When a new value is inserted into a frame, we call pandas.api.types.pandas_dtype(value) to extract the dtype of an object like a pandas Series or numpy array. After #7261, when a scalar value is passed, this usually raises a TypeError, so we construct a local pandas Series from the object and extract the dtype from there.
When the passed value is a date-like string, pandas will instead raise a ValueError because it tries to parse it as a numpy structured dtype. After this fix, we now catch ValueError in addition to TypeError to handle this case.
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What do these changes do?
When a new value is inserted into a frame, we call
pandas.api.types.pandas_dtype(value)to extract the dtype of an object like a pandas Series or numpy array. After #7261, when a scalar value is passed, this usually raises a TypeError, so we construct a local pandas Series from the object and extract the dtype from there.When the passed value is a date-like string, pandas will instead raise a ValueError because it tries to parse it as a numpy structured dtype. After this fix, we now catch ValueError in addition to TypeError to handle this case.
flake8 modin/ asv_bench/benchmarks scripts/doc_checker.pyblack --check modin/ asv_bench/benchmarks scripts/doc_checker.pygit commit -sdocs/development/architecture.rstis up-to-date