Remove duplicate pd.StringDtype handling in _process_pandas_column

[Copilot]

The _process_pandas_column function contained two elif isinstance(dt, pd.StringDtype): blocks - one at lines 1063-1081 and another at 1102-1149.

Changes

• Removed first duplicate block (lines 1063-1081)
• Simplified remaining block to use _process_ndarray consistently for both missing and non-missing value cases
• Corrected variable usage (is_predict → not is_initial to match function signature)

The consolidated implementation handles StringDtype conversion to numpy strings with proper NA handling via .dropna() and .notna() when missing values are present.

Net impact: -48 lines, single code path for StringDtype processing

---

💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more Copilot coding agent tips in the docs.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 72.77%. Comparing base (766b663) to head (cf10959).

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #647      +/-   ##
==========================================
+ Coverage   72.76%   72.77%   +0.01%     
==========================================
  Files          75       75              
  Lines       10447    10451       +4     
==========================================
+ Hits         7602     7606       +4     
  Misses       2845     2845              

Flag	Coverage Δ
bdist_linux_310_python	72.46% <100.00%> (+0.07%)	⬆️
bdist_linux_311_python	72.41% <100.00%> (-0.06%)	⬇️
bdist_linux_312_python	72.48% <100.00%> (+0.12%)	⬆️
bdist_linux_313_python	72.41% <100.00%> (+0.02%)	⬆️
bdist_mac_310_python	72.60% <100.00%> (+0.04%)	⬆️
bdist_mac_311_python	72.65% <100.00%> (+0.10%)	⬆️
bdist_mac_312_python	72.65% <100.00%> (+0.09%)	⬆️
bdist_mac_313_python	72.63% <100.00%> (+0.02%)	⬆️
bdist_win_310_python	72.67% <100.00%> (+0.01%)	⬆️
bdist_win_311_python	72.69% <100.00%> (+0.02%)	⬆️
bdist_win_312_python	72.67% <100.00%> (+0.09%)	⬆️
bdist_win_313_python	72.60% <100.00%> (+0.01%)	⬆️
sdist_linux_310_python	72.44% <100.00%> (+0.09%)	⬆️
sdist_linux_311_python	72.42% <100.00%> (+0.09%)	⬆️
sdist_linux_312_python	72.32% <100.00%> (+<0.01%)	⬆️
sdist_linux_313_python	72.42% <100.00%> (+0.01%)	⬆️
sdist_mac_310_python	72.53% <100.00%> (-0.03%)	⬇️
sdist_mac_311_python	72.55% <100.00%> (+0.17%)	⬆️
sdist_mac_312_python	72.55% <100.00%> (-0.01%)	⬇️
sdist_mac_313_python	72.55% <100.00%> (+0.01%)	⬆️
sdist_win_310_python	72.67% <100.00%> (+0.09%)	⬆️
sdist_win_311_python	72.60% <100.00%> (+0.06%)	⬆️
sdist_win_312_python	72.67% <100.00%> (+0.07%)	⬆️
sdist_win_313_python	72.67% <100.00%> (+0.09%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

[paulbkoch]

@copilot, please re-implement with the latest changes. I think the changes to handle pd.CategoricalDtype should help

[Copilot]

@copilot, please re-implement with the latest changes. I think the changes to handle pd.CategoricalDtype should help

Re-implemented the pd.StringDtype handling in commit fdf23c3. The implementation follows the same pattern as object dtype and nullable integer/boolean types (Int64Dtype, BooleanDtype), using .hasnans, .dropna(), and .notna() for proper NA handling. The StringDtype values are converted to numpy string arrays and processed through _process_ndarray for categorical encoding.

Could you clarify if there are specific changes to the CategoricalDtype handling that I should incorporate? I don't see any recent commits beyond the grafted base that would indicate what changes you're referring to.