columns)
+        df2 = pd.concat(
+            [
+                df,
+                DataFrame(
+                    "world",
+                    index=list("def"),
+                    columns=MultiIndex.from_tuples([("red", extra)]),
+                ),
+            ],
+            axis=1,
+        )
+
+        # check that the repr is good
+        # make sure that we have a correct sparsified repr
+        # e.g. only 1 header of read
+        assert str(df2).splitlines()[0].split() == ["red"]
+
+        # GH 8017
+        # sorting fails after columns added
+
+        # construct single-dtype then sort
+        result = df.copy().sort_index(axis=1)
+        expected = df.iloc[:, [0, 2, 1, 3]]
+        tm.assert_frame_equal(result, expected)
+
+        result = df2.sort_index(axis=1)
+        expected = df2.iloc[:, [0, 2, 1, 4, 3]]
+        tm.assert_frame_equal(result, expected)
+
+        # setitem then sort
+        result = df.copy()
+        result[("red", extra)] = "world"
+
+        result = result.sort_index(axis=1)
+        tm.assert_frame_equal(result, expected)
+
 
 class TestDataFrameSortIndexKey:
     def test_sort_multi_index_key(self):