155 lines
5.7 KiB
Python
155 lines
5.7 KiB
Python
from datetime import timedelta
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import numpy as np
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import pytest
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from pandas import (
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DataFrame,
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DatetimeIndex,
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PeriodIndex,
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Series,
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Timedelta,
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date_range,
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period_range,
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to_datetime,
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)
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import pandas._testing as tm
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def _get_with_delta(delta, freq="YE-DEC"):
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return date_range(
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to_datetime("1/1/2001") + delta,
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to_datetime("12/31/2009") + delta,
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freq=freq,
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)
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class TestToTimestamp:
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def test_to_timestamp(self, frame_or_series):
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K = 5
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index = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
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obj = DataFrame(
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np.random.default_rng(2).standard_normal((len(index), K)),
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index=index,
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columns=["A", "B", "C", "D", "E"],
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)
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obj["mix"] = "a"
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obj = tm.get_obj(obj, frame_or_series)
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exp_index = date_range("1/1/2001", end="12/31/2009", freq="YE-DEC")
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exp_index = exp_index + Timedelta(1, "D") - Timedelta(1, "ns")
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result = obj.to_timestamp("D", "end")
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tm.assert_index_equal(result.index, exp_index)
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tm.assert_numpy_array_equal(result.values, obj.values)
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if frame_or_series is Series:
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assert result.name == "A"
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exp_index = date_range("1/1/2001", end="1/1/2009", freq="YS-JAN")
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result = obj.to_timestamp("D", "start")
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tm.assert_index_equal(result.index, exp_index)
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result = obj.to_timestamp(how="start")
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tm.assert_index_equal(result.index, exp_index)
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delta = timedelta(hours=23)
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result = obj.to_timestamp("H", "end")
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exp_index = _get_with_delta(delta)
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exp_index = exp_index + Timedelta(1, "h") - Timedelta(1, "ns")
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tm.assert_index_equal(result.index, exp_index)
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delta = timedelta(hours=23, minutes=59)
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result = obj.to_timestamp("T", "end")
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exp_index = _get_with_delta(delta)
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exp_index = exp_index + Timedelta(1, "m") - Timedelta(1, "ns")
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tm.assert_index_equal(result.index, exp_index)
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result = obj.to_timestamp("S", "end")
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delta = timedelta(hours=23, minutes=59, seconds=59)
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exp_index = _get_with_delta(delta)
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exp_index = exp_index + Timedelta(1, "s") - Timedelta(1, "ns")
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tm.assert_index_equal(result.index, exp_index)
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def test_to_timestamp_columns(self):
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K = 5
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index = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
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df = DataFrame(
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np.random.default_rng(2).standard_normal((len(index), K)),
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index=index,
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columns=["A", "B", "C", "D", "E"],
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)
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df["mix"] = "a"
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# columns
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df = df.T
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exp_index = date_range("1/1/2001", end="12/31/2009", freq="YE-DEC")
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exp_index = exp_index + Timedelta(1, "D") - Timedelta(1, "ns")
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result = df.to_timestamp("D", "end", axis=1)
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tm.assert_index_equal(result.columns, exp_index)
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tm.assert_numpy_array_equal(result.values, df.values)
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exp_index = date_range("1/1/2001", end="1/1/2009", freq="YS-JAN")
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result = df.to_timestamp("D", "start", axis=1)
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tm.assert_index_equal(result.columns, exp_index)
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delta = timedelta(hours=23)
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result = df.to_timestamp("H", "end", axis=1)
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exp_index = _get_with_delta(delta)
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exp_index = exp_index + Timedelta(1, "h") - Timedelta(1, "ns")
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tm.assert_index_equal(result.columns, exp_index)
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delta = timedelta(hours=23, minutes=59)
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result = df.to_timestamp("min", "end", axis=1)
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exp_index = _get_with_delta(delta)
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exp_index = exp_index + Timedelta(1, "m") - Timedelta(1, "ns")
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tm.assert_index_equal(result.columns, exp_index)
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result = df.to_timestamp("S", "end", axis=1)
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delta = timedelta(hours=23, minutes=59, seconds=59)
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exp_index = _get_with_delta(delta)
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exp_index = exp_index + Timedelta(1, "s") - Timedelta(1, "ns")
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tm.assert_index_equal(result.columns, exp_index)
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result1 = df.to_timestamp("5min", axis=1)
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result2 = df.to_timestamp("min", axis=1)
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expected = date_range("2001-01-01", "2009-01-01", freq="YS")
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assert isinstance(result1.columns, DatetimeIndex)
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assert isinstance(result2.columns, DatetimeIndex)
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tm.assert_numpy_array_equal(result1.columns.asi8, expected.asi8)
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tm.assert_numpy_array_equal(result2.columns.asi8, expected.asi8)
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# PeriodIndex.to_timestamp always use 'infer'
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assert result1.columns.freqstr == "YS-JAN"
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assert result2.columns.freqstr == "YS-JAN"
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def test_to_timestamp_invalid_axis(self):
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index = period_range(freq="Y", start="1/1/2001", end="12/1/2009")
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obj = DataFrame(
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np.random.default_rng(2).standard_normal((len(index), 5)), index=index
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)
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# invalid axis
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with pytest.raises(ValueError, match="axis"):
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obj.to_timestamp(axis=2)
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def test_to_timestamp_hourly(self, frame_or_series):
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index = period_range(freq="h", start="1/1/2001", end="1/2/2001")
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obj = Series(1, index=index, name="foo")
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if frame_or_series is not Series:
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obj = obj.to_frame()
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exp_index = date_range("1/1/2001 00:59:59", end="1/2/2001 00:59:59", freq="h")
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result = obj.to_timestamp(how="end")
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exp_index = exp_index + Timedelta(1, "s") - Timedelta(1, "ns")
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tm.assert_index_equal(result.index, exp_index)
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if frame_or_series is Series:
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assert result.name == "foo"
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def test_to_timestamp_raises(self, index, frame_or_series):
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# GH#33327
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obj = frame_or_series(index=index, dtype=object)
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if not isinstance(index, PeriodIndex):
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msg = f"unsupported Type {type(index).__name__}"
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with pytest.raises(TypeError, match=msg):
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obj.to_timestamp()
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