test_repr.py 1.1 KB

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  1. import numpy as np
  2. import pytest
  3. import pandas as pd
  4. from pandas.core.arrays.floating import (
  5. Float32Dtype,
  6. Float64Dtype,
  7. )
  8. def test_dtypes(dtype):
  9. # smoke tests on auto dtype construction
  10. np.dtype(dtype.type).kind == "f"
  11. assert dtype.name is not None
  12. @pytest.mark.parametrize(
  13. "dtype, expected",
  14. [(Float32Dtype(), "Float32Dtype()"), (Float64Dtype(), "Float64Dtype()")],
  15. )
  16. def test_repr_dtype(dtype, expected):
  17. assert repr(dtype) == expected
  18. def test_repr_array():
  19. result = repr(pd.array([1.0, None, 3.0]))
  20. expected = "<FloatingArray>\n[1.0, <NA>, 3.0]\nLength: 3, dtype: Float64"
  21. assert result == expected
  22. def test_repr_array_long():
  23. data = pd.array([1.0, 2.0, None] * 1000)
  24. expected = """<FloatingArray>
  25. [ 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0,
  26. ...
  27. <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>, 1.0, 2.0, <NA>]
  28. Length: 3000, dtype: Float64"""
  29. result = repr(data)
  30. assert result == expected
  31. def test_frame_repr(data_missing):
  32. df = pd.DataFrame({"A": data_missing})
  33. result = repr(df)
  34. expected = " A\n0 <NA>\n1 0.1"
  35. assert result == expected