| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110 |
- """
- 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)
|
