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| import numpy as np
| import pytest
|
| from pandas import (
| DataFrame,
| NaT,
| Series,
| Timedelta,
| Timestamp,
| date_range,
| )
| import pandas._testing as tm
|
|
| def test_group_shift_with_null_key():
| # This test is designed to replicate the segfault in issue #13813.
| n_rows = 1200
|
| # Generate a moderately large dataframe with occasional missing
| # values in column `B`, and then group by [`A`, `B`]. This should
| # force `-1` in `labels` array of `g._grouper.group_info` exactly
| # at those places, where the group-by key is partially missing.
| df = DataFrame(
| [(i % 12, i % 3 if i % 3 else np.nan, i) for i in range(n_rows)],
| dtype=float,
| columns=["A", "B", "Z"],
| index=None,
| )
| g = df.groupby(["A", "B"])
|
| expected = DataFrame(
| [(i + 12 if i % 3 and i < n_rows - 12 else np.nan) for i in range(n_rows)],
| dtype=float,
| columns=["Z"],
| index=None,
| )
| result = g.shift(-1)
|
| tm.assert_frame_equal(result, expected)
|
|
| def test_group_shift_with_fill_value():
| # GH #24128
| n_rows = 24
| df = DataFrame(
| [(i % 12, i % 3, i) for i in range(n_rows)],
| dtype=float,
| columns=["A", "B", "Z"],
| index=None,
| )
| g = df.groupby(["A", "B"])
|
| expected = DataFrame(
| [(i + 12 if i < n_rows - 12 else 0) for i in range(n_rows)],
| dtype=float,
| columns=["Z"],
| index=None,
| )
| result = g.shift(-1, fill_value=0)
|
| tm.assert_frame_equal(result, expected)
|
|
| def test_group_shift_lose_timezone():
| # GH 30134
| now_dt = Timestamp.utcnow().as_unit("ns")
| df = DataFrame({"a": [1, 1], "date": now_dt})
| result = df.groupby("a").shift(0).iloc[0]
| expected = Series({"date": now_dt}, name=result.name)
| tm.assert_series_equal(result, expected)
|
|
| def test_group_diff_real_series(any_real_numpy_dtype):
| df = DataFrame(
| {"a": [1, 2, 3, 3, 2], "b": [1, 2, 3, 4, 5]},
| dtype=any_real_numpy_dtype,
| )
| result = df.groupby("a")["b"].diff()
| exp_dtype = "float"
| if any_real_numpy_dtype in ["int8", "int16", "float32"]:
| exp_dtype = "float32"
| expected = Series([np.nan, np.nan, np.nan, 1.0, 3.0], dtype=exp_dtype, name="b")
| tm.assert_series_equal(result, expected)
|
|
| def test_group_diff_real_frame(any_real_numpy_dtype):
| df = DataFrame(
| {
| "a": [1, 2, 3, 3, 2],
| "b": [1, 2, 3, 4, 5],
| "c": [1, 2, 3, 4, 6],
| },
| dtype=any_real_numpy_dtype,
| )
| result = df.groupby("a").diff()
| exp_dtype = "float"
| if any_real_numpy_dtype in ["int8", "int16", "float32"]:
| exp_dtype = "float32"
| expected = DataFrame(
| {
| "b": [np.nan, np.nan, np.nan, 1.0, 3.0],
| "c": [np.nan, np.nan, np.nan, 1.0, 4.0],
| },
| dtype=exp_dtype,
| )
| tm.assert_frame_equal(result, expected)
|
|
| @pytest.mark.parametrize(
| "data",
| [
| [
| Timestamp("2013-01-01"),
| Timestamp("2013-01-02"),
| Timestamp("2013-01-03"),
| ],
| [Timedelta("5 days"), Timedelta("6 days"), Timedelta("7 days")],
| ],
| )
| def test_group_diff_datetimelike(data, unit):
| df = DataFrame({"a": [1, 2, 2], "b": data})
| df["b"] = df["b"].dt.as_unit(unit)
| result = df.groupby("a")["b"].diff()
| expected = Series([NaT, NaT, Timedelta("1 days")], name="b").dt.as_unit(unit)
| tm.assert_series_equal(result, expected)
|
|
| def test_group_diff_bool():
| df = DataFrame({"a": [1, 2, 3, 3, 2], "b": [True, True, False, False, True]})
| result = df.groupby("a")["b"].diff()
| expected = Series([np.nan, np.nan, np.nan, False, False], name="b")
| tm.assert_series_equal(result, expected)
|
|
| def test_group_diff_object_raises(object_dtype):
| df = DataFrame(
| {"a": ["foo", "bar", "bar"], "b": ["baz", "foo", "foo"]}, dtype=object_dtype
| )
| with pytest.raises(TypeError, match=r"unsupported operand type\(s\) for -"):
| df.groupby("a")["b"].diff()
|
|
| def test_empty_shift_with_fill():
| # GH 41264, single-index check
| df = DataFrame(columns=["a", "b", "c"])
| shifted = df.groupby(["a"]).shift(1)
| shifted_with_fill = df.groupby(["a"]).shift(1, fill_value=0)
| tm.assert_frame_equal(shifted, shifted_with_fill)
| tm.assert_index_equal(shifted.index, shifted_with_fill.index)
|
|
| def test_multindex_empty_shift_with_fill():
| # GH 41264, multi-index check
| df = DataFrame(columns=["a", "b", "c"])
| shifted = df.groupby(["a", "b"]).shift(1)
| shifted_with_fill = df.groupby(["a", "b"]).shift(1, fill_value=0)
| tm.assert_frame_equal(shifted, shifted_with_fill)
| tm.assert_index_equal(shifted.index, shifted_with_fill.index)
|
|
| def test_shift_periods_freq():
| # GH 54093
| data = {"a": [1, 2, 3, 4, 5, 6], "b": [0, 0, 0, 1, 1, 1]}
| df = DataFrame(data, index=date_range(start="20100101", periods=6))
| result = df.groupby(df.index).shift(periods=-2, freq="D")
| expected = DataFrame(data, index=date_range(start="2009-12-30", periods=6))
| tm.assert_frame_equal(result, expected)
|
|
| def test_shift_deprecate_freq_and_fill_value():
| # GH 53832
| data = {"a": [1, 2, 3, 4, 5, 6], "b": [0, 0, 0, 1, 1, 1]}
| df = DataFrame(data, index=date_range(start="20100101", periods=6))
| msg = (
| "Passing a 'freq' together with a 'fill_value' silently ignores the fill_value"
| )
| with tm.assert_produces_warning(FutureWarning, match=msg):
| df.groupby(df.index).shift(periods=-2, freq="D", fill_value="1")
|
|
| def test_shift_disallow_suffix_if_periods_is_int():
| # GH#44424
| data = {"a": [1, 2, 3, 4, 5, 6], "b": [0, 0, 0, 1, 1, 1]}
| df = DataFrame(data)
| msg = "Cannot specify `suffix` if `periods` is an int."
| with pytest.raises(ValueError, match=msg):
| df.groupby("b").shift(1, suffix="fails")
|
|
| def test_group_shift_with_multiple_periods():
| # GH#44424
| df = DataFrame({"a": [1, 2, 3, 3, 2], "b": [True, True, False, False, True]})
|
| shifted_df = df.groupby("b")[["a"]].shift([0, 1])
| expected_df = DataFrame(
| {"a_0": [1, 2, 3, 3, 2], "a_1": [np.nan, 1.0, np.nan, 3.0, 2.0]}
| )
| tm.assert_frame_equal(shifted_df, expected_df)
|
| # series
| shifted_series = df.groupby("b")["a"].shift([0, 1])
| tm.assert_frame_equal(shifted_series, expected_df)
|
|
| def test_group_shift_with_multiple_periods_and_freq():
| # GH#44424
| df = DataFrame(
| {"a": [1, 2, 3, 4, 5], "b": [True, True, False, False, True]},
| index=date_range("1/1/2000", periods=5, freq="h"),
| )
| shifted_df = df.groupby("b")[["a"]].shift(
| [0, 1],
| freq="h",
| )
| expected_df = DataFrame(
| {
| "a_0": [1.0, 2.0, 3.0, 4.0, 5.0, np.nan],
| "a_1": [
| np.nan,
| 1.0,
| 2.0,
| 3.0,
| 4.0,
| 5.0,
| ],
| },
| index=date_range("1/1/2000", periods=6, freq="h"),
| )
| tm.assert_frame_equal(shifted_df, expected_df)
|
|
| def test_group_shift_with_multiple_periods_and_fill_value():
| # GH#44424
| df = DataFrame(
| {"a": [1, 2, 3, 4, 5], "b": [True, True, False, False, True]},
| )
| shifted_df = df.groupby("b")[["a"]].shift([0, 1], fill_value=-1)
| expected_df = DataFrame(
| {"a_0": [1, 2, 3, 4, 5], "a_1": [-1, 1, -1, 3, 2]},
| )
| tm.assert_frame_equal(shifted_df, expected_df)
|
|
| def test_group_shift_with_multiple_periods_and_both_fill_and_freq_deprecated():
| # GH#44424
| df = DataFrame(
| {"a": [1, 2, 3, 4, 5], "b": [True, True, False, False, True]},
| index=date_range("1/1/2000", periods=5, freq="h"),
| )
| msg = (
| "Passing a 'freq' together with a 'fill_value' silently ignores the "
| "fill_value"
| )
| with tm.assert_produces_warning(FutureWarning, match=msg):
| df.groupby("b")[["a"]].shift([1, 2], fill_value=1, freq="h")
|
|
