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/usr/local/lib64/python3.6/site-packages/pandas/tests/series/methods/

/usr/local/lib64/python3.6/site-packages/pandas/tests/series/methods

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
test_align.py	5359	0644	edit dl rm
test_append.py	9600	0644	edit dl rm
test_argsort.py	2249	0644	edit dl rm
test_asfreq.py	3616	0644	edit dl rm
test_asof.py	5515	0644	edit dl rm
test_astype.py	2628	0644	edit dl rm
test_at_time.py	2629	0644	edit dl rm
test_autocorr.py	999	0644	edit dl rm
test_between.py	1197	0644	edit dl rm
test_between_time.py	5086	0644	edit dl rm
test_clip.py	3384	0644	edit dl rm
test_combine.py	627	0644	edit dl rm
test_combine_first.py	3411	0644	edit dl rm
test_compare.py	3734	0644	edit dl rm
test_convert_dtypes.py	9914	0644	edit dl rm
test_count.py	1123	0644	edit dl rm
test_cov_corr.py	5215	0644	edit dl rm
test_describe.py	4640	0644	edit dl rm
test_diff.py	2331	0644	edit dl rm
test_drop.py	2986	0644	edit dl rm
test_droplevel.py	629	0644	edit dl rm
test_drop_duplicates.py	6850	0644	edit dl rm
test_duplicated.py	996	0644	edit dl rm
test_equals.py	1295	0644	edit dl rm
test_explode.py	3538	0644	edit dl rm
test_fillna.py	6513	0644	edit dl rm
test_first_and_last.py	2042	0644	edit dl rm
test_head_tail.py	343	0644	edit dl rm
test_interpolate.py	27757	0644	edit dl rm
test_isin.py	3445	0644	edit dl rm
test_nlargest.py	7121	0644	edit dl rm
test_pct_change.py	2968	0644	edit dl rm
test_quantile.py	6810	0644	edit dl rm
test_rank.py	20287	0644	edit dl rm
test_reindex_like.py	1245	0644	edit dl rm
test_rename.py	3378	0644	edit dl rm
test_rename_axis.py	1503	0644	edit dl rm
test_replace.py	15559	0644	edit dl rm
test_reset_index.py	4636	0644	edit dl rm
test_round.py	1970	0644	edit dl rm
test_searchsorted.py	2121	0644	edit dl rm
test_shift.py	12595	0644	edit dl rm
test_sort_index.py	12277	0644	edit dl rm
test_sort_values.py	7981	0644	edit dl rm
test_to_dict.py	742	0644	edit dl rm
test_to_period.py	1755	0644	edit dl rm
test_to_timestamp.py	2616	0644	edit dl rm
test_truncate.py	5557	0644	edit dl rm
test_tz_convert.py	1008	0644	edit dl rm
test_tz_localize.py	3108	0644	edit dl rm
test_unstack.py	4208	0644	edit dl rm
test_update.py	4213	0644	edit dl rm
test_value_counts.py	8136	0644	edit dl rm
__init__.py	225	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/series/methods/test_asof.py (5515B)

import numpy as np
import pytest

from pandas._libs.tslibs import IncompatibleFrequency

from pandas import Series, Timestamp, date_range, isna, notna, offsets
import pandas._testing as tm

class TestSeriesAsof:
    def test_basic(self):

# array or list or dates
        N = 50
        rng = date_range("1/1/1990", periods=N, freq="53s")
        ts = Series(np.random.randn(N), index=rng)
        ts.iloc[15:30] = np.nan
        dates = date_range("1/1/1990", periods=N * 3, freq="25s")

result = ts.asof(dates)
        assert notna(result).all()
        lb = ts.index[14]
        ub = ts.index[30]

result = ts.asof(list(dates))
        assert notna(result).all()
        lb = ts.index[14]
        ub = ts.index[30]

mask = (result.index >= lb) & (result.index < ub)
        rs = result[mask]
        assert (rs == ts[lb]).all()

val = result[result.index[result.index >= ub][0]]
        assert ts[ub] == val

def test_scalar(self):

N = 30
        rng = date_range("1/1/1990", periods=N, freq="53s")
        ts = Series(np.arange(N), index=rng)
        ts.iloc[5:10] = np.NaN
        ts.iloc[15:20] = np.NaN

val1 = ts.asof(ts.index[7])
        val2 = ts.asof(ts.index[19])

assert val1 == ts[4]
        assert val2 == ts[14]

# accepts strings
        val1 = ts.asof(str(ts.index[7]))
        assert val1 == ts[4]

# in there
        result = ts.asof(ts.index[3])
        assert result == ts[3]

# no as of value
        d = ts.index[0] - offsets.BDay()
        assert np.isnan(ts.asof(d))

def test_with_nan(self):
        # basic asof test
        rng = date_range("1/1/2000", "1/2/2000", freq="4h")
        s = Series(np.arange(len(rng)), index=rng)
        r = s.resample("2h").mean()

result = r.asof(r.index)
        expected = Series(
            [0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6.0],
            index=date_range("1/1/2000", "1/2/2000", freq="2h"),
        )
        tm.assert_series_equal(result, expected)

r.iloc[3:5] = np.nan
        result = r.asof(r.index)
        expected = Series(
            [0, 0, 1, 1, 1, 1, 3, 3, 4, 4, 5, 5, 6.0],
            index=date_range("1/1/2000", "1/2/2000", freq="2h"),
        )
        tm.assert_series_equal(result, expected)

r.iloc[-3:] = np.nan
        result = r.asof(r.index)
        expected = Series(
            [0, 0, 1, 1, 1, 1, 3, 3, 4, 4, 4, 4, 4.0],
            index=date_range("1/1/2000", "1/2/2000", freq="2h"),
        )
        tm.assert_series_equal(result, expected)

def test_periodindex(self):
        from pandas import PeriodIndex, period_range

# array or list or dates
        N = 50
        rng = period_range("1/1/1990", periods=N, freq="H")
        ts = Series(np.random.randn(N), index=rng)
        ts.iloc[15:30] = np.nan
        dates = date_range("1/1/1990", periods=N * 3, freq="37min")

result = ts.asof(dates)
        assert notna(result).all()
        lb = ts.index[14]
        ub = ts.index[30]

result = ts.asof(list(dates))
        assert notna(result).all()
        lb = ts.index[14]
        ub = ts.index[30]

pix = PeriodIndex(result.index.values, freq="H")
        mask = (pix >= lb) & (pix < ub)
        rs = result[mask]
        assert (rs == ts[lb]).all()

ts.iloc[5:10] = np.nan
        ts.iloc[15:20] = np.nan

val1 = ts.asof(ts.index[7])
        val2 = ts.asof(ts.index[19])

assert val1 == ts[4]
        assert val2 == ts[14]

# accepts strings
        val1 = ts.asof(str(ts.index[7]))
        assert val1 == ts[4]

# in there
        assert ts.asof(ts.index[3]) == ts[3]

# no as of value
        d = ts.index[0].to_timestamp() - offsets.BDay()
        assert isna(ts.asof(d))

# Mismatched freq
        msg = "Input has different freq"
        with pytest.raises(IncompatibleFrequency, match=msg):
            ts.asof(rng.asfreq("D"))

def test_errors(self):

s = Series(
            [1, 2, 3],
            index=[Timestamp("20130101"), Timestamp("20130103"), Timestamp("20130102")],
        )

# non-monotonic
        assert not s.index.is_monotonic
        with pytest.raises(ValueError, match="requires a sorted index"):
            s.asof(s.index[0])

# subset with Series
        N = 10
        rng = date_range("1/1/1990", periods=N, freq="53s")
        s = Series(np.random.randn(N), index=rng)
        with pytest.raises(ValueError, match="not valid for Series"):
            s.asof(s.index[0], subset="foo")

def test_all_nans(self):
        # GH 15713
        # series is all nans
        result = Series([np.nan]).asof([0])
        expected = Series([np.nan])
        tm.assert_series_equal(result, expected)

# testing non-default indexes
        N = 50
        rng = date_range("1/1/1990", periods=N, freq="53s")

dates = date_range("1/1/1990", periods=N * 3, freq="25s")
        result = Series(np.nan, index=rng).asof(dates)
        expected = Series(np.nan, index=dates)
        tm.assert_series_equal(result, expected)

# testing scalar input
        date = date_range("1/1/1990", periods=N * 3, freq="25s")[0]
        result = Series(np.nan, index=rng).asof(date)
        assert isna(result)

# test name is propagated
        result = Series(np.nan, index=[1, 2, 3, 4], name="test").asof([4, 5])
        expected = Series(np.nan, index=[4, 5], name="test")
        tm.assert_series_equal(result, expected)

import numpy as np import pytest from pandas._libs.tslibs import IncompatibleFrequency from pandas import Series, Timestamp, date_range, isna, notna, offsets import pandas._testing as tm class TestSeriesAsof: def test_basic(self): # array or list or dates N = 50 rng = date_range("1/1/1990", periods=N, freq="53s") ts = Series(np.random.randn(N), index=rng) ts.iloc[15:30] = np.nan dates = date_range("1/1/1990", periods=N * 3, freq="25s") result = ts.asof(dates) assert notna(result).all() lb = ts.index[14] ub = ts.index[30] result = ts.asof(list(dates)) assert notna(result).all() lb = ts.index[14] ub = ts.index[30] mask = (result.index >= lb) & (result.index < ub) rs = result[mask] assert (rs == ts[lb]).all() val = result[result.index[result.index >= ub][0]] assert ts[ub] == val def test_scalar(self): N = 30 rng = date_range("1/1/1990", periods=N, freq="53s") ts = Series(np.arange(N), index=rng) ts.iloc[5:10] = np.NaN ts.iloc[15:20] = np.NaN val1 = ts.asof(ts.index[7]) val2 = ts.asof(ts.index[19]) assert val1 == ts[4] assert val2 == ts[14] # accepts strings val1 = ts.asof(str(ts.index[7])) assert val1 == ts[4] # in there result = ts.asof(ts.index[3]) assert result == ts[3] # no as of value d = ts.index[0] - offsets.BDay() assert np.isnan(ts.asof(d)) def test_with_nan(self): # basic asof test rng = date_range("1/1/2000", "1/2/2000", freq="4h") s = Series(np.arange(len(rng)), index=rng) r = s.resample("2h").mean() result = r.asof(r.index) expected = Series( [0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6.0], index=date_range("1/1/2000", "1/2/2000", freq="2h"), ) tm.assert_series_equal(result, expected) r.iloc[3:5] = np.nan result = r.asof(r.index) expected = Series( [0, 0, 1, 1, 1, 1, 3, 3, 4, 4, 5, 5, 6.0], index=date_range("1/1/2000", "1/2/2000", freq="2h"), ) tm.assert_series_equal(result, expected) r.iloc[-3:] = np.nan result = r.asof(r.index) expected = Series( [0, 0, 1, 1, 1, 1, 3, 3, 4, 4, 4, 4, 4.0], index=date_range("1/1/2000", "1/2/2000", freq="2h"), ) tm.assert_series_equal(result, expected) def test_periodindex(self): from pandas import PeriodIndex, period_range # array or list or dates N = 50 rng = period_range("1/1/1990", periods=N, freq="H") ts = Series(np.random.randn(N), index=rng) ts.iloc[15:30] = np.nan dates = date_range("1/1/1990", periods=N * 3, freq="37min") result = ts.asof(dates) assert notna(result).all() lb = ts.index[14] ub = ts.index[30] result = ts.asof(list(dates)) assert notna(result).all() lb = ts.index[14] ub = ts.index[30] pix = PeriodIndex(result.index.values, freq="H") mask = (pix >= lb) & (pix < ub) rs = result[mask] assert (rs == ts[lb]).all() ts.iloc[5:10] = np.nan ts.iloc[15:20] = np.nan val1 = ts.asof(ts.index[7]) val2 = ts.asof(ts.index[19]) assert val1 == ts[4] assert val2 == ts[14] # accepts strings val1 = ts.asof(str(ts.index[7])) assert val1 == ts[4] # in there assert ts.asof(ts.index[3]) == ts[3] # no as of value d = ts.index[0].to_timestamp() - offsets.BDay() assert isna(ts.asof(d)) # Mismatched freq msg = "Input has different freq" with pytest.raises(IncompatibleFrequency, match=msg): ts.asof(rng.asfreq("D")) def test_errors(self): s = Series( [1, 2, 3], index=[Timestamp("20130101"), Timestamp("20130103"), Timestamp("20130102")], ) # non-monotonic assert not s.index.is_monotonic with pytest.raises(ValueError, match="requires a sorted index"): s.asof(s.index[0]) # subset with Series N = 10 rng = date_range("1/1/1990", periods=N, freq="53s") s = Series(np.random.randn(N), index=rng) with pytest.raises(ValueError, match="not valid for Series"): s.asof(s.index[0], subset="foo") def test_all_nans(self): # GH 15713 # series is all nans result = Series([np.nan]).asof([0]) expected = Series([np.nan]) tm.assert_series_equal(result, expected) # testing non-default indexes N = 50 rng = date_range("1/1/1990", periods=N, freq="53s") dates = date_range("1/1/1990", periods=N * 3, freq="25s") result = Series(np.nan, index=rng).asof(dates) expected = Series(np.nan, index=dates) tm.assert_series_equal(result, expected) # testing scalar input date = date_range("1/1/1990", periods=N * 3, freq="25s")[0] result = Series(np.nan, index=rng).asof(date) assert isna(result) # test name is propagated result = Series(np.nan, index=[1, 2, 3, 4], name="test").asof([4, 5]) expected = Series(np.nan, index=[4, 5], name="test") tm.assert_series_equal(result, expected)