""" test_insert is specifically for the DataFrame.insert method; not to be confused with tests with "insert" in their names that are really testing __setitem__. """ import numpy as np import pytest from pandas.errors import PerformanceWarning from pandas import ( DataFrame, Index, ) import pandas._testing as tm class TestDataFrameInsert: def test_insert(self): df = DataFrame( np.random.randn(5, 3), index=np.arange(5), columns=["c", "b", "a"] ) df.insert(0, "foo", df["a"]) tm.assert_index_equal(df.columns, Index(["foo", "c", "b", "a"])) tm.assert_series_equal(df["a"], df["foo"], check_names=False) df.insert(2, "bar", df["c"]) tm.assert_index_equal(df.columns, Index(["foo", "c", "bar", "b", "a"])) tm.assert_almost_equal(df["c"], df["bar"], check_names=False) with pytest.raises(ValueError, match="already exists"): df.insert(1, "a", df["b"]) msg = "cannot insert c, already exists" with pytest.raises(ValueError, match=msg): df.insert(1, "c", df["b"]) df.columns.name = "some_name" # preserve columns name field df.insert(0, "baz", df["c"]) assert df.columns.name == "some_name" def test_insert_column_bug_4032(self): # GH#4032, inserting a column and renaming causing errors df = DataFrame({"b": [1.1, 2.2]}) df = df.rename(columns={}) df.insert(0, "a", [1, 2]) result = df.rename(columns={}) str(result) expected = DataFrame([[1, 1.1], [2, 2.2]], columns=["a", "b"]) tm.assert_frame_equal(result, expected) df.insert(0, "c", [1.3, 2.3]) result = df.rename(columns={}) str(result) expected = DataFrame([[1.3, 1, 1.1], [2.3, 2, 2.2]], columns=["c", "a", "b"]) tm.assert_frame_equal(result, expected) def test_insert_with_columns_dups(self): # GH#14291 df = DataFrame() df.insert(0, "A", ["g", "h", "i"], allow_duplicates=True) df.insert(0, "A", ["d", "e", "f"], allow_duplicates=True) df.insert(0, "A", ["a", "b", "c"], allow_duplicates=True) exp = DataFrame( [["a", "d", "g"], ["b", "e", "h"], ["c", "f", "i"]], columns=["A", "A", "A"] ) tm.assert_frame_equal(df, exp) def test_insert_item_cache(self, using_array_manager, using_copy_on_write): df = DataFrame(np.random.randn(4, 3)) ser = df[0] if using_array_manager: expected_warning = None else: # with BlockManager warn about high fragmentation of single dtype expected_warning = PerformanceWarning with tm.assert_produces_warning(expected_warning): for n in range(100): df[n + 3] = df[1] * n if using_copy_on_write: ser.iloc[0] = 99 assert df.iloc[0, 0] == df[0][0] assert df.iloc[0, 0] != 99 else: ser.values[0] = 99 assert df.iloc[0, 0] == df[0][0] assert df.iloc[0, 0] == 99 def test_insert_EA_no_warning(self): # PerformanceWarning about fragmented frame should not be raised when # using EAs (https://github.com/pandas-dev/pandas/issues/44098) df = DataFrame(np.random.randint(0, 100, size=(3, 100)), dtype="Int64") with tm.assert_produces_warning(None): df["a"] = np.array([1, 2, 3]) def test_insert_frame(self): # GH#42403 df = DataFrame({"col1": [1, 2], "col2": [3, 4]}) msg = r"Expected a 1D array, got an array with shape \(2, 2\)" with pytest.raises(ValueError, match=msg): df.insert(1, "newcol", df)