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735 lines
23 KiB
735 lines
23 KiB
6 months ago
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from datetime import datetime
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import re
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import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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DataFrame,
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Index,
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MultiIndex,
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Series,
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_testing as tm,
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)
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from pandas.tests.strings import (
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_convert_na_value,
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object_pyarrow_numpy,
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)
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@pytest.mark.parametrize("method", ["split", "rsplit"])
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def test_split(any_string_dtype, method):
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values = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype)
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result = getattr(values.str, method)("_")
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exp = Series([["a", "b", "c"], ["c", "d", "e"], np.nan, ["f", "g", "h"]])
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exp = _convert_na_value(values, exp)
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tm.assert_series_equal(result, exp)
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@pytest.mark.parametrize("method", ["split", "rsplit"])
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def test_split_more_than_one_char(any_string_dtype, method):
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# more than one char
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values = Series(["a__b__c", "c__d__e", np.nan, "f__g__h"], dtype=any_string_dtype)
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result = getattr(values.str, method)("__")
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exp = Series([["a", "b", "c"], ["c", "d", "e"], np.nan, ["f", "g", "h"]])
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exp = _convert_na_value(values, exp)
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tm.assert_series_equal(result, exp)
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result = getattr(values.str, method)("__", expand=False)
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tm.assert_series_equal(result, exp)
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def test_split_more_regex_split(any_string_dtype):
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# regex split
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values = Series(["a,b_c", "c_d,e", np.nan, "f,g,h"], dtype=any_string_dtype)
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result = values.str.split("[,_]")
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exp = Series([["a", "b", "c"], ["c", "d", "e"], np.nan, ["f", "g", "h"]])
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exp = _convert_na_value(values, exp)
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tm.assert_series_equal(result, exp)
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def test_split_regex(any_string_dtype):
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# GH 43563
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# explicit regex = True split
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values = Series("xxxjpgzzz.jpg", dtype=any_string_dtype)
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result = values.str.split(r"\.jpg", regex=True)
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exp = Series([["xxxjpgzzz", ""]])
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tm.assert_series_equal(result, exp)
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def test_split_regex_explicit(any_string_dtype):
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# explicit regex = True split with compiled regex
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regex_pat = re.compile(r".jpg")
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values = Series("xxxjpgzzz.jpg", dtype=any_string_dtype)
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result = values.str.split(regex_pat)
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exp = Series([["xx", "zzz", ""]])
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tm.assert_series_equal(result, exp)
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# explicit regex = False split
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result = values.str.split(r"\.jpg", regex=False)
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exp = Series([["xxxjpgzzz.jpg"]])
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tm.assert_series_equal(result, exp)
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# non explicit regex split, pattern length == 1
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result = values.str.split(r".")
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exp = Series([["xxxjpgzzz", "jpg"]])
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tm.assert_series_equal(result, exp)
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# non explicit regex split, pattern length != 1
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result = values.str.split(r".jpg")
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exp = Series([["xx", "zzz", ""]])
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tm.assert_series_equal(result, exp)
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# regex=False with pattern compiled regex raises error
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with pytest.raises(
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ValueError,
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match="Cannot use a compiled regex as replacement pattern with regex=False",
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):
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values.str.split(regex_pat, regex=False)
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@pytest.mark.parametrize("expand", [None, False])
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@pytest.mark.parametrize("method", ["split", "rsplit"])
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def test_split_object_mixed(expand, method):
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mixed = Series(["a_b_c", np.nan, "d_e_f", True, datetime.today(), None, 1, 2.0])
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result = getattr(mixed.str, method)("_", expand=expand)
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exp = Series(
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[
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["a", "b", "c"],
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np.nan,
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["d", "e", "f"],
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np.nan,
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np.nan,
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None,
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np.nan,
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np.nan,
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]
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)
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assert isinstance(result, Series)
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tm.assert_almost_equal(result, exp)
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@pytest.mark.parametrize("method", ["split", "rsplit"])
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@pytest.mark.parametrize("n", [None, 0])
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def test_split_n(any_string_dtype, method, n):
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s = Series(["a b", pd.NA, "b c"], dtype=any_string_dtype)
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expected = Series([["a", "b"], pd.NA, ["b", "c"]])
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result = getattr(s.str, method)(" ", n=n)
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expected = _convert_na_value(s, expected)
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tm.assert_series_equal(result, expected)
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def test_rsplit(any_string_dtype):
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# regex split is not supported by rsplit
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values = Series(["a,b_c", "c_d,e", np.nan, "f,g,h"], dtype=any_string_dtype)
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result = values.str.rsplit("[,_]")
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exp = Series([["a,b_c"], ["c_d,e"], np.nan, ["f,g,h"]])
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exp = _convert_na_value(values, exp)
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tm.assert_series_equal(result, exp)
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def test_rsplit_max_number(any_string_dtype):
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# setting max number of splits, make sure it's from reverse
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values = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype)
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result = values.str.rsplit("_", n=1)
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exp = Series([["a_b", "c"], ["c_d", "e"], np.nan, ["f_g", "h"]])
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exp = _convert_na_value(values, exp)
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tm.assert_series_equal(result, exp)
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def test_split_blank_string(any_string_dtype):
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# expand blank split GH 20067
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values = Series([""], name="test", dtype=any_string_dtype)
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result = values.str.split(expand=True)
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exp = DataFrame([[]], dtype=any_string_dtype) # NOTE: this is NOT an empty df
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tm.assert_frame_equal(result, exp)
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def test_split_blank_string_with_non_empty(any_string_dtype):
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values = Series(["a b c", "a b", "", " "], name="test", dtype=any_string_dtype)
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result = values.str.split(expand=True)
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exp = DataFrame(
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[
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["a", "b", "c"],
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["a", "b", None],
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[None, None, None],
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[None, None, None],
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],
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dtype=any_string_dtype,
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)
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tm.assert_frame_equal(result, exp)
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@pytest.mark.parametrize("method", ["split", "rsplit"])
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def test_split_noargs(any_string_dtype, method):
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# #1859
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s = Series(["Wes McKinney", "Travis Oliphant"], dtype=any_string_dtype)
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result = getattr(s.str, method)()
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expected = ["Travis", "Oliphant"]
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assert result[1] == expected
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@pytest.mark.parametrize(
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"data, pat",
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[
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(["bd asdf jfg", "kjasdflqw asdfnfk"], None),
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(["bd asdf jfg", "kjasdflqw asdfnfk"], "asdf"),
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(["bd_asdf_jfg", "kjasdflqw_asdfnfk"], "_"),
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],
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)
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@pytest.mark.parametrize("n", [-1, 0])
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def test_split_maxsplit(data, pat, any_string_dtype, n):
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# re.split 0, str.split -1
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s = Series(data, dtype=any_string_dtype)
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result = s.str.split(pat=pat, n=n)
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xp = s.str.split(pat=pat)
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tm.assert_series_equal(result, xp)
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@pytest.mark.parametrize(
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"data, pat, expected",
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[
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(
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["split once", "split once too!"],
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None,
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Series({0: ["split", "once"], 1: ["split", "once too!"]}),
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),
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(
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["split_once", "split_once_too!"],
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"_",
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Series({0: ["split", "once"], 1: ["split", "once_too!"]}),
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),
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],
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)
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def test_split_no_pat_with_nonzero_n(data, pat, expected, any_string_dtype):
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s = Series(data, dtype=any_string_dtype)
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result = s.str.split(pat=pat, n=1)
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tm.assert_series_equal(expected, result, check_index_type=False)
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def test_split_to_dataframe_no_splits(any_string_dtype):
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s = Series(["nosplit", "alsonosplit"], dtype=any_string_dtype)
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result = s.str.split("_", expand=True)
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exp = DataFrame({0: Series(["nosplit", "alsonosplit"], dtype=any_string_dtype)})
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tm.assert_frame_equal(result, exp)
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def test_split_to_dataframe(any_string_dtype):
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s = Series(["some_equal_splits", "with_no_nans"], dtype=any_string_dtype)
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result = s.str.split("_", expand=True)
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exp = DataFrame(
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{0: ["some", "with"], 1: ["equal", "no"], 2: ["splits", "nans"]},
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dtype=any_string_dtype,
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)
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tm.assert_frame_equal(result, exp)
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def test_split_to_dataframe_unequal_splits(any_string_dtype):
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s = Series(
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["some_unequal_splits", "one_of_these_things_is_not"], dtype=any_string_dtype
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)
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result = s.str.split("_", expand=True)
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exp = DataFrame(
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{
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0: ["some", "one"],
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1: ["unequal", "of"],
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2: ["splits", "these"],
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3: [None, "things"],
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4: [None, "is"],
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5: [None, "not"],
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},
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dtype=any_string_dtype,
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)
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tm.assert_frame_equal(result, exp)
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def test_split_to_dataframe_with_index(any_string_dtype):
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s = Series(
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["some_splits", "with_index"], index=["preserve", "me"], dtype=any_string_dtype
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)
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result = s.str.split("_", expand=True)
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exp = DataFrame(
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{0: ["some", "with"], 1: ["splits", "index"]},
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index=["preserve", "me"],
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dtype=any_string_dtype,
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)
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tm.assert_frame_equal(result, exp)
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with pytest.raises(ValueError, match="expand must be"):
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s.str.split("_", expand="not_a_boolean")
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def test_split_to_multiindex_expand_no_splits():
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# https://github.com/pandas-dev/pandas/issues/23677
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idx = Index(["nosplit", "alsonosplit", np.nan])
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result = idx.str.split("_", expand=True)
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exp = idx
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tm.assert_index_equal(result, exp)
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assert result.nlevels == 1
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def test_split_to_multiindex_expand():
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idx = Index(["some_equal_splits", "with_no_nans", np.nan, None])
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result = idx.str.split("_", expand=True)
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exp = MultiIndex.from_tuples(
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[
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("some", "equal", "splits"),
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("with", "no", "nans"),
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[np.nan, np.nan, np.nan],
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[None, None, None],
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]
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)
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tm.assert_index_equal(result, exp)
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assert result.nlevels == 3
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def test_split_to_multiindex_expand_unequal_splits():
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idx = Index(["some_unequal_splits", "one_of_these_things_is_not", np.nan, None])
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result = idx.str.split("_", expand=True)
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exp = MultiIndex.from_tuples(
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[
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("some", "unequal", "splits", np.nan, np.nan, np.nan),
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("one", "of", "these", "things", "is", "not"),
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(np.nan, np.nan, np.nan, np.nan, np.nan, np.nan),
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(None, None, None, None, None, None),
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]
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)
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tm.assert_index_equal(result, exp)
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assert result.nlevels == 6
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with pytest.raises(ValueError, match="expand must be"):
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idx.str.split("_", expand="not_a_boolean")
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def test_rsplit_to_dataframe_expand_no_splits(any_string_dtype):
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s = Series(["nosplit", "alsonosplit"], dtype=any_string_dtype)
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result = s.str.rsplit("_", expand=True)
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exp = DataFrame({0: Series(["nosplit", "alsonosplit"])}, dtype=any_string_dtype)
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tm.assert_frame_equal(result, exp)
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def test_rsplit_to_dataframe_expand(any_string_dtype):
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s = Series(["some_equal_splits", "with_no_nans"], dtype=any_string_dtype)
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result = s.str.rsplit("_", expand=True)
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exp = DataFrame(
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{0: ["some", "with"], 1: ["equal", "no"], 2: ["splits", "nans"]},
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dtype=any_string_dtype,
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)
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tm.assert_frame_equal(result, exp)
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result = s.str.rsplit("_", expand=True, n=2)
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exp = DataFrame(
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{0: ["some", "with"], 1: ["equal", "no"], 2: ["splits", "nans"]},
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dtype=any_string_dtype,
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)
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tm.assert_frame_equal(result, exp)
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result = s.str.rsplit("_", expand=True, n=1)
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exp = DataFrame(
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{0: ["some_equal", "with_no"], 1: ["splits", "nans"]}, dtype=any_string_dtype
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)
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tm.assert_frame_equal(result, exp)
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|
|
def test_rsplit_to_dataframe_expand_with_index(any_string_dtype):
|
||
|
|
s = Series(
|
||
|
|
["some_splits", "with_index"], index=["preserve", "me"], dtype=any_string_dtype
|
||
|
|
)
|
||
|
|
result = s.str.rsplit("_", expand=True)
|
||
|
|
exp = DataFrame(
|
||
|
|
{0: ["some", "with"], 1: ["splits", "index"]},
|
||
|
|
index=["preserve", "me"],
|
||
|
|
dtype=any_string_dtype,
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, exp)
|
||
|
|
|
||
|
|
|
||
|
|
def test_rsplit_to_multiindex_expand_no_split():
|
||
|
|
idx = Index(["nosplit", "alsonosplit"])
|
||
|
|
result = idx.str.rsplit("_", expand=True)
|
||
|
|
exp = idx
|
||
|
|
tm.assert_index_equal(result, exp)
|
||
|
|
assert result.nlevels == 1
|
||
|
|
|
||
|
|
|
||
|
|
def test_rsplit_to_multiindex_expand():
|
||
|
|
idx = Index(["some_equal_splits", "with_no_nans"])
|
||
|
|
result = idx.str.rsplit("_", expand=True)
|
||
|
|
exp = MultiIndex.from_tuples([("some", "equal", "splits"), ("with", "no", "nans")])
|
||
|
|
tm.assert_index_equal(result, exp)
|
||
|
|
assert result.nlevels == 3
|
||
|
|
|
||
|
|
|
||
|
|
def test_rsplit_to_multiindex_expand_n():
|
||
|
|
idx = Index(["some_equal_splits", "with_no_nans"])
|
||
|
|
result = idx.str.rsplit("_", expand=True, n=1)
|
||
|
|
exp = MultiIndex.from_tuples([("some_equal", "splits"), ("with_no", "nans")])
|
||
|
|
tm.assert_index_equal(result, exp)
|
||
|
|
assert result.nlevels == 2
|
||
|
|
|
||
|
|
|
||
|
|
def test_split_nan_expand(any_string_dtype):
|
||
|
|
# gh-18450
|
||
|
|
s = Series(["foo,bar,baz", np.nan], dtype=any_string_dtype)
|
||
|
|
result = s.str.split(",", expand=True)
|
||
|
|
exp = DataFrame(
|
||
|
|
[["foo", "bar", "baz"], [np.nan, np.nan, np.nan]], dtype=any_string_dtype
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, exp)
|
||
|
|
|
||
|
|
# check that these are actually np.nan/pd.NA and not None
|
||
|
|
# TODO see GH 18463
|
||
|
|
# tm.assert_frame_equal does not differentiate
|
||
|
|
if any_string_dtype in object_pyarrow_numpy:
|
||
|
|
assert all(np.isnan(x) for x in result.iloc[1])
|
||
|
|
else:
|
||
|
|
assert all(x is pd.NA for x in result.iloc[1])
|
||
|
|
|
||
|
|
|
||
|
|
def test_split_with_name_series(any_string_dtype):
|
||
|
|
# GH 12617
|
||
|
|
|
||
|
|
# should preserve name
|
||
|
|
s = Series(["a,b", "c,d"], name="xxx", dtype=any_string_dtype)
|
||
|
|
res = s.str.split(",")
|
||
|
|
exp = Series([["a", "b"], ["c", "d"]], name="xxx")
|
||
|
|
tm.assert_series_equal(res, exp)
|
||
|
|
|
||
|
|
res = s.str.split(",", expand=True)
|
||
|
|
exp = DataFrame([["a", "b"], ["c", "d"]], dtype=any_string_dtype)
|
||
|
|
tm.assert_frame_equal(res, exp)
|
||
|
|
|
||
|
|
|
||
|
|
def test_split_with_name_index():
|
||
|
|
# GH 12617
|
||
|
|
idx = Index(["a,b", "c,d"], name="xxx")
|
||
|
|
res = idx.str.split(",")
|
||
|
|
exp = Index([["a", "b"], ["c", "d"]], name="xxx")
|
||
|
|
assert res.nlevels == 1
|
||
|
|
tm.assert_index_equal(res, exp)
|
||
|
|
|
||
|
|
res = idx.str.split(",", expand=True)
|
||
|
|
exp = MultiIndex.from_tuples([("a", "b"), ("c", "d")])
|
||
|
|
assert res.nlevels == 2
|
||
|
|
tm.assert_index_equal(res, exp)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, exp",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
[
|
||
|
|
("a", "__", "b__c"),
|
||
|
|
("c", "__", "d__e"),
|
||
|
|
np.nan,
|
||
|
|
("f", "__", "g__h"),
|
||
|
|
None,
|
||
|
|
],
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
[
|
||
|
|
("a__b", "__", "c"),
|
||
|
|
("c__d", "__", "e"),
|
||
|
|
np.nan,
|
||
|
|
("f__g", "__", "h"),
|
||
|
|
None,
|
||
|
|
],
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_series_more_than_one_char(method, exp, any_string_dtype):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
# more than one char
|
||
|
|
s = Series(["a__b__c", "c__d__e", np.nan, "f__g__h", None], dtype=any_string_dtype)
|
||
|
|
result = getattr(s.str, method)("__", expand=False)
|
||
|
|
expected = Series(exp)
|
||
|
|
expected = _convert_na_value(s, expected)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, exp",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
[("a", " ", "b c"), ("c", " ", "d e"), np.nan, ("f", " ", "g h"), None],
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
[("a b", " ", "c"), ("c d", " ", "e"), np.nan, ("f g", " ", "h"), None],
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_series_none(any_string_dtype, method, exp):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
# None
|
||
|
|
s = Series(["a b c", "c d e", np.nan, "f g h", None], dtype=any_string_dtype)
|
||
|
|
result = getattr(s.str, method)(expand=False)
|
||
|
|
expected = Series(exp)
|
||
|
|
expected = _convert_na_value(s, expected)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, exp",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
[("abc", "", ""), ("cde", "", ""), np.nan, ("fgh", "", ""), None],
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
[("", "", "abc"), ("", "", "cde"), np.nan, ("", "", "fgh"), None],
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_series_not_split(any_string_dtype, method, exp):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
# Not split
|
||
|
|
s = Series(["abc", "cde", np.nan, "fgh", None], dtype=any_string_dtype)
|
||
|
|
result = getattr(s.str, method)("_", expand=False)
|
||
|
|
expected = Series(exp)
|
||
|
|
expected = _convert_na_value(s, expected)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, exp",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
[("a", "_", "b_c"), ("c", "_", "d_e"), np.nan, ("f", "_", "g_h")],
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
[("a_b", "_", "c"), ("c_d", "_", "e"), np.nan, ("f_g", "_", "h")],
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_series_unicode(any_string_dtype, method, exp):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
# unicode
|
||
|
|
s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype)
|
||
|
|
|
||
|
|
result = getattr(s.str, method)("_", expand=False)
|
||
|
|
expected = Series(exp)
|
||
|
|
expected = _convert_na_value(s, expected)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("method", ["partition", "rpartition"])
|
||
|
|
def test_partition_series_stdlib(any_string_dtype, method):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
# compare to standard lib
|
||
|
|
s = Series(["A_B_C", "B_C_D", "E_F_G", "EFGHEF"], dtype=any_string_dtype)
|
||
|
|
result = getattr(s.str, method)("_", expand=False).tolist()
|
||
|
|
assert result == [getattr(v, method)("_") for v in s]
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, expand, exp, exp_levels",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
False,
|
||
|
|
np.array(
|
||
|
|
[("a", "_", "b_c"), ("c", "_", "d_e"), ("f", "_", "g_h"), np.nan, None],
|
||
|
|
dtype=object,
|
||
|
|
),
|
||
|
|
1,
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
False,
|
||
|
|
np.array(
|
||
|
|
[("a_b", "_", "c"), ("c_d", "_", "e"), ("f_g", "_", "h"), np.nan, None],
|
||
|
|
dtype=object,
|
||
|
|
),
|
||
|
|
1,
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_index(method, expand, exp, exp_levels):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
|
||
|
|
values = Index(["a_b_c", "c_d_e", "f_g_h", np.nan, None])
|
||
|
|
|
||
|
|
result = getattr(values.str, method)("_", expand=expand)
|
||
|
|
exp = Index(exp)
|
||
|
|
tm.assert_index_equal(result, exp)
|
||
|
|
assert result.nlevels == exp_levels
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, exp",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
{
|
||
|
|
0: ["a", "c", np.nan, "f", None],
|
||
|
|
1: ["_", "_", np.nan, "_", None],
|
||
|
|
2: ["b_c", "d_e", np.nan, "g_h", None],
|
||
|
|
},
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
{
|
||
|
|
0: ["a_b", "c_d", np.nan, "f_g", None],
|
||
|
|
1: ["_", "_", np.nan, "_", None],
|
||
|
|
2: ["c", "e", np.nan, "h", None],
|
||
|
|
},
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_to_dataframe(any_string_dtype, method, exp):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
|
||
|
|
s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h", None], dtype=any_string_dtype)
|
||
|
|
result = getattr(s.str, method)("_")
|
||
|
|
expected = DataFrame(
|
||
|
|
exp,
|
||
|
|
dtype=any_string_dtype,
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"method, exp",
|
||
|
|
[
|
||
|
|
[
|
||
|
|
"partition",
|
||
|
|
{
|
||
|
|
0: ["a", "c", np.nan, "f", None],
|
||
|
|
1: ["_", "_", np.nan, "_", None],
|
||
|
|
2: ["b_c", "d_e", np.nan, "g_h", None],
|
||
|
|
},
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"rpartition",
|
||
|
|
{
|
||
|
|
0: ["a_b", "c_d", np.nan, "f_g", None],
|
||
|
|
1: ["_", "_", np.nan, "_", None],
|
||
|
|
2: ["c", "e", np.nan, "h", None],
|
||
|
|
},
|
||
|
|
],
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_partition_to_dataframe_from_series(any_string_dtype, method, exp):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/23558
|
||
|
|
s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h", None], dtype=any_string_dtype)
|
||
|
|
result = getattr(s.str, method)("_", expand=True)
|
||
|
|
expected = DataFrame(
|
||
|
|
exp,
|
||
|
|
dtype=any_string_dtype,
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_partition_with_name(any_string_dtype):
|
||
|
|
# GH 12617
|
||
|
|
|
||
|
|
s = Series(["a,b", "c,d"], name="xxx", dtype=any_string_dtype)
|
||
|
|
result = s.str.partition(",")
|
||
|
|
expected = DataFrame(
|
||
|
|
{0: ["a", "c"], 1: [",", ","], 2: ["b", "d"]}, dtype=any_string_dtype
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_partition_with_name_expand(any_string_dtype):
|
||
|
|
# GH 12617
|
||
|
|
# should preserve name
|
||
|
|
s = Series(["a,b", "c,d"], name="xxx", dtype=any_string_dtype)
|
||
|
|
result = s.str.partition(",", expand=False)
|
||
|
|
expected = Series([("a", ",", "b"), ("c", ",", "d")], name="xxx")
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_partition_index_with_name():
|
||
|
|
idx = Index(["a,b", "c,d"], name="xxx")
|
||
|
|
result = idx.str.partition(",")
|
||
|
|
expected = MultiIndex.from_tuples([("a", ",", "b"), ("c", ",", "d")])
|
||
|
|
assert result.nlevels == 3
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_partition_index_with_name_expand_false():
|
||
|
|
idx = Index(["a,b", "c,d"], name="xxx")
|
||
|
|
# should preserve name
|
||
|
|
result = idx.str.partition(",", expand=False)
|
||
|
|
expected = Index(np.array([("a", ",", "b"), ("c", ",", "d")]), name="xxx")
|
||
|
|
assert result.nlevels == 1
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("method", ["partition", "rpartition"])
|
||
|
|
def test_partition_sep_kwarg(any_string_dtype, method):
|
||
|
|
# GH 22676; depr kwarg "pat" in favor of "sep"
|
||
|
|
s = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype)
|
||
|
|
|
||
|
|
expected = getattr(s.str, method)(sep="_")
|
||
|
|
result = getattr(s.str, method)("_")
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_get():
|
||
|
|
ser = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"])
|
||
|
|
result = ser.str.split("_").str.get(1)
|
||
|
|
expected = Series(["b", "d", np.nan, "g"], dtype=object)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_get_mixed_object():
|
||
|
|
ser = Series(["a_b_c", np.nan, "c_d_e", True, datetime.today(), None, 1, 2.0])
|
||
|
|
result = ser.str.split("_").str.get(1)
|
||
|
|
expected = Series(
|
||
|
|
["b", np.nan, "d", np.nan, np.nan, None, np.nan, np.nan], dtype=object
|
||
|
|
)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("idx", [2, -3])
|
||
|
|
def test_get_bounds(idx):
|
||
|
|
ser = Series(["1_2_3_4_5", "6_7_8_9_10", "11_12"])
|
||
|
|
result = ser.str.split("_").str.get(idx)
|
||
|
|
expected = Series(["3", "8", np.nan], dtype=object)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"idx, exp", [[2, [3, 3, np.nan, "b"]], [-1, [3, 3, np.nan, np.nan]]]
|
||
|
|
)
|
||
|
|
def test_get_complex(idx, exp):
|
||
|
|
# GH 20671, getting value not in dict raising `KeyError`
|
||
|
|
ser = Series([(1, 2, 3), [1, 2, 3], {1, 2, 3}, {1: "a", 2: "b", 3: "c"}])
|
||
|
|
|
||
|
|
result = ser.str.get(idx)
|
||
|
|
expected = Series(exp)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("to_type", [tuple, list, np.array])
|
||
|
|
def test_get_complex_nested(to_type):
|
||
|
|
ser = Series([to_type([to_type([1, 2])])])
|
||
|
|
|
||
|
|
result = ser.str.get(0)
|
||
|
|
expected = Series([to_type([1, 2])])
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
result = ser.str.get(1)
|
||
|
|
expected = Series([np.nan])
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_get_strings(any_string_dtype):
|
||
|
|
ser = Series(["a", "ab", np.nan, "abc"], dtype=any_string_dtype)
|
||
|
|
result = ser.str.get(2)
|
||
|
|
expected = Series([np.nan, np.nan, np.nan, "c"], dtype=any_string_dtype)
|
||
|
|
tm.assert_series_equal(result, expected)
|