import numpy as np import pytest import pandas.util._test_decorators as td from pandas import ( CategoricalDtype, DataFrame, NaT, Series, Timestamp, ) import pandas._testing as tm class TestUpdate: def test_update(self, using_copy_on_write): s = Series([1.5, np.nan, 3.0, 4.0, np.nan]) s2 = Series([np.nan, 3.5, np.nan, 5.0]) s.update(s2) expected = Series([1.5, 3.5, 3.0, 5.0, np.nan]) tm.assert_series_equal(s, expected) # GH 3217 df = DataFrame([{"a": 1}, {"a": 3, "b": 2}]) df["c"] = np.nan df_orig = df.copy() df["c"].update(Series(["foo"], index=[0])) if using_copy_on_write: expected = df_orig else: expected = DataFrame( [[1, np.nan, "foo"], [3, 2.0, np.nan]], columns=["a", "b", "c"] ) tm.assert_frame_equal(df, expected) @pytest.mark.parametrize( "other, dtype, expected", [ # other is int ([61, 63], "int32", Series([10, 61, 12], dtype="int32")), ([61, 63], "int64", Series([10, 61, 12])), ([61, 63], float, Series([10.0, 61.0, 12.0])), ([61, 63], object, Series([10, 61, 12], dtype=object)), # other is float, but can be cast to int ([61.0, 63.0], "int32", Series([10, 61, 12], dtype="int32")), ([61.0, 63.0], "int64", Series([10, 61, 12])), ([61.0, 63.0], float, Series([10.0, 61.0, 12.0])), ([61.0, 63.0], object, Series([10, 61.0, 12], dtype=object)), # others is float, cannot be cast to int ([61.1, 63.1], "int32", Series([10.0, 61.1, 12.0])), ([61.1, 63.1], "int64", Series([10.0, 61.1, 12.0])), ([61.1, 63.1], float, Series([10.0, 61.1, 12.0])), ([61.1, 63.1], object, Series([10, 61.1, 12], dtype=object)), # other is object, cannot be cast ([(61,), (63,)], "int32", Series([10, (61,), 12])), ([(61,), (63,)], "int64", Series([10, (61,), 12])), ([(61,), (63,)], float, Series([10.0, (61,), 12.0])), ([(61,), (63,)], object, Series([10, (61,), 12])), ], ) def test_update_dtypes(self, other, dtype, expected): ser = Series([10, 11, 12], dtype=dtype) other = Series(other, index=[1, 3]) ser.update(other) tm.assert_series_equal(ser, expected) @pytest.mark.parametrize( "series, other, expected", [ # update by key ( Series({"a": 1, "b": 2, "c": 3, "d": 4}), {"b": 5, "c": np.nan}, Series({"a": 1, "b": 5, "c": 3, "d": 4}), ), # update by position (Series([1, 2, 3, 4]), [np.nan, 5, 1], Series([1, 5, 1, 4])), ], ) def test_update_from_non_series(self, series, other, expected): # GH 33215 series.update(other) tm.assert_series_equal(series, expected) @pytest.mark.parametrize( "data, other, expected, dtype", [ (["a", None], [None, "b"], ["a", "b"], "string[python]"), pytest.param( ["a", None], [None, "b"], ["a", "b"], "string[pyarrow]", marks=td.skip_if_no("pyarrow"), ), ([1, None], [None, 2], [1, 2], "Int64"), ([True, None], [None, False], [True, False], "boolean"), ( ["a", None], [None, "b"], ["a", "b"], CategoricalDtype(categories=["a", "b"]), ), ( [Timestamp(year=2020, month=1, day=1, tz="Europe/London"), NaT], [NaT, Timestamp(year=2020, month=1, day=1, tz="Europe/London")], [Timestamp(year=2020, month=1, day=1, tz="Europe/London")] * 2, "datetime64[ns, Europe/London]", ), ], ) def test_update_extension_array_series(self, data, other, expected, dtype): result = Series(data, dtype=dtype) other = Series(other, dtype=dtype) expected = Series(expected, dtype=dtype) result.update(other) tm.assert_series_equal(result, expected) def test_update_with_categorical_type(self): # GH 25744 dtype = CategoricalDtype(["a", "b", "c", "d"]) s1 = Series(["a", "b", "c"], index=[1, 2, 3], dtype=dtype) s2 = Series(["b", "a"], index=[1, 2], dtype=dtype) s1.update(s2) result = s1 expected = Series(["b", "a", "c"], index=[1, 2, 3], dtype=dtype) tm.assert_series_equal(result, expected)