added golden USCensusPEP_PopulationEstimatebyRace

[niveditasing]

This PR includes:

1. Safe Coordinate-Based DataFrame Access (iloc Refactoring)
   To eliminate risk of unexpected behavior, performance side-effects, and standard Pandas warnings (such as SettingWithCopyWarning):
   • Replaced chained indexing: Converted chained lookups like df.iloc[j]["Area"] = ... to standard, safe coordinate-based syntax:
     df.iloc[j, 0] = ....
   • Added explicit casting: Wrapped coordinates inside explicit str(...) casting to guarantee concatenation safety regardless of the
     column's underlying data type.

---

2. Pandas Deprecation Upgrades
   • Modernized deprecated parameters under pd.read_table(...).
   • Replaced the deprecated delim_whitespace=True with explicit standard separator regex: sep=r'\s+', ensuring perfect compatibility with
     recent and future Pandas versions.

---

3. Have updated the goldens with a 0.2% increase in the threshold to address the non-permanent deletions caused by the unavailability of source URLs.

Testing results: https://storage.mtls.cloud.google.com/datcom-import-test/scripts/us_census/pep/population_estimate_by_race/USCensusPEP_PopulationEstimatebyRace/2026_07_17T00_22_16_589130_07_00/input0/validation/validation_output.csv

PR checklist : https://docs.google.com/spreadsheets/d/1BzweR9Sj58j0H2_BweGTmfE4Z1lrjPZL8u1FS0kzCeg/edit?pli=1&gid=0#gid=0

[gemini-code-assist]

Code Review

This pull request adds several golden data CSV files and introduces a validation configuration file (validation_config.json) along with its reference in the manifest to enable automated validation checks for the US Census PEP population estimate by race import. Feedback on the changes highlights a critical filename mismatch in the validation configuration that would cause a file-not-found error, as well as recommendations to ensure all validation rules have unique rule_id values for clearer reporting.

[gemini-code-assist]

The refactoring of iloc indexing and the fix for the length evaluation bug are important improvements for data integrity and performance. Using sorted(os.listdir()) is a good practice for ensuring deterministic behavior across different filesystems. The transition to requests.Session with urllib3 retries will significantly improve the robustness of the data ingestion process. One suggestion: verify that the validation_config.json thresholds are sufficiently strict to catch regressions in the golden files, as the 0.1% threshold should be evaluated against the expected variance of the Census data.

[niveditasing]

@gemini-code-assist review

[gemini-code-assist]

Code Review

This pull request introduces validation configurations and golden summary reports for US Census PEP population estimates by race. It updates preprocess.py to use a robust requests.Session with retry logic, fixes a bug in a string length check, sorts input files, and updates pandas operations to avoid deprecation warnings. Feedback is provided to extend the retry adapter configuration to cover both HTTP and HTTPS protocols.