import numpy as np from pandas.core.dtypes.common import is_float_dtype from pandas import ( DataFrame, isna, ) import pandas._testing as tm class TestSetValue: def test_set_value(self, float_frame): for idx in float_frame.index: for col in float_frame.columns: float_frame._set_value(idx, col, 1) assert float_frame[col][idx] == 1 def test_set_value_resize(self, float_frame, using_infer_string): res = float_frame._set_value("foobar", "B", 0) assert res is None assert float_frame.index[-1] == "foobar" assert float_frame._get_value("foobar", "B") == 0 float_frame.loc["foobar", "qux"] = 0 assert float_frame._get_value("foobar", "qux") == 0 res = float_frame.copy() res._set_value("foobar", "baz", "sam") if using_infer_string: assert res["baz"].dtype == "string" else: assert res["baz"].dtype == np.object_ res = float_frame.copy() res._set_value("foobar", "baz", True) assert res["baz"].dtype == np.object_ res = float_frame.copy() res._set_value("foobar", "baz", 5) assert is_float_dtype(res["baz"]) assert isna(res["baz"].drop(["foobar"])).all() with tm.assert_produces_warning( FutureWarning, match="Setting an item of incompatible dtype" ): res._set_value("foobar", "baz", "sam") assert res.loc["foobar", "baz"] == "sam" def test_set_value_with_index_dtype_change(self): df_orig = DataFrame( np.random.default_rng(2).standard_normal((3, 3)), index=range(3), columns=list("ABC"), ) # this is actually ambiguous as the 2 is interpreted as a positional # so column is not created df = df_orig.copy() df._set_value("C", 2, 1.0) assert list(df.index) == list(df_orig.index) + ["C"] # assert list(df.columns) == list(df_orig.columns) + [2] df = df_orig.copy() df.loc["C", 2] = 1.0 assert list(df.index) == list(df_orig.index) + ["C"] # assert list(df.columns) == list(df_orig.columns) + [2] # create both new df = df_orig.copy() df._set_value("C", "D", 1.0) assert list(df.index) == list(df_orig.index) + ["C"] assert list(df.columns) == list(df_orig.columns) + ["D"] df = df_orig.copy() df.loc["C", "D"] = 1.0 assert list(df.index) == list(df_orig.index) + ["C"] assert list(df.columns) == list(df_orig.columns) + ["D"]