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