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See :ref:`extending.extension-types` for more.
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"""
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+ # Explanations for the ExtensionArrays listed below:
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+ #
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+ # ArrowExtensionArray: Wraps an Apache Arrow array for high-performance data handling.
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+ # ArrowStringArray: A specific version for string data backed by Apache Arrow.
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+ # BooleanArray: Stores boolean data (True, False) but with the ability to hold missing values (NA).
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+ # Categorical: For data that belongs to a fixed, finite set of categories. Very memory efficient.
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+ # DatetimeArray: Handles timezone-aware or timezone-naive date and time data.
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+ # FloatingArray: For floating-point (decimal) numbers, with support for missing values.
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+ # IntegerArray: For integer (whole) numbers, with support for missing values.
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+ # IntervalArray: Stores data representing intervals or ranges (e.g., 1-5, 6-10).
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+ # NumpyExtensionArray: A wrapper around a standard NumPy array, for compatibility within the extension system.
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+ # PeriodArray: For data representing regular time periods (e.g., months, quarters, years).
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+ # SparseArray: Memory-efficient array for data that is mostly zero or NA.
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+ # StringArray: Dedicated array for handling string data, with support for missing values.
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+ # TimedeltaArray: For data representing durations or differences in time (e.g., 2 days, 5 hours).
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+
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from pandas .core .arrays import (
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ArrowExtensionArray ,
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ArrowStringArray ,
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