848 lines
28 KiB
Python
848 lines
28 KiB
Python
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from datetime import (
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datetime,
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timedelta,
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)
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import numpy as np
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import pytest
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from pandas.compat import (
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pa_version_under2p0,
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pa_version_under4p0,
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)
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from pandas.errors import PerformanceWarning
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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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isna,
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)
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import pandas._testing as tm
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@pytest.mark.parametrize("pattern", [0, True, Series(["foo", "bar"])])
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def test_startswith_endswith_non_str_patterns(pattern):
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# GH3485
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ser = Series(["foo", "bar"])
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msg = f"expected a string or tuple, not {type(pattern).__name__}"
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with pytest.raises(TypeError, match=msg):
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ser.str.startswith(pattern)
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with pytest.raises(TypeError, match=msg):
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ser.str.endswith(pattern)
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def assert_series_or_index_equal(left, right):
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if isinstance(left, Series):
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tm.assert_series_equal(left, right)
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else: # Index
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tm.assert_index_equal(left, right)
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def test_iter():
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# GH3638
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strs = "google", "wikimedia", "wikipedia", "wikitravel"
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ser = Series(strs)
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with tm.assert_produces_warning(FutureWarning):
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for s in ser.str:
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# iter must yield a Series
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assert isinstance(s, Series)
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# indices of each yielded Series should be equal to the index of
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# the original Series
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tm.assert_index_equal(s.index, ser.index)
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for el in s:
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# each element of the series is either a basestring/str or nan
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assert isinstance(el, str) or isna(el)
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# desired behavior is to iterate until everything would be nan on the
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# next iter so make sure the last element of the iterator was 'l' in
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# this case since 'wikitravel' is the longest string
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assert s.dropna().values.item() == "l"
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def test_iter_empty(any_string_dtype):
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ser = Series([], dtype=any_string_dtype)
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i, s = 100, 1
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with tm.assert_produces_warning(FutureWarning):
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for i, s in enumerate(ser.str):
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pass
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# nothing to iterate over so nothing defined values should remain
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# unchanged
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assert i == 100
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assert s == 1
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def test_iter_single_element(any_string_dtype):
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ser = Series(["a"], dtype=any_string_dtype)
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with tm.assert_produces_warning(FutureWarning):
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for i, s in enumerate(ser.str):
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pass
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assert not i
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tm.assert_series_equal(ser, s)
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def test_iter_object_try_string():
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ser = Series(
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[
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slice(None, np.random.randint(10), np.random.randint(10, 20))
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for _ in range(4)
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]
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)
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i, s = 100, "h"
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with tm.assert_produces_warning(FutureWarning):
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for i, s in enumerate(ser.str):
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pass
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assert i == 100
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assert s == "h"
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# test integer/float dtypes (inferred by constructor) and mixed
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def test_count(any_string_dtype):
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ser = Series(["foo", "foofoo", np.nan, "foooofooofommmfoo"], dtype=any_string_dtype)
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result = ser.str.count("f[o]+")
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expected_dtype = np.float64 if any_string_dtype == "object" else "Int64"
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expected = Series([1, 2, np.nan, 4], dtype=expected_dtype)
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tm.assert_series_equal(result, expected)
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def test_count_mixed_object():
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ser = Series(
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["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0],
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dtype=object,
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)
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result = ser.str.count("a")
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expected = Series([1, np.nan, 0, np.nan, np.nan, 0, np.nan, np.nan, np.nan])
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tm.assert_series_equal(result, expected)
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def test_repeat(any_string_dtype):
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ser = Series(["a", "b", np.nan, "c", np.nan, "d"], dtype=any_string_dtype)
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result = ser.str.repeat(3)
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expected = Series(
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["aaa", "bbb", np.nan, "ccc", np.nan, "ddd"], dtype=any_string_dtype
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)
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tm.assert_series_equal(result, expected)
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result = ser.str.repeat([1, 2, 3, 4, 5, 6])
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expected = Series(
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["a", "bb", np.nan, "cccc", np.nan, "dddddd"], dtype=any_string_dtype
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)
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tm.assert_series_equal(result, expected)
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def test_repeat_mixed_object():
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ser = Series(["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0])
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result = ser.str.repeat(3)
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expected = Series(
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["aaa", np.nan, "bbb", np.nan, np.nan, "foofoofoo", np.nan, np.nan, np.nan]
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)
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize("arg, repeat", [[None, 4], ["b", None]])
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def test_repeat_with_null(any_string_dtype, arg, repeat):
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# GH: 31632
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ser = Series(["a", arg], dtype=any_string_dtype)
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result = ser.str.repeat([3, repeat])
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expected = Series(["aaa", np.nan], dtype=any_string_dtype)
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tm.assert_series_equal(result, expected)
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def test_empty_str_methods(any_string_dtype):
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empty_str = empty = Series(dtype=any_string_dtype)
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if any_string_dtype == "object":
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empty_int = Series(dtype="int64")
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empty_bool = Series(dtype=bool)
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else:
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empty_int = Series(dtype="Int64")
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empty_bool = Series(dtype="boolean")
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empty_object = Series(dtype=object)
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empty_bytes = Series(dtype=object)
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empty_df = DataFrame()
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# GH7241
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# (extract) on empty series
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tm.assert_series_equal(empty_str, empty.str.cat(empty))
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assert "" == empty.str.cat()
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tm.assert_series_equal(empty_str, empty.str.title())
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tm.assert_series_equal(empty_int, empty.str.count("a"))
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_bool, empty.str.contains("a"))
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_bool, empty.str.startswith("a"))
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_bool, empty.str.endswith("a"))
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tm.assert_series_equal(empty_str, empty.str.lower())
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tm.assert_series_equal(empty_str, empty.str.upper())
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_str, empty.str.replace("a", "b"))
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tm.assert_series_equal(empty_str, empty.str.repeat(3))
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_bool, empty.str.match("^a"))
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tm.assert_frame_equal(
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DataFrame(columns=[0], dtype=any_string_dtype),
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empty.str.extract("()", expand=True),
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)
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tm.assert_frame_equal(
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DataFrame(columns=[0, 1], dtype=any_string_dtype),
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empty.str.extract("()()", expand=True),
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)
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tm.assert_series_equal(empty_str, empty.str.extract("()", expand=False))
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tm.assert_frame_equal(
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DataFrame(columns=[0, 1], dtype=any_string_dtype),
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empty.str.extract("()()", expand=False),
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)
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tm.assert_frame_equal(empty_df, empty.str.get_dummies())
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tm.assert_series_equal(empty_str, empty_str.str.join(""))
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_int, empty.str.len())
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tm.assert_series_equal(empty_object, empty_str.str.findall("a"))
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tm.assert_series_equal(empty_int, empty.str.find("a"))
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tm.assert_series_equal(empty_int, empty.str.rfind("a"))
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tm.assert_series_equal(empty_str, empty.str.pad(42))
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tm.assert_series_equal(empty_str, empty.str.center(42))
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tm.assert_series_equal(empty_object, empty.str.split("a"))
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tm.assert_series_equal(empty_object, empty.str.rsplit("a"))
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tm.assert_series_equal(empty_object, empty.str.partition("a", expand=False))
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tm.assert_frame_equal(empty_df, empty.str.partition("a"))
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tm.assert_series_equal(empty_object, empty.str.rpartition("a", expand=False))
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tm.assert_frame_equal(empty_df, empty.str.rpartition("a"))
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tm.assert_series_equal(empty_str, empty.str.slice(stop=1))
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tm.assert_series_equal(empty_str, empty.str.slice(step=1))
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_str, empty.str.strip())
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_str, empty.str.lstrip())
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with tm.maybe_produces_warning(
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PerformanceWarning,
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any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
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):
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tm.assert_series_equal(empty_str, empty.str.rstrip())
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tm.assert_series_equal(empty_str, empty.str.wrap(42))
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tm.assert_series_equal(empty_str, empty.str.get(0))
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tm.assert_series_equal(empty_object, empty_bytes.str.decode("ascii"))
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tm.assert_series_equal(empty_bytes, empty.str.encode("ascii"))
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# ismethods should always return boolean (GH 29624)
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tm.assert_series_equal(empty_bool, empty.str.isalnum())
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tm.assert_series_equal(empty_bool, empty.str.isalpha())
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tm.assert_series_equal(empty_bool, empty.str.isdigit())
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with tm.maybe_produces_warning(
|
|||
|
|
PerformanceWarning,
|
|||
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any_string_dtype == "string[pyarrow]" and pa_version_under2p0,
|
|||
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):
|
|||
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tm.assert_series_equal(empty_bool, empty.str.isspace())
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tm.assert_series_equal(empty_bool, empty.str.islower())
|
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tm.assert_series_equal(empty_bool, empty.str.isupper())
|
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|
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tm.assert_series_equal(empty_bool, empty.str.istitle())
|
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tm.assert_series_equal(empty_bool, empty.str.isnumeric())
|
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|
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tm.assert_series_equal(empty_bool, empty.str.isdecimal())
|
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|
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tm.assert_series_equal(empty_str, empty.str.capitalize())
|
|||
|
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tm.assert_series_equal(empty_str, empty.str.swapcase())
|
|||
|
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tm.assert_series_equal(empty_str, empty.str.normalize("NFC"))
|
|||
|
|
|
|||
|
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table = str.maketrans("a", "b")
|
|||
|
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tm.assert_series_equal(empty_str, empty.str.translate(table))
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, expected",
|
|||
|
|
[
|
|||
|
|
("isalnum", [True, True, True, True, True, False, True, True, False, False]),
|
|||
|
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("isalpha", [True, True, True, False, False, False, True, False, False, False]),
|
|||
|
|
(
|
|||
|
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"isdigit",
|
|||
|
|
[False, False, False, True, False, False, False, True, False, False],
|
|||
|
|
),
|
|||
|
|
(
|
|||
|
|
"isnumeric",
|
|||
|
|
[False, False, False, True, False, False, False, True, False, False],
|
|||
|
|
),
|
|||
|
|
(
|
|||
|
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"isspace",
|
|||
|
|
[False, False, False, False, False, False, False, False, False, True],
|
|||
|
|
),
|
|||
|
|
(
|
|||
|
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"islower",
|
|||
|
|
[False, True, False, False, False, False, False, False, False, False],
|
|||
|
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),
|
|||
|
|
(
|
|||
|
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"isupper",
|
|||
|
|
[True, False, False, False, True, False, True, False, False, False],
|
|||
|
|
),
|
|||
|
|
(
|
|||
|
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"istitle",
|
|||
|
|
[True, False, True, False, True, False, False, False, False, False],
|
|||
|
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),
|
|||
|
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],
|
|||
|
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)
|
|||
|
|
def test_ismethods(method, expected, any_string_dtype):
|
|||
|
|
ser = Series(
|
|||
|
|
["A", "b", "Xy", "4", "3A", "", "TT", "55", "-", " "], dtype=any_string_dtype
|
|||
|
|
)
|
|||
|
|
expected_dtype = "bool" if any_string_dtype == "object" else "boolean"
|
|||
|
|
expected = Series(expected, dtype=expected_dtype)
|
|||
|
|
with tm.maybe_produces_warning(
|
|||
|
|
PerformanceWarning,
|
|||
|
|
any_string_dtype == "string[pyarrow]"
|
|||
|
|
and pa_version_under2p0
|
|||
|
|
and method == "isspace",
|
|||
|
|
):
|
|||
|
|
result = getattr(ser.str, method)()
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
# compare with standard library
|
|||
|
|
expected = [getattr(item, method)() for item in ser]
|
|||
|
|
assert list(result) == expected
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, expected",
|
|||
|
|
[
|
|||
|
|
("isnumeric", [False, True, True, False, True, True, False]),
|
|||
|
|
("isdecimal", [False, True, False, False, False, True, False]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_isnumeric_unicode(method, expected, any_string_dtype):
|
|||
|
|
# 0x00bc: ¼ VULGAR FRACTION ONE QUARTER
|
|||
|
|
# 0x2605: ★ not number
|
|||
|
|
# 0x1378: ፸ ETHIOPIC NUMBER SEVENTY
|
|||
|
|
# 0xFF13: ３ Em 3
|
|||
|
|
ser = Series(["A", "3", "¼", "★", "፸", "３", "four"], dtype=any_string_dtype)
|
|||
|
|
expected_dtype = "bool" if any_string_dtype == "object" else "boolean"
|
|||
|
|
expected = Series(expected, dtype=expected_dtype)
|
|||
|
|
result = getattr(ser.str, method)()
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
# compare with standard library
|
|||
|
|
expected = [getattr(item, method)() for item in ser]
|
|||
|
|
assert list(result) == expected
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, expected",
|
|||
|
|
[
|
|||
|
|
("isnumeric", [False, np.nan, True, False, np.nan, True, False]),
|
|||
|
|
("isdecimal", [False, np.nan, False, False, np.nan, True, False]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_isnumeric_unicode_missing(method, expected, any_string_dtype):
|
|||
|
|
values = ["A", np.nan, "¼", "★", np.nan, "３", "four"]
|
|||
|
|
ser = Series(values, dtype=any_string_dtype)
|
|||
|
|
expected_dtype = "object" if any_string_dtype == "object" else "boolean"
|
|||
|
|
expected = Series(expected, dtype=expected_dtype)
|
|||
|
|
result = getattr(ser.str, method)()
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_spilt_join_roundtrip(any_string_dtype):
|
|||
|
|
ser = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype)
|
|||
|
|
result = ser.str.split("_").str.join("_")
|
|||
|
|
expected = ser.astype(object)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_spilt_join_roundtrip_mixed_object():
|
|||
|
|
ser = Series(
|
|||
|
|
["a_b", np.nan, "asdf_cas_asdf", True, datetime.today(), "foo", None, 1, 2.0]
|
|||
|
|
)
|
|||
|
|
result = ser.str.split("_").str.join("_")
|
|||
|
|
expected = Series(
|
|||
|
|
["a_b", np.nan, "asdf_cas_asdf", np.nan, np.nan, "foo", np.nan, np.nan, np.nan]
|
|||
|
|
)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_len(any_string_dtype):
|
|||
|
|
ser = Series(
|
|||
|
|
["foo", "fooo", "fooooo", np.nan, "fooooooo", "foo\n", "あ"],
|
|||
|
|
dtype=any_string_dtype,
|
|||
|
|
)
|
|||
|
|
with tm.maybe_produces_warning(
|
|||
|
|
PerformanceWarning,
|
|||
|
|
any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
|
|||
|
|
):
|
|||
|
|
result = ser.str.len()
|
|||
|
|
expected_dtype = "float64" if any_string_dtype == "object" else "Int64"
|
|||
|
|
expected = Series([3, 4, 6, np.nan, 8, 4, 1], dtype=expected_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_len_mixed():
|
|||
|
|
ser = Series(
|
|||
|
|
["a_b", np.nan, "asdf_cas_asdf", True, datetime.today(), "foo", None, 1, 2.0]
|
|||
|
|
)
|
|||
|
|
result = ser.str.len()
|
|||
|
|
expected = Series([3, np.nan, 13, np.nan, np.nan, 3, np.nan, np.nan, np.nan])
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method,sub,start,end,expected",
|
|||
|
|
[
|
|||
|
|
("index", "EF", None, None, [4, 3, 1, 0]),
|
|||
|
|
("rindex", "EF", None, None, [4, 5, 7, 4]),
|
|||
|
|
("index", "EF", 3, None, [4, 3, 7, 4]),
|
|||
|
|
("rindex", "EF", 3, None, [4, 5, 7, 4]),
|
|||
|
|
("index", "E", 4, 8, [4, 5, 7, 4]),
|
|||
|
|
("rindex", "E", 0, 5, [4, 3, 1, 4]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_index(method, sub, start, end, index_or_series, any_string_dtype, expected):
|
|||
|
|
|
|||
|
|
obj = index_or_series(
|
|||
|
|
["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF"], dtype=any_string_dtype
|
|||
|
|
)
|
|||
|
|
expected_dtype = np.int64 if any_string_dtype == "object" else "Int64"
|
|||
|
|
expected = index_or_series(expected, dtype=expected_dtype)
|
|||
|
|
|
|||
|
|
result = getattr(obj.str, method)(sub, start, end)
|
|||
|
|
|
|||
|
|
if index_or_series is Series:
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
else:
|
|||
|
|
tm.assert_index_equal(result, expected)
|
|||
|
|
|
|||
|
|
# compare with standard library
|
|||
|
|
expected = [getattr(item, method)(sub, start, end) for item in obj]
|
|||
|
|
assert list(result) == expected
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_index_not_found_raises(index_or_series, any_string_dtype):
|
|||
|
|
obj = index_or_series(
|
|||
|
|
["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF"], dtype=any_string_dtype
|
|||
|
|
)
|
|||
|
|
with pytest.raises(ValueError, match="substring not found"):
|
|||
|
|
obj.str.index("DE")
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize("method", ["index", "rindex"])
|
|||
|
|
def test_index_wrong_type_raises(index_or_series, any_string_dtype, method):
|
|||
|
|
obj = index_or_series([], dtype=any_string_dtype)
|
|||
|
|
msg = "expected a string object, not int"
|
|||
|
|
|
|||
|
|
with pytest.raises(TypeError, match=msg):
|
|||
|
|
getattr(obj.str, method)(0)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, exp",
|
|||
|
|
[
|
|||
|
|
["index", [1, 1, 0]],
|
|||
|
|
["rindex", [3, 1, 2]],
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_index_missing(any_string_dtype, method, exp):
|
|||
|
|
ser = Series(["abcb", "ab", "bcbe", np.nan], dtype=any_string_dtype)
|
|||
|
|
expected_dtype = np.float64 if any_string_dtype == "object" else "Int64"
|
|||
|
|
|
|||
|
|
result = getattr(ser.str, method)("b")
|
|||
|
|
expected = Series(exp + [np.nan], dtype=expected_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_pipe_failures(any_string_dtype):
|
|||
|
|
# #2119
|
|||
|
|
ser = Series(["A|B|C"], dtype=any_string_dtype)
|
|||
|
|
|
|||
|
|
result = ser.str.split("|")
|
|||
|
|
expected = Series([["A", "B", "C"]], dtype=object)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
with tm.maybe_produces_warning(
|
|||
|
|
PerformanceWarning,
|
|||
|
|
any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
|
|||
|
|
):
|
|||
|
|
result = ser.str.replace("|", " ", regex=False)
|
|||
|
|
expected = Series(["A B C"], dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"start, stop, step, expected",
|
|||
|
|
[
|
|||
|
|
(2, 5, None, ["foo", "bar", np.nan, "baz"]),
|
|||
|
|
(0, 3, -1, ["", "", np.nan, ""]),
|
|||
|
|
(None, None, -1, ["owtoofaa", "owtrabaa", np.nan, "xuqzabaa"]),
|
|||
|
|
(3, 10, 2, ["oto", "ato", np.nan, "aqx"]),
|
|||
|
|
(3, 0, -1, ["ofa", "aba", np.nan, "aba"]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_slice(start, stop, step, expected, any_string_dtype):
|
|||
|
|
ser = Series(["aafootwo", "aabartwo", np.nan, "aabazqux"], dtype=any_string_dtype)
|
|||
|
|
result = ser.str.slice(start, stop, step)
|
|||
|
|
expected = Series(expected, dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"start, stop, step, expected",
|
|||
|
|
[
|
|||
|
|
(2, 5, None, ["foo", np.nan, "bar", np.nan, np.nan, np.nan, np.nan, np.nan]),
|
|||
|
|
(4, 1, -1, ["oof", np.nan, "rab", np.nan, np.nan, np.nan, np.nan, np.nan]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_slice_mixed_object(start, stop, step, expected):
|
|||
|
|
ser = Series(["aafootwo", np.nan, "aabartwo", True, datetime.today(), None, 1, 2.0])
|
|||
|
|
result = ser.str.slice(start, stop, step)
|
|||
|
|
expected = Series(expected)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"start,stop,repl,expected",
|
|||
|
|
[
|
|||
|
|
(2, 3, None, ["shrt", "a it longer", "evnlongerthanthat", "", np.nan]),
|
|||
|
|
(2, 3, "z", ["shzrt", "a zit longer", "evznlongerthanthat", "z", np.nan]),
|
|||
|
|
(2, 2, "z", ["shzort", "a zbit longer", "evzenlongerthanthat", "z", np.nan]),
|
|||
|
|
(2, 1, "z", ["shzort", "a zbit longer", "evzenlongerthanthat", "z", np.nan]),
|
|||
|
|
(-1, None, "z", ["shorz", "a bit longez", "evenlongerthanthaz", "z", np.nan]),
|
|||
|
|
(None, -2, "z", ["zrt", "zer", "zat", "z", np.nan]),
|
|||
|
|
(6, 8, "z", ["shortz", "a bit znger", "evenlozerthanthat", "z", np.nan]),
|
|||
|
|
(-10, 3, "z", ["zrt", "a zit longer", "evenlongzerthanthat", "z", np.nan]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_slice_replace(start, stop, repl, expected, any_string_dtype):
|
|||
|
|
ser = Series(
|
|||
|
|
["short", "a bit longer", "evenlongerthanthat", "", np.nan],
|
|||
|
|
dtype=any_string_dtype,
|
|||
|
|
)
|
|||
|
|
expected = Series(expected, dtype=any_string_dtype)
|
|||
|
|
result = ser.str.slice_replace(start, stop, repl)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, exp",
|
|||
|
|
[
|
|||
|
|
["strip", ["aa", "bb", np.nan, "cc"]],
|
|||
|
|
["lstrip", ["aa ", "bb \n", np.nan, "cc "]],
|
|||
|
|
["rstrip", [" aa", " bb", np.nan, "cc"]],
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_strip_lstrip_rstrip(any_string_dtype, method, exp):
|
|||
|
|
ser = Series([" aa ", " bb \n", np.nan, "cc "], dtype=any_string_dtype)
|
|||
|
|
|
|||
|
|
with tm.maybe_produces_warning(
|
|||
|
|
PerformanceWarning,
|
|||
|
|
any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
|
|||
|
|
):
|
|||
|
|
result = getattr(ser.str, method)()
|
|||
|
|
expected = Series(exp, dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, exp",
|
|||
|
|
[
|
|||
|
|
["strip", ["aa", np.nan, "bb"]],
|
|||
|
|
["lstrip", ["aa ", np.nan, "bb \t\n"]],
|
|||
|
|
["rstrip", [" aa", np.nan, " bb"]],
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_strip_lstrip_rstrip_mixed_object(method, exp):
|
|||
|
|
ser = Series([" aa ", np.nan, " bb \t\n", True, datetime.today(), None, 1, 2.0])
|
|||
|
|
|
|||
|
|
result = getattr(ser.str, method)()
|
|||
|
|
expected = Series(exp + [np.nan, np.nan, np.nan, np.nan, np.nan])
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"method, exp",
|
|||
|
|
[
|
|||
|
|
["strip", ["ABC", " BNSD", "LDFJH "]],
|
|||
|
|
["lstrip", ["ABCxx", " BNSD", "LDFJH xx"]],
|
|||
|
|
["rstrip", ["xxABC", "xx BNSD", "LDFJH "]],
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_strip_lstrip_rstrip_args(any_string_dtype, method, exp):
|
|||
|
|
ser = Series(["xxABCxx", "xx BNSD", "LDFJH xx"], dtype=any_string_dtype)
|
|||
|
|
|
|||
|
|
with tm.maybe_produces_warning(
|
|||
|
|
PerformanceWarning,
|
|||
|
|
any_string_dtype == "string[pyarrow]" and pa_version_under4p0,
|
|||
|
|
):
|
|||
|
|
result = getattr(ser.str, method)("x")
|
|||
|
|
expected = Series(exp, dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"prefix, expected", [("a", ["b", " b c", "bc"]), ("ab", ["", "a b c", "bc"])]
|
|||
|
|
)
|
|||
|
|
def test_removeprefix(any_string_dtype, prefix, expected):
|
|||
|
|
ser = Series(["ab", "a b c", "bc"], dtype=any_string_dtype)
|
|||
|
|
result = ser.str.removeprefix(prefix)
|
|||
|
|
ser_expected = Series(expected, dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, ser_expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"suffix, expected", [("c", ["ab", "a b ", "b"]), ("bc", ["ab", "a b c", ""])]
|
|||
|
|
)
|
|||
|
|
def test_removesuffix(any_string_dtype, suffix, expected):
|
|||
|
|
ser = Series(["ab", "a b c", "bc"], dtype=any_string_dtype)
|
|||
|
|
result = ser.str.removesuffix(suffix)
|
|||
|
|
ser_expected = Series(expected, dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, ser_expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_string_slice_get_syntax(any_string_dtype):
|
|||
|
|
ser = Series(
|
|||
|
|
["YYY", "B", "C", "YYYYYYbYYY", "BYYYcYYY", np.nan, "CYYYBYYY", "dog", "cYYYt"],
|
|||
|
|
dtype=any_string_dtype,
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
result = ser.str[0]
|
|||
|
|
expected = ser.str.get(0)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
result = ser.str[:3]
|
|||
|
|
expected = ser.str.slice(stop=3)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
result = ser.str[2::-1]
|
|||
|
|
expected = ser.str.slice(start=2, step=-1)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_string_slice_out_of_bounds_nested():
|
|||
|
|
ser = Series([(1, 2), (1,), (3, 4, 5)])
|
|||
|
|
result = ser.str[1]
|
|||
|
|
expected = Series([2, np.nan, 4])
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_string_slice_out_of_bounds(any_string_dtype):
|
|||
|
|
ser = Series(["foo", "b", "ba"], dtype=any_string_dtype)
|
|||
|
|
result = ser.str[1]
|
|||
|
|
expected = Series(["o", np.nan, "a"], dtype=any_string_dtype)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_encode_decode(any_string_dtype):
|
|||
|
|
ser = Series(["a", "b", "a\xe4"], dtype=any_string_dtype).str.encode("utf-8")
|
|||
|
|
result = ser.str.decode("utf-8")
|
|||
|
|
expected = ser.map(lambda x: x.decode("utf-8"))
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_encode_errors_kwarg(any_string_dtype):
|
|||
|
|
ser = Series(["a", "b", "a\x9d"], dtype=any_string_dtype)
|
|||
|
|
|
|||
|
|
msg = (
|
|||
|
|
r"'charmap' codec can't encode character '\\x9d' in position 1: "
|
|||
|
|
"character maps to <undefined>"
|
|||
|
|
)
|
|||
|
|
with pytest.raises(UnicodeEncodeError, match=msg):
|
|||
|
|
ser.str.encode("cp1252")
|
|||
|
|
|
|||
|
|
result = ser.str.encode("cp1252", "ignore")
|
|||
|
|
expected = ser.map(lambda x: x.encode("cp1252", "ignore"))
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_decode_errors_kwarg():
|
|||
|
|
ser = Series([b"a", b"b", b"a\x9d"])
|
|||
|
|
|
|||
|
|
msg = (
|
|||
|
|
"'charmap' codec can't decode byte 0x9d in position 1: "
|
|||
|
|
"character maps to <undefined>"
|
|||
|
|
)
|
|||
|
|
with pytest.raises(UnicodeDecodeError, match=msg):
|
|||
|
|
ser.str.decode("cp1252")
|
|||
|
|
|
|||
|
|
result = ser.str.decode("cp1252", "ignore")
|
|||
|
|
expected = ser.map(lambda x: x.decode("cp1252", "ignore"))
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"form, expected",
|
|||
|
|
[
|
|||
|
|
("NFKC", ["ABC", "ABC", "123", np.nan, "アイエ"]),
|
|||
|
|
("NFC", ["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"]),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_normalize(form, expected, any_string_dtype):
|
|||
|
|
ser = Series(
|
|||
|
|
["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"],
|
|||
|
|
index=["a", "b", "c", "d", "e"],
|
|||
|
|
dtype=any_string_dtype,
|
|||
|
|
)
|
|||
|
|
expected = Series(expected, index=["a", "b", "c", "d", "e"], dtype=any_string_dtype)
|
|||
|
|
result = ser.str.normalize(form)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_normalize_bad_arg_raises(any_string_dtype):
|
|||
|
|
ser = Series(
|
|||
|
|
["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"],
|
|||
|
|
index=["a", "b", "c", "d", "e"],
|
|||
|
|
dtype=any_string_dtype,
|
|||
|
|
)
|
|||
|
|
with pytest.raises(ValueError, match="invalid normalization form"):
|
|||
|
|
ser.str.normalize("xxx")
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_normalize_index():
|
|||
|
|
idx = Index(["ＡＢＣ", "１２３", "ｱｲｴ"])
|
|||
|
|
expected = Index(["ABC", "123", "アイエ"])
|
|||
|
|
result = idx.str.normalize("NFKC")
|
|||
|
|
tm.assert_index_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"values,inferred_type",
|
|||
|
|
[
|
|||
|
|
(["a", "b"], "string"),
|
|||
|
|
(["a", "b", 1], "mixed-integer"),
|
|||
|
|
(["a", "b", 1.3], "mixed"),
|
|||
|
|
(["a", "b", 1.3, 1], "mixed-integer"),
|
|||
|
|
(["aa", datetime(2011, 1, 1)], "mixed"),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_index_str_accessor_visibility(values, inferred_type, index_or_series):
|
|||
|
|
from pandas.core.strings import StringMethods
|
|||
|
|
|
|||
|
|
obj = index_or_series(values)
|
|||
|
|
if index_or_series is Index:
|
|||
|
|
assert obj.inferred_type == inferred_type
|
|||
|
|
|
|||
|
|
assert isinstance(obj.str, StringMethods)
|
|||
|
|
|
|||
|
|
|
|||
|
|
@pytest.mark.parametrize(
|
|||
|
|
"values,inferred_type",
|
|||
|
|
[
|
|||
|
|
([1, np.nan], "floating"),
|
|||
|
|
([datetime(2011, 1, 1)], "datetime64"),
|
|||
|
|
([timedelta(1)], "timedelta64"),
|
|||
|
|
],
|
|||
|
|
)
|
|||
|
|
def test_index_str_accessor_non_string_values_raises(
|
|||
|
|
values, inferred_type, index_or_series
|
|||
|
|
):
|
|||
|
|
obj = index_or_series(values)
|
|||
|
|
if index_or_series is Index:
|
|||
|
|
assert obj.inferred_type == inferred_type
|
|||
|
|
|
|||
|
|
msg = "Can only use .str accessor with string values"
|
|||
|
|
with pytest.raises(AttributeError, match=msg):
|
|||
|
|
obj.str
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_index_str_accessor_multiindex_raises():
|
|||
|
|
# MultiIndex has mixed dtype, but not allow to use accessor
|
|||
|
|
idx = MultiIndex.from_tuples([("a", "b"), ("a", "b")])
|
|||
|
|
assert idx.inferred_type == "mixed"
|
|||
|
|
|
|||
|
|
msg = "Can only use .str accessor with Index, not MultiIndex"
|
|||
|
|
with pytest.raises(AttributeError, match=msg):
|
|||
|
|
idx.str
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_str_accessor_no_new_attributes(any_string_dtype):
|
|||
|
|
# https://github.com/pandas-dev/pandas/issues/10673
|
|||
|
|
ser = Series(list("aabbcde"), dtype=any_string_dtype)
|
|||
|
|
with pytest.raises(AttributeError, match="You cannot add any new attribute"):
|
|||
|
|
ser.str.xlabel = "a"
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_cat_on_bytes_raises():
|
|||
|
|
lhs = Series(np.array(list("abc"), "S1").astype(object))
|
|||
|
|
rhs = Series(np.array(list("def"), "S1").astype(object))
|
|||
|
|
msg = "Cannot use .str.cat with values of inferred dtype 'bytes'"
|
|||
|
|
with pytest.raises(TypeError, match=msg):
|
|||
|
|
lhs.str.cat(rhs)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_str_accessor_in_apply_func():
|
|||
|
|
# https://github.com/pandas-dev/pandas/issues/38979
|
|||
|
|
df = DataFrame(zip("abc", "def"))
|
|||
|
|
expected = Series(["A/D", "B/E", "C/F"])
|
|||
|
|
result = df.apply(lambda f: "/".join(f.str.upper()), axis=1)
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_zfill():
|
|||
|
|
# https://github.com/pandas-dev/pandas/issues/20868
|
|||
|
|
value = Series(["-1", "1", "1000", 10, np.nan])
|
|||
|
|
expected = Series(["-01", "001", "1000", np.nan, np.nan])
|
|||
|
|
tm.assert_series_equal(value.str.zfill(3), expected)
|
|||
|
|
|
|||
|
|
value = Series(["-2", "+5"])
|
|||
|
|
expected = Series(["-0002", "+0005"])
|
|||
|
|
tm.assert_series_equal(value.str.zfill(5), expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_zfill_with_non_integer_argument():
|
|||
|
|
value = Series(["-2", "+5"])
|
|||
|
|
wid = "a"
|
|||
|
|
msg = f"width must be of integer type, not {type(wid).__name__}"
|
|||
|
|
with pytest.raises(TypeError, match=msg):
|
|||
|
|
value.str.zfill(wid)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_zfill_with_leading_sign():
|
|||
|
|
value = Series(["-cat", "-1", "+dog"])
|
|||
|
|
expected = Series(["-0cat", "-0001", "+0dog"])
|
|||
|
|
tm.assert_series_equal(value.str.zfill(5), expected)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def test_get_with_dict_label():
|
|||
|
|
# GH47911
|
|||
|
|
s = Series(
|
|||
|
|
[
|
|||
|
|
{"name": "Hello", "value": "World"},
|
|||
|
|
{"name": "Goodbye", "value": "Planet"},
|
|||
|
|
{"value": "Sea"},
|
|||
|
|
]
|
|||
|
|
)
|
|||
|
|
result = s.str.get("name")
|
|||
|
|
expected = Series(["Hello", "Goodbye", None])
|
|||
|
|
tm.assert_series_equal(result, expected)
|
|||
|
|
result = s.str.get("value")
|
|||
|
|
expected = Series(["World", "Planet", "Sea"])
|
|||
|
|
tm.assert_series_equal(result, expected)
|