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import numpy as np
import pytest
from pandas import (
Index,
NaT,
Period,
PeriodIndex,
Series,
date_range,
offsets,
period_range,
)
import pandas._testing as tm
class TestPeriodIndex:
def test_view_asi8(self):
idx = PeriodIndex([], freq="M")
exp = np.array([], dtype=np.int64)
tm.assert_numpy_array_equal(idx.view("i8"), exp)
tm.assert_numpy_array_equal(idx.asi8, exp)
idx = PeriodIndex(["2011-01", NaT], freq="M")
exp = np.array([492, -9223372036854775808], dtype=np.int64)
tm.assert_numpy_array_equal(idx.view("i8"), exp)
tm.assert_numpy_array_equal(idx.asi8, exp)
exp = np.array([14975, -9223372036854775808], dtype=np.int64)
idx = PeriodIndex(["2011-01-01", NaT], freq="D")
tm.assert_numpy_array_equal(idx.view("i8"), exp)
tm.assert_numpy_array_equal(idx.asi8, exp)
def test_values(self):
idx = PeriodIndex([], freq="M")
exp = np.array([], dtype=object)
tm.assert_numpy_array_equal(idx.values, exp)
tm.assert_numpy_array_equal(idx.to_numpy(), exp)
exp = np.array([], dtype=np.int64)
tm.assert_numpy_array_equal(idx.asi8, exp)
idx = PeriodIndex(["2011-01", NaT], freq="M")
exp = np.array([Period("2011-01", freq="M"), NaT], dtype=object)
tm.assert_numpy_array_equal(idx.values, exp)
tm.assert_numpy_array_equal(idx.to_numpy(), exp)
exp = np.array([492, -9223372036854775808], dtype=np.int64)
tm.assert_numpy_array_equal(idx.asi8, exp)
idx = PeriodIndex(["2011-01-01", NaT], freq="D")
exp = np.array([Period("2011-01-01", freq="D"), NaT], dtype=object)
tm.assert_numpy_array_equal(idx.values, exp)
tm.assert_numpy_array_equal(idx.to_numpy(), exp)
exp = np.array([14975, -9223372036854775808], dtype=np.int64)
tm.assert_numpy_array_equal(idx.asi8, exp)
@pytest.mark.parametrize(
"field",
[
"year",
"month",
"day",
"hour",
"minute",
"second",
"weekofyear",
"week",
"dayofweek",
"day_of_week",
"dayofyear",
"day_of_year",
"quarter",
"qyear",
"days_in_month",
],
)
@pytest.mark.parametrize(
"periodindex",
[
period_range(freq="Y", start="1/1/2001", end="12/1/2005"),
period_range(freq="Q", start="1/1/2001", end="12/1/2002"),
period_range(freq="M", start="1/1/2001", end="1/1/2002"),
period_range(freq="D", start="12/1/2001", end="6/1/2001"),
period_range(freq="h", start="12/31/2001", end="1/1/2002 23:00"),
period_range(freq="Min", start="12/31/2001", end="1/1/2002 00:20"),
period_range(
freq="s", start="12/31/2001 00:00:00", end="12/31/2001 00:05:00"
),
period_range(end=Period("2006-12-31", "W"), periods=10),
],
)
def test_fields(self, periodindex, field):
periods = list(periodindex)
ser = Series(periodindex)
field_idx = getattr(periodindex, field)
assert len(periodindex) == len(field_idx)
for x, val in zip(periods, field_idx):
assert getattr(x, field) == val
if len(ser) == 0:
return
field_s = getattr(ser.dt, field)
assert len(periodindex) == len(field_s)
for x, val in zip(periods, field_s):
assert getattr(x, field) == val
def test_is_(self):
create_index = lambda: period_range(freq="Y", start="1/1/2001", end="12/1/2009")
index = create_index()
assert index.is_(index)
assert not index.is_(create_index())
assert index.is_(index.view())
assert index.is_(index.view().view().view().view().view())
assert index.view().is_(index)
ind2 = index.view()
index.name = "Apple"
assert ind2.is_(index)
assert not index.is_(index[:])
assert not index.is_(index.asfreq("M"))
assert not index.is_(index.asfreq("Y"))
assert not index.is_(index - 2)
assert not index.is_(index - 0)
def test_index_unique(self):
idx = PeriodIndex([2000, 2007, 2007, 2009, 2009], freq="Y-JUN")
expected = PeriodIndex([2000, 2007, 2009], freq="Y-JUN")
tm.assert_index_equal(idx.unique(), expected)
assert idx.nunique() == 3
def test_pindex_fieldaccessor_nat(self):
idx = PeriodIndex(
["2011-01", "2011-02", "NaT", "2012-03", "2012-04"], freq="D", name="name"
)
exp = Index([2011, 2011, -1, 2012, 2012], dtype=np.int64, name="name")
tm.assert_index_equal(idx.year, exp)
exp = Index([1, 2, -1, 3, 4], dtype=np.int64, name="name")
tm.assert_index_equal(idx.month, exp)
def test_pindex_multiples(self):
expected = PeriodIndex(
["2011-01", "2011-03", "2011-05", "2011-07", "2011-09", "2011-11"],
freq="2M",
)
pi = period_range(start="1/1/11", end="12/31/11", freq="2M")
tm.assert_index_equal(pi, expected)
assert pi.freq == offsets.MonthEnd(2)
assert pi.freqstr == "2M"
pi = period_range(start="1/1/11", periods=6, freq="2M")
tm.assert_index_equal(pi, expected)
assert pi.freq == offsets.MonthEnd(2)
assert pi.freqstr == "2M"
@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
@pytest.mark.filterwarnings("ignore:Period with BDay freq:FutureWarning")
def test_iteration(self):
index = period_range(start="1/1/10", periods=4, freq="B")
result = list(index)
assert isinstance(result[0], Period)
assert result[0].freq == index.freq
def test_with_multi_index(self):
# #1705
index = date_range("1/1/2012", periods=4, freq="12h")
index_as_arrays = [index.to_period(freq="D"), index.hour]
s = Series([0, 1, 2, 3], index_as_arrays)
assert isinstance(s.index.levels[0], PeriodIndex)
assert isinstance(s.index.values[0][0], Period)
def test_map(self):
# test_map_dictlike generally tests
index = PeriodIndex([2005, 2007, 2009], freq="Y")
result = index.map(lambda x: x.ordinal)
exp = Index([x.ordinal for x in index])
tm.assert_index_equal(result, exp)
def test_maybe_convert_timedelta():
pi = PeriodIndex(["2000", "2001"], freq="D")
offset = offsets.Day(2)
assert pi._maybe_convert_timedelta(offset) == 2
assert pi._maybe_convert_timedelta(2) == 2
offset = offsets.BusinessDay()
msg = r"Input has different freq=B from PeriodIndex\(freq=D\)"
with pytest.raises(ValueError, match=msg):
pi._maybe_convert_timedelta(offset)
@pytest.mark.parametrize("array", [True, False])
def test_dunder_array(array):
obj = PeriodIndex(["2000-01-01", "2001-01-01"], freq="D")
if array:
obj = obj._data
expected = np.array([obj[0], obj[1]], dtype=object)
result = np.array(obj)
tm.assert_numpy_array_equal(result, expected)
result = np.asarray(obj)
tm.assert_numpy_array_equal(result, expected)
expected = obj.asi8
for dtype in ["i8", "int64", np.int64]:
result = np.array(obj, dtype=dtype)
tm.assert_numpy_array_equal(result, expected)
result = np.asarray(obj, dtype=dtype)
tm.assert_numpy_array_equal(result, expected)
for dtype in ["float64", "int32", "uint64"]:
msg = "argument must be"
with pytest.raises(TypeError, match=msg):
np.array(obj, dtype=dtype)
with pytest.raises(TypeError, match=msg):
np.array(obj, dtype=getattr(np, dtype))