Improve pandas history ergonomics: self-describing KeyErrors, DataFrame.get(symbol), lazy DataFrame on typed history

[jhonabreul]

Description

Improves history/pandas ergonomics in Python, targeting the most common interop failure modes:

• Self-describing PandasMapper KeyErrors. The old error was opaque:

  KeyError: "No key found for either mapped or original key. Mapped Key: []; Original Key: []"
  

  The error now names the requested keys, lists the frame's columns and index levels, and adds a targeted hint for the three recurring mistakes: an index level requested as a column (→ get_level_values/reset_index), a symbol that lives in the index (→ df.loc/df.xs), and a symbol with no data (→ df.get(key)). Any failure while building the description falls back to the legacy message.

• DataFrame.get(symbol) now returns the symbol's sub-frame, or None when the symbol has no data, instead of raising. Column lookups keep pandas semantics.

• Typed history results expose .data_frame. The typed History<T> overloads now return DataHistory<T> instead of a plain IEnumerable, so self.history[TradeBar](symbol, 10).data_frame works. DataHistory<T> still implements IEnumerable<T>, the conversion is lazy, and this mirrors the existing OptionHistory/FutureHistory pattern.

Deferred: opt-in wide/unstacked frame shapes (breaking default change, needs its own design), and pandas-only attribute hints on typed results (needs an interop-layer extension point).

Related Issue

N/A

Motivation and Context

MultiIndex/typed-result confusion is a dominant Python crash class. Each opaque KeyError costs a full backtest iteration to decode. These changes make the errors self-explanatory and add safe accessors, without changing any default frame shape.

Requires Documentation Change

The typed history return type (DataHistory<T>) and history.get(symbol)/.data_frame accessors could be mentioned in the history docs.

How Has This Been Tested?

• New PandasIndexingTests cases: each KeyError variant (missing column, index-level key, symbol in index, missing symbol) asserts the new message; DataFrame.get tested for symbol, missing symbol, and column keys. All red before the fix.
• New AlgorithmHistoryTests.TypedHistoryResultsExposeADataFrame (C# and Python): typed results expose the expected frame and remain enumerable.
• Full AlgorithmHistoryTests, PandasConverterTests, PandasIndexingTests, PythonUtilTests fixtures pass.
• History regression backtests (C# + Python) pass unchanged.

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• Refactor (non-breaking change which improves implementation)
• Performance (non-breaking change which improves performance. Please add associated performance test and results)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Non-functional change (xml comments/documentation/etc)

Checklist:

• My code follows the code style of this project.
• I have read the CONTRIBUTING document.
• I have added tests to cover my changes.
• All new and existing tests passed.
• My branch follows the naming convention bug-<issue#>-<description> or feature-<issue#>-<description>