234 lines
7.5 KiB
Python
234 lines
7.5 KiB
Python
import numpy as np
|
|
import pytest
|
|
|
|
import pandas as pd
|
|
from pandas import DataFrame, Index, Series, Timestamp, date_range
|
|
import pandas._testing as tm
|
|
|
|
|
|
class TestDatetimeIndex:
|
|
def test_indexing_with_datetime_tz(self):
|
|
|
|
# GH#8260
|
|
# support datetime64 with tz
|
|
|
|
idx = Index(date_range("20130101", periods=3, tz="US/Eastern"), name="foo")
|
|
dr = date_range("20130110", periods=3)
|
|
df = DataFrame({"A": idx, "B": dr})
|
|
df["C"] = idx
|
|
df.iloc[1, 1] = pd.NaT
|
|
df.iloc[1, 2] = pd.NaT
|
|
|
|
# indexing
|
|
result = df.iloc[1]
|
|
expected = Series(
|
|
[Timestamp("2013-01-02 00:00:00-0500", tz="US/Eastern"), pd.NaT, pd.NaT],
|
|
index=list("ABC"),
|
|
dtype="object",
|
|
name=1,
|
|
)
|
|
tm.assert_series_equal(result, expected)
|
|
result = df.loc[1]
|
|
expected = Series(
|
|
[Timestamp("2013-01-02 00:00:00-0500", tz="US/Eastern"), pd.NaT, pd.NaT],
|
|
index=list("ABC"),
|
|
dtype="object",
|
|
name=1,
|
|
)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# indexing - fast_xs
|
|
df = DataFrame({"a": date_range("2014-01-01", periods=10, tz="UTC")})
|
|
result = df.iloc[5]
|
|
expected = Series(
|
|
[Timestamp("2014-01-06 00:00:00+0000", tz="UTC")], index=["a"], name=5
|
|
)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
result = df.loc[5]
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# indexing - boolean
|
|
result = df[df.a > df.a[3]]
|
|
expected = df.iloc[4:]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# indexing - setting an element
|
|
df = DataFrame(
|
|
data=pd.to_datetime(["2015-03-30 20:12:32", "2015-03-12 00:11:11"]),
|
|
columns=["time"],
|
|
)
|
|
df["new_col"] = ["new", "old"]
|
|
df.time = df.set_index("time").index.tz_localize("UTC")
|
|
v = df[df.new_col == "new"].set_index("time").index.tz_convert("US/Pacific")
|
|
|
|
# trying to set a single element on a part of a different timezone
|
|
# this converts to object
|
|
df2 = df.copy()
|
|
df2.loc[df2.new_col == "new", "time"] = v
|
|
|
|
expected = Series([v[0], df.loc[1, "time"]], name="time")
|
|
tm.assert_series_equal(df2.time, expected)
|
|
|
|
v = df.loc[df.new_col == "new", "time"] + pd.Timedelta("1s")
|
|
df.loc[df.new_col == "new", "time"] = v
|
|
tm.assert_series_equal(df.loc[df.new_col == "new", "time"], v)
|
|
|
|
def test_consistency_with_tz_aware_scalar(self):
|
|
# xef gh-12938
|
|
# various ways of indexing the same tz-aware scalar
|
|
df = Series([Timestamp("2016-03-30 14:35:25", tz="Europe/Brussels")]).to_frame()
|
|
|
|
df = pd.concat([df, df]).reset_index(drop=True)
|
|
expected = Timestamp("2016-03-30 14:35:25+0200", tz="Europe/Brussels")
|
|
|
|
result = df[0][0]
|
|
assert result == expected
|
|
|
|
result = df.iloc[0, 0]
|
|
assert result == expected
|
|
|
|
result = df.loc[0, 0]
|
|
assert result == expected
|
|
|
|
result = df.iat[0, 0]
|
|
assert result == expected
|
|
|
|
result = df.at[0, 0]
|
|
assert result == expected
|
|
|
|
result = df[0].loc[0]
|
|
assert result == expected
|
|
|
|
result = df[0].at[0]
|
|
assert result == expected
|
|
|
|
def test_indexing_with_datetimeindex_tz(self):
|
|
|
|
# GH 12050
|
|
# indexing on a series with a datetimeindex with tz
|
|
index = date_range("2015-01-01", periods=2, tz="utc")
|
|
|
|
ser = Series(range(2), index=index, dtype="int64")
|
|
|
|
# list-like indexing
|
|
|
|
for sel in (index, list(index)):
|
|
# getitem
|
|
result = ser[sel]
|
|
expected = ser.copy()
|
|
if sel is not index:
|
|
expected.index = expected.index._with_freq(None)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# setitem
|
|
result = ser.copy()
|
|
result[sel] = 1
|
|
expected = Series(1, index=index)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# .loc getitem
|
|
result = ser.loc[sel]
|
|
expected = ser.copy()
|
|
if sel is not index:
|
|
expected.index = expected.index._with_freq(None)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# .loc setitem
|
|
result = ser.copy()
|
|
result.loc[sel] = 1
|
|
expected = Series(1, index=index)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# single element indexing
|
|
|
|
# getitem
|
|
assert ser[index[1]] == 1
|
|
|
|
# setitem
|
|
result = ser.copy()
|
|
result[index[1]] = 5
|
|
expected = Series([0, 5], index=index)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
# .loc getitem
|
|
assert ser.loc[index[1]] == 1
|
|
|
|
# .loc setitem
|
|
result = ser.copy()
|
|
result.loc[index[1]] = 5
|
|
expected = Series([0, 5], index=index)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize("to_period", [True, False])
|
|
def test_loc_getitem_listlike_of_datetimelike_keys(self, to_period):
|
|
# GH 11497
|
|
|
|
idx = date_range("2011-01-01", "2011-01-02", freq="D", name="idx")
|
|
if to_period:
|
|
idx = idx.to_period("D")
|
|
ser = Series([0.1, 0.2], index=idx, name="s")
|
|
|
|
keys = [Timestamp("2011-01-01"), Timestamp("2011-01-02")]
|
|
if to_period:
|
|
keys = [x.to_period("D") for x in keys]
|
|
result = ser.loc[keys]
|
|
exp = Series([0.1, 0.2], index=idx, name="s")
|
|
if not to_period:
|
|
exp.index = exp.index._with_freq(None)
|
|
tm.assert_series_equal(result, exp, check_index_type=True)
|
|
|
|
keys = [
|
|
Timestamp("2011-01-02"),
|
|
Timestamp("2011-01-02"),
|
|
Timestamp("2011-01-01"),
|
|
]
|
|
if to_period:
|
|
keys = [x.to_period("D") for x in keys]
|
|
exp = Series(
|
|
[0.2, 0.2, 0.1], index=Index(keys, name="idx", dtype=idx.dtype), name="s"
|
|
)
|
|
result = ser.loc[keys]
|
|
tm.assert_series_equal(result, exp, check_index_type=True)
|
|
|
|
keys = [
|
|
Timestamp("2011-01-03"),
|
|
Timestamp("2011-01-02"),
|
|
Timestamp("2011-01-03"),
|
|
]
|
|
if to_period:
|
|
keys = [x.to_period("D") for x in keys]
|
|
|
|
with pytest.raises(KeyError, match="with any missing labels"):
|
|
ser.loc[keys]
|
|
|
|
def test_nanosecond_getitem_setitem_with_tz(self):
|
|
# GH 11679
|
|
data = ["2016-06-28 08:30:00.123456789"]
|
|
index = pd.DatetimeIndex(data, dtype="datetime64[ns, America/Chicago]")
|
|
df = DataFrame({"a": [10]}, index=index)
|
|
result = df.loc[df.index[0]]
|
|
expected = Series(10, index=["a"], name=df.index[0])
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
result = df.copy()
|
|
result.loc[df.index[0], "a"] = -1
|
|
expected = DataFrame(-1, index=index, columns=["a"])
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_loc_setitem_with_existing_dst(self):
|
|
# GH 18308
|
|
start = Timestamp("2017-10-29 00:00:00+0200", tz="Europe/Madrid")
|
|
end = Timestamp("2017-10-29 03:00:00+0100", tz="Europe/Madrid")
|
|
ts = Timestamp("2016-10-10 03:00:00", tz="Europe/Madrid")
|
|
idx = pd.date_range(start, end, closed="left", freq="H")
|
|
result = DataFrame(index=idx, columns=["value"])
|
|
result.loc[ts, "value"] = 12
|
|
expected = DataFrame(
|
|
[np.nan] * len(idx) + [12],
|
|
index=idx.append(pd.DatetimeIndex([ts])),
|
|
columns=["value"],
|
|
dtype=object,
|
|
)
|
|
tm.assert_frame_equal(result, expected)
|