import numpy as np from pandas import Series, Timestamp, date_range import pandas._testing as tm from pandas.api.types import is_scalar class TestSeriesSearchSorted: def test_searchsorted(self): ser = Series([1, 2, 3]) result = ser.searchsorted(1, side="left") assert is_scalar(result) assert result == 0 result = ser.searchsorted(1, side="right") assert is_scalar(result) assert result == 1 def test_searchsorted_numeric_dtypes_scalar(self): ser = Series([1, 2, 90, 1000, 3e9]) res = ser.searchsorted(30) assert is_scalar(res) assert res == 2 res = ser.searchsorted([30]) exp = np.array([2], dtype=np.intp) tm.assert_numpy_array_equal(res, exp) def test_searchsorted_numeric_dtypes_vector(self): ser = Series([1, 2, 90, 1000, 3e9]) res = ser.searchsorted([91, 2e6]) exp = np.array([3, 4], dtype=np.intp) tm.assert_numpy_array_equal(res, exp) def test_searchsorted_datetime64_scalar(self): ser = Series(date_range("20120101", periods=10, freq="2D")) val = Timestamp("20120102") res = ser.searchsorted(val) assert is_scalar(res) assert res == 1 def test_searchsorted_datetime64_scalar_mixed_timezones(self): # GH 30086 ser = Series(date_range("20120101", periods=10, freq="2D", tz="UTC")) val = Timestamp("20120102", tz="America/New_York") res = ser.searchsorted(val) assert is_scalar(res) assert res == 1 def test_searchsorted_datetime64_list(self): ser = Series(date_range("20120101", periods=10, freq="2D")) vals = [Timestamp("20120102"), Timestamp("20120104")] res = ser.searchsorted(vals) exp = np.array([1, 2], dtype=np.intp) tm.assert_numpy_array_equal(res, exp) def test_searchsorted_sorter(self): # GH8490 ser = Series([3, 1, 2]) res = ser.searchsorted([0, 3], sorter=np.argsort(ser)) exp = np.array([0, 2], dtype=np.intp) tm.assert_numpy_array_equal(res, exp)