Tags: alexhallam/tv
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Release v0.3.1: Enhanced Polars Data Type Mapping Patch release enhancing the Polars data type mapping functionality. Enhancements: - Comprehensive DataFrame examples demonstrating all Polars data types - 12 detailed examples covering basic, complex, and nested types - Visual verification of abbreviated data types in table output - Enhanced demo with both full and abbreviated type displays - Improved documentation and testing coverage New Examples: - Basic types (String, Int32, Float64, Boolean, Date) - Date/time types (Date, Datetime<ns>, Time, Datetime<ns, UTC>) - List types (List<Float64>, List<String>, List<Int64>) - Array types (Array<Float64, 3>, Array<Int64, 3>) - Struct types with complex field definitions - Nullable types (Int64?, Float64?, Boolean?) - Decimal types (Decimal(10, 2), Decimal(38, 9)) - Duration types (Duration<ns>) - Categorical and Enum types - Nested complex types (List<List<Int64>>, List<Struct<...>>) All data types now properly display abbreviated forms in table output.
fix: NA values now properly colored in formatted output - Updated NA detection logic to use is_na_string_padded() instead of is_na() for formatted strings - Fixed NA value coloring in both CLI and Python bindings - NA values now properly use the selected color palette across all interfaces - Bumped version to 1.8.93
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