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llmeval-env/lib/python3.10/site-packages/pandas/tests/frame/methods/test_add_prefix_suffix.py

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+import pytest
+
+from pandas import Index
+import pandas._testing as tm
+
+
+def test_add_prefix_suffix(float_frame):
+    with_prefix = float_frame.add_prefix("foo#")
+    expected = Index([f"foo#{c}" for c in float_frame.columns])
+    tm.assert_index_equal(with_prefix.columns, expected)
+
+    with_suffix = float_frame.add_suffix("#foo")
+    expected = Index([f"{c}#foo" for c in float_frame.columns])
+    tm.assert_index_equal(with_suffix.columns, expected)
+
+    with_pct_prefix = float_frame.add_prefix("%")
+    expected = Index([f"%{c}" for c in float_frame.columns])
+    tm.assert_index_equal(with_pct_prefix.columns, expected)
+
+    with_pct_suffix = float_frame.add_suffix("%")
+    expected = Index([f"{c}%" for c in float_frame.columns])
+    tm.assert_index_equal(with_pct_suffix.columns, expected)
+
+
+def test_add_prefix_suffix_axis(float_frame):
+    # GH 47819
+    with_prefix = float_frame.add_prefix("foo#", axis=0)
+    expected = Index([f"foo#{c}" for c in float_frame.index])
+    tm.assert_index_equal(with_prefix.index, expected)
+
+    with_prefix = float_frame.add_prefix("foo#", axis=1)
+    expected = Index([f"foo#{c}" for c in float_frame.columns])
+    tm.assert_index_equal(with_prefix.columns, expected)
+
+    with_pct_suffix = float_frame.add_suffix("#foo", axis=0)
+    expected = Index([f"{c}#foo" for c in float_frame.index])
+    tm.assert_index_equal(with_pct_suffix.index, expected)
+
+    with_pct_suffix = float_frame.add_suffix("#foo", axis=1)
+    expected = Index([f"{c}#foo" for c in float_frame.columns])
+    tm.assert_index_equal(with_pct_suffix.columns, expected)
+
+
+def test_add_prefix_suffix_invalid_axis(float_frame):
+    with pytest.raises(ValueError, match="No axis named 2 for object type DataFrame"):
+        float_frame.add_prefix("foo#", axis=2)
+
+    with pytest.raises(ValueError, match="No axis named 2 for object type DataFrame"):
+        float_frame.add_suffix("foo#", axis=2)

llmeval-env/lib/python3.10/site-packages/pandas/tests/frame/methods/test_asfreq.py

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+from datetime import datetime
+
+import numpy as np
+import pytest
+
+from pandas._libs.tslibs.offsets import MonthEnd
+
+from pandas import (
+    DataFrame,
+    DatetimeIndex,
+    Series,
+    date_range,
+    period_range,
+    to_datetime,
+)
+import pandas._testing as tm
+
+from pandas.tseries import offsets
+
+
+class TestAsFreq:
+    @pytest.fixture(params=["s", "ms", "us", "ns"])
+    def unit(self, request):
+        return request.param
+
+    def test_asfreq2(self, frame_or_series):
+        ts = frame_or_series(
+            [0.0, 1.0, 2.0],
+            index=DatetimeIndex(
+                [
+                    datetime(2009, 10, 30),
+                    datetime(2009, 11, 30),
+                    datetime(2009, 12, 31),
+                ],
+                dtype="M8[ns]",
+                freq="BME",
+            ),
+        )
+
+        daily_ts = ts.asfreq("B")
+        monthly_ts = daily_ts.asfreq("BME")
+        tm.assert_equal(monthly_ts, ts)
+
+        daily_ts = ts.asfreq("B", method="pad")
+        monthly_ts = daily_ts.asfreq("BME")
+        tm.assert_equal(monthly_ts, ts)
+
+        daily_ts = ts.asfreq(offsets.BDay())
+        monthly_ts = daily_ts.asfreq(offsets.BMonthEnd())
+        tm.assert_equal(monthly_ts, ts)
+
+        result = ts[:0].asfreq("ME")
+        assert len(result) == 0
+        assert result is not ts
+
+        if frame_or_series is Series:
+            daily_ts = ts.asfreq("D", fill_value=-1)
+            result = daily_ts.value_counts().sort_index()
+            expected = Series(
+                [60, 1, 1, 1], index=[-1.0, 2.0, 1.0, 0.0], name="count"
+            ).sort_index()
+            tm.assert_series_equal(result, expected)
+
+    def test_asfreq_datetimeindex_empty(self, frame_or_series):
+        # GH#14320
+        index = DatetimeIndex(["2016-09-29 11:00"])
+        expected = frame_or_series(index=index, dtype=object).asfreq("h")
+        result = frame_or_series([3], index=index.copy()).asfreq("h")
+        tm.assert_index_equal(expected.index, result.index)
+
+    @pytest.mark.parametrize("tz", ["US/Eastern", "dateutil/US/Eastern"])
+    def test_tz_aware_asfreq_smoke(self, tz, frame_or_series):
+        dr = date_range("2011-12-01", "2012-07-20", freq="D", tz=tz)
+
+        obj = frame_or_series(
+            np.random.default_rng(2).standard_normal(len(dr)), index=dr
+        )
+
+        # it works!
+        obj.asfreq("min")
+
+    def test_asfreq_normalize(self, frame_or_series):
+        rng = date_range("1/1/2000 09:30", periods=20)
+        norm = date_range("1/1/2000", periods=20)
+
+        vals = np.random.default_rng(2).standard_normal((20, 3))
+
+        obj = DataFrame(vals, index=rng)
+        expected = DataFrame(vals, index=norm)
+        if frame_or_series is Series:
+            obj = obj[0]
+            expected = expected[0]
+
+        result = obj.asfreq("D", normalize=True)
+        tm.assert_equal(result, expected)
+
+    def test_asfreq_keep_index_name(self, frame_or_series):
+        # GH#9854
+        index_name = "bar"
+        index = date_range("20130101", periods=20, name=index_name)
+        obj = DataFrame(list(range(20)), columns=["foo"], index=index)
+        obj = tm.get_obj(obj, frame_or_series)
+
+        assert index_name == obj.index.name
+        assert index_name == obj.asfreq("10D").index.name
+
+    def test_asfreq_ts(self, frame_or_series):
+        index = period_range(freq="Y", start="1/1/2001", end="12/31/2010")
+        obj = DataFrame(
+            np.random.default_rng(2).standard_normal((len(index), 3)), index=index
+        )
+        obj = tm.get_obj(obj, frame_or_series)
+
+        result = obj.asfreq("D", how="end")
+        exp_index = index.asfreq("D", how="end")
+        assert len(result) == len(obj)
+        tm.assert_index_equal(result.index, exp_index)
+
+        result = obj.asfreq("D", how="start")
+        exp_index = index.asfreq("D", how="start")
+        assert len(result) == len(obj)
+        tm.assert_index_equal(result.index, exp_index)
+
+    def test_asfreq_resample_set_correct_freq(self, frame_or_series):
+        # GH#5613
+        # we test if .asfreq() and .resample() set the correct value for .freq
+        dti = to_datetime(["2012-01-01", "2012-01-02", "2012-01-03"])
+        obj = DataFrame({"col": [1, 2, 3]}, index=dti)
+        obj = tm.get_obj(obj, frame_or_series)
+
+        # testing the settings before calling .asfreq() and .resample()
+        assert obj.index.freq is None
+        assert obj.index.inferred_freq == "D"
+
+        # does .asfreq() set .freq correctly?
+        assert obj.asfreq("D").index.freq == "D"
+
+        # does .resample() set .freq correctly?
+        assert obj.resample("D").asfreq().index.freq == "D"
+
+    def test_asfreq_empty(self, datetime_frame):
+        # test does not blow up on length-0 DataFrame
+        zero_length = datetime_frame.reindex([])
+        result = zero_length.asfreq("BME")
+        assert result is not zero_length
+
+    def test_asfreq(self, datetime_frame):
+        offset_monthly = datetime_frame.asfreq(offsets.BMonthEnd())
+        rule_monthly = datetime_frame.asfreq("BME")
+
+        tm.assert_frame_equal(offset_monthly, rule_monthly)
+
+        rule_monthly.asfreq("B", method="pad")
+        # TODO: actually check that this worked.
+
+        # don't forget!
+        rule_monthly.asfreq("B", method="pad")
+
+    def test_asfreq_datetimeindex(self):
+        df = DataFrame(
+            {"A": [1, 2, 3]},
+            index=[datetime(2011, 11, 1), datetime(2011, 11, 2), datetime(2011, 11, 3)],
+        )
+        df = df.asfreq("B")
+        assert isinstance(df.index, DatetimeIndex)
+
+        ts = df["A"].asfreq("B")
+        assert isinstance(ts.index, DatetimeIndex)
+
+    def test_asfreq_fillvalue(self):
+        # test for fill value during upsampling, related to issue 3715
+
+        # setup
+        rng = date_range("1/1/2016", periods=10, freq="2s")
+        # Explicit cast to 'float' to avoid implicit cast when setting None
+        ts = Series(np.arange(len(rng)), index=rng, dtype="float")
+        df = DataFrame({"one": ts})
+
+        # insert pre-existing missing value
+        df.loc["2016-01-01 00:00:08", "one"] = None
+
+        actual_df = df.asfreq(freq="1s", fill_value=9.0)
+        expected_df = df.asfreq(freq="1s").fillna(9.0)
+        expected_df.loc["2016-01-01 00:00:08", "one"] = None
+        tm.assert_frame_equal(expected_df, actual_df)
+
+        expected_series = ts.asfreq(freq="1s").fillna(9.0)
+        actual_series = ts.asfreq(freq="1s", fill_value=9.0)
+        tm.assert_series_equal(expected_series, actual_series)
+
+    def test_asfreq_with_date_object_index(self, frame_or_series):
+        rng = date_range("1/1/2000", periods=20)
+        ts = frame_or_series(np.random.default_rng(2).standard_normal(20), index=rng)
+
+        ts2 = ts.copy()
+        ts2.index = [x.date() for x in ts2.index]
+
+        result = ts2.asfreq("4h", method="ffill")
+        expected = ts.asfreq("4h", method="ffill")
+        tm.assert_equal(result, expected)
+
+    def test_asfreq_with_unsorted_index(self, frame_or_series):
+        # GH#39805
+        # Test that rows are not dropped when the datetime index is out of order
+        index = to_datetime(["2021-01-04", "2021-01-02", "2021-01-03", "2021-01-01"])
+        result = frame_or_series(range(4), index=index)
+
+        expected = result.reindex(sorted(index))
+        expected.index = expected.index._with_freq("infer")
+
+        result = result.asfreq("D")
+        tm.assert_equal(result, expected)
+
+    def test_asfreq_after_normalize(self, unit):
+        # https://github.com/pandas-dev/pandas/issues/50727
+        result = DatetimeIndex(
+            date_range("2000", periods=2).as_unit(unit).normalize(), freq="D"
+        )
+        expected = DatetimeIndex(["2000-01-01", "2000-01-02"], freq="D").as_unit(unit)
+        tm.assert_index_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "freq, freq_half",
+        [
+            ("2ME", "ME"),
+            (MonthEnd(2), MonthEnd(1)),
+        ],
+    )
+    def test_asfreq_2ME(self, freq, freq_half):
+        index = date_range("1/1/2000", periods=6, freq=freq_half)
+        df = DataFrame({"s": Series([0.0, 1.0, 2.0, 3.0, 4.0, 5.0], index=index)})
+        expected = df.asfreq(freq=freq)
+
+        index = date_range("1/1/2000", periods=3, freq=freq)
+        result = DataFrame({"s": Series([0.0, 2.0, 4.0], index=index)})
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "freq, freq_depr",
+        [
+            ("2ME", "2M"),
+            ("2QE", "2Q"),
+            ("2QE-SEP", "2Q-SEP"),
+            ("1BQE", "1BQ"),
+            ("2BQE-SEP", "2BQ-SEP"),
+            ("1YE", "1Y"),
+            ("2YE-MAR", "2Y-MAR"),
+            ("1YE", "1A"),
+            ("2YE-MAR", "2A-MAR"),
+            ("2BYE-MAR", "2BA-MAR"),
+        ],
+    )
+    def test_asfreq_frequency_M_Q_Y_A_deprecated(self, freq, freq_depr):
+        # GH#9586, #55978
+        depr_msg = f"'{freq_depr[1:]}' is deprecated and will be removed "
+        f"in a future version, please use '{freq[1:]}' instead."
+
+        index = date_range("1/1/2000", periods=4, freq=f"{freq[1:]}")
+        df = DataFrame({"s": Series([0.0, 1.0, 2.0, 3.0], index=index)})
+        expected = df.asfreq(freq=freq)
+        with tm.assert_produces_warning(FutureWarning, match=depr_msg):
+            result = df.asfreq(freq=freq_depr)
+        tm.assert_frame_equal(result, expected)