test_pop.py 2.2 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172
  1. import numpy as np
  2. from pandas import (
  3. DataFrame,
  4. MultiIndex,
  5. Series,
  6. )
  7. import pandas._testing as tm
  8. class TestDataFramePop:
  9. def test_pop(self, float_frame, warn_copy_on_write):
  10. float_frame.columns.name = "baz"
  11. float_frame.pop("A")
  12. assert "A" not in float_frame
  13. float_frame["foo"] = "bar"
  14. float_frame.pop("foo")
  15. assert "foo" not in float_frame
  16. assert float_frame.columns.name == "baz"
  17. # gh-10912: inplace ops cause caching issue
  18. a = DataFrame([[1, 2, 3], [4, 5, 6]], columns=["A", "B", "C"], index=["X", "Y"])
  19. b = a.pop("B")
  20. with tm.assert_cow_warning(warn_copy_on_write):
  21. b += 1
  22. # original frame
  23. expected = DataFrame([[1, 3], [4, 6]], columns=["A", "C"], index=["X", "Y"])
  24. tm.assert_frame_equal(a, expected)
  25. # result
  26. expected = Series([2, 5], index=["X", "Y"], name="B") + 1
  27. tm.assert_series_equal(b, expected)
  28. def test_pop_non_unique_cols(self):
  29. df = DataFrame({0: [0, 1], 1: [0, 1], 2: [4, 5]})
  30. df.columns = ["a", "b", "a"]
  31. res = df.pop("a")
  32. assert type(res) == DataFrame
  33. assert len(res) == 2
  34. assert len(df.columns) == 1
  35. assert "b" in df.columns
  36. assert "a" not in df.columns
  37. assert len(df.index) == 2
  38. def test_mixed_depth_pop(self):
  39. arrays = [
  40. ["a", "top", "top", "routine1", "routine1", "routine2"],
  41. ["", "OD", "OD", "result1", "result2", "result1"],
  42. ["", "wx", "wy", "", "", ""],
  43. ]
  44. tuples = sorted(zip(*arrays))
  45. index = MultiIndex.from_tuples(tuples)
  46. df = DataFrame(np.random.default_rng(2).standard_normal((4, 6)), columns=index)
  47. df1 = df.copy()
  48. df2 = df.copy()
  49. result = df1.pop("a")
  50. expected = df2.pop(("a", "", ""))
  51. tm.assert_series_equal(expected, result, check_names=False)
  52. tm.assert_frame_equal(df1, df2)
  53. assert result.name == "a"
  54. expected = df1["top"]
  55. df1 = df1.drop(["top"], axis=1)
  56. result = df2.pop("top")
  57. tm.assert_frame_equal(expected, result)
  58. tm.assert_frame_equal(df1, df2)