A PyQT GUI application for converting InfoLease report outputs into Excel files. Handles parsing and summarizing. Learns where files are meant to be store and compiles monthly and yearly summaries.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
InfoLeaseExtract/venv/Lib/site-packages/pandas/tests/series/methods/test_append.py

271 lines
9.8 KiB

import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
DatetimeIndex,
Index,
Series,
Timestamp,
date_range,
)
import pandas._testing as tm
class TestSeriesAppend:
def test_append_preserve_name(self, datetime_series):
result = datetime_series[:5]._append(datetime_series[5:])
assert result.name == datetime_series.name
def test_append(self, datetime_series, string_series, object_series):
appended_series = string_series._append(object_series)
for idx, value in appended_series.items():
if idx in string_series.index:
assert value == string_series[idx]
elif idx in object_series.index:
assert value == object_series[idx]
else:
raise AssertionError("orphaned index!")
msg = "Indexes have overlapping values:"
with pytest.raises(ValueError, match=msg):
datetime_series._append(datetime_series, verify_integrity=True)
def test_append_many(self, datetime_series):
pieces = [datetime_series[:5], datetime_series[5:10], datetime_series[10:]]
result = pieces[0]._append(pieces[1:])
tm.assert_series_equal(result, datetime_series)
def test_append_duplicates(self):
# GH 13677
s1 = Series([1, 2, 3])
s2 = Series([4, 5, 6])
exp = Series([1, 2, 3, 4, 5, 6], index=[0, 1, 2, 0, 1, 2])
tm.assert_series_equal(s1._append(s2), exp)
tm.assert_series_equal(pd.concat([s1, s2]), exp)
# the result must have RangeIndex
exp = Series([1, 2, 3, 4, 5, 6])
tm.assert_series_equal(
s1._append(s2, ignore_index=True), exp, check_index_type=True
)
tm.assert_series_equal(
pd.concat([s1, s2], ignore_index=True), exp, check_index_type=True
)
msg = "Indexes have overlapping values:"
with pytest.raises(ValueError, match=msg):
s1._append(s2, verify_integrity=True)
with pytest.raises(ValueError, match=msg):
pd.concat([s1, s2], verify_integrity=True)
def test_append_tuples(self):
# GH 28410
s = Series([1, 2, 3])
list_input = [s, s]
tuple_input = (s, s)
expected = s._append(list_input)
result = s._append(tuple_input)
tm.assert_series_equal(expected, result)
def test_append_dataframe_raises(self):
# GH 31413
df = DataFrame({"A": [1, 2], "B": [3, 4]})
msg = "to_append should be a Series or list/tuple of Series, got DataFrame"
with pytest.raises(TypeError, match=msg):
df.A._append(df)
with pytest.raises(TypeError, match=msg):
df.A._append([df])
def test_append_raises_future_warning(self):
# GH#35407
with tm.assert_produces_warning(FutureWarning):
Series([1, 2]).append(Series([3, 4]))
class TestSeriesAppendWithDatetimeIndex:
def test_append(self):
rng = date_range("5/8/2012 1:45", periods=10, freq="5T")
ts = Series(np.random.randn(len(rng)), rng)
df = DataFrame(np.random.randn(len(rng), 4), index=rng)
result = ts._append(ts)
result_df = df._append(df)
ex_index = DatetimeIndex(np.tile(rng.values, 2))
tm.assert_index_equal(result.index, ex_index)
tm.assert_index_equal(result_df.index, ex_index)
appended = rng.append(rng)
tm.assert_index_equal(appended, ex_index)
appended = rng.append([rng, rng])
ex_index = DatetimeIndex(np.tile(rng.values, 3))
tm.assert_index_equal(appended, ex_index)
# different index names
rng1 = rng.copy()
rng2 = rng.copy()
rng1.name = "foo"
rng2.name = "bar"
assert rng1.append(rng1).name == "foo"
assert rng1.append(rng2).name is None
def test_append_tz(self):
# see gh-2938
rng = date_range("5/8/2012 1:45", periods=10, freq="5T", tz="US/Eastern")
rng2 = date_range("5/8/2012 2:35", periods=10, freq="5T", tz="US/Eastern")
rng3 = date_range("5/8/2012 1:45", periods=20, freq="5T", tz="US/Eastern")
ts = Series(np.random.randn(len(rng)), rng)
df = DataFrame(np.random.randn(len(rng), 4), index=rng)
ts2 = Series(np.random.randn(len(rng2)), rng2)
df2 = DataFrame(np.random.randn(len(rng2), 4), index=rng2)
result = ts._append(ts2)
result_df = df._append(df2)
tm.assert_index_equal(result.index, rng3)
tm.assert_index_equal(result_df.index, rng3)
appended = rng.append(rng2)
tm.assert_index_equal(appended, rng3)
def test_append_tz_explicit_pytz(self):
# see gh-2938
from pytz import timezone as timezone
rng = date_range(
"5/8/2012 1:45", periods=10, freq="5T", tz=timezone("US/Eastern")
)
rng2 = date_range(
"5/8/2012 2:35", periods=10, freq="5T", tz=timezone("US/Eastern")
)
rng3 = date_range(
"5/8/2012 1:45", periods=20, freq="5T", tz=timezone("US/Eastern")
)
ts = Series(np.random.randn(len(rng)), rng)
df = DataFrame(np.random.randn(len(rng), 4), index=rng)
ts2 = Series(np.random.randn(len(rng2)), rng2)
df2 = DataFrame(np.random.randn(len(rng2), 4), index=rng2)
result = ts._append(ts2)
result_df = df._append(df2)
tm.assert_index_equal(result.index, rng3)
tm.assert_index_equal(result_df.index, rng3)
appended = rng.append(rng2)
tm.assert_index_equal(appended, rng3)
def test_append_tz_dateutil(self):
# see gh-2938
rng = date_range(
"5/8/2012 1:45", periods=10, freq="5T", tz="dateutil/US/Eastern"
)
rng2 = date_range(
"5/8/2012 2:35", periods=10, freq="5T", tz="dateutil/US/Eastern"
)
rng3 = date_range(
"5/8/2012 1:45", periods=20, freq="5T", tz="dateutil/US/Eastern"
)
ts = Series(np.random.randn(len(rng)), rng)
df = DataFrame(np.random.randn(len(rng), 4), index=rng)
ts2 = Series(np.random.randn(len(rng2)), rng2)
df2 = DataFrame(np.random.randn(len(rng2), 4), index=rng2)
result = ts._append(ts2)
result_df = df._append(df2)
tm.assert_index_equal(result.index, rng3)
tm.assert_index_equal(result_df.index, rng3)
appended = rng.append(rng2)
tm.assert_index_equal(appended, rng3)
def test_series_append_aware(self):
rng1 = date_range("1/1/2011 01:00", periods=1, freq="H", tz="US/Eastern")
rng2 = date_range("1/1/2011 02:00", periods=1, freq="H", tz="US/Eastern")
ser1 = Series([1], index=rng1)
ser2 = Series([2], index=rng2)
ts_result = ser1._append(ser2)
exp_index = DatetimeIndex(
["2011-01-01 01:00", "2011-01-01 02:00"], tz="US/Eastern", freq="H"
)
exp = Series([1, 2], index=exp_index)
tm.assert_series_equal(ts_result, exp)
assert ts_result.index.tz == rng1.tz
rng1 = date_range("1/1/2011 01:00", periods=1, freq="H", tz="UTC")
rng2 = date_range("1/1/2011 02:00", periods=1, freq="H", tz="UTC")
ser1 = Series([1], index=rng1)
ser2 = Series([2], index=rng2)
ts_result = ser1._append(ser2)
exp_index = DatetimeIndex(
["2011-01-01 01:00", "2011-01-01 02:00"], tz="UTC", freq="H"
)
exp = Series([1, 2], index=exp_index)
tm.assert_series_equal(ts_result, exp)
utc = rng1.tz
assert utc == ts_result.index.tz
# GH#7795
# different tz coerces to object dtype, not UTC
rng1 = date_range("1/1/2011 01:00", periods=1, freq="H", tz="US/Eastern")
rng2 = date_range("1/1/2011 02:00", periods=1, freq="H", tz="US/Central")
ser1 = Series([1], index=rng1)
ser2 = Series([2], index=rng2)
ts_result = ser1._append(ser2)
exp_index = Index(
[
Timestamp("1/1/2011 01:00", tz="US/Eastern"),
Timestamp("1/1/2011 02:00", tz="US/Central"),
]
)
exp = Series([1, 2], index=exp_index)
tm.assert_series_equal(ts_result, exp)
def test_series_append_aware_naive(self):
rng1 = date_range("1/1/2011 01:00", periods=1, freq="H")
rng2 = date_range("1/1/2011 02:00", periods=1, freq="H", tz="US/Eastern")
ser1 = Series(np.random.randn(len(rng1)), index=rng1)
ser2 = Series(np.random.randn(len(rng2)), index=rng2)
ts_result = ser1._append(ser2)
expected = ser1.index.astype(object).append(ser2.index.astype(object))
assert ts_result.index.equals(expected)
# mixed
rng1 = date_range("1/1/2011 01:00", periods=1, freq="H")
rng2 = range(100)
ser1 = Series(np.random.randn(len(rng1)), index=rng1)
ser2 = Series(np.random.randn(len(rng2)), index=rng2)
ts_result = ser1._append(ser2)
expected = ser1.index.astype(object).append(ser2.index)
assert ts_result.index.equals(expected)
def test_series_append_dst(self):
rng1 = date_range("1/1/2016 01:00", periods=3, freq="H", tz="US/Eastern")
rng2 = date_range("8/1/2016 01:00", periods=3, freq="H", tz="US/Eastern")
ser1 = Series([1, 2, 3], index=rng1)
ser2 = Series([10, 11, 12], index=rng2)
ts_result = ser1._append(ser2)
exp_index = DatetimeIndex(
[
"2016-01-01 01:00",
"2016-01-01 02:00",
"2016-01-01 03:00",
"2016-08-01 01:00",
"2016-08-01 02:00",
"2016-08-01 03:00",
],
tz="US/Eastern",
)
exp = Series([1, 2, 3, 10, 11, 12], index=exp_index)
tm.assert_series_equal(ts_result, exp)
assert ts_result.index.tz == rng1.tz