Mining Drill data Analysis

I have a set of drilling-related mining datasets that need to be explored specifically for trend analysis aimed at pinpointing potential anomalies. Your job is to dive into the data, surface any irregular patterns or outliers, and explain what they might mean operationally.

What I will hand over:
• Raw drill-run datasets in their current format (CSV / Excel); if you prefer a different format, let me know and I can convert it before we start.

What I need back:
• A concise, reproducible script or notebook (Python, R or similar) that carries out the full trend analysis pipeline.
• Clear visualisations that highlight identified trends and the exact data points flagged as anomalies.
• A short report (PDF or Markdown) summarising your methodology, the key findings, and recommended next steps.

Acceptance criteria:
• Code runs end-to-end on my machine with only standard open-source libraries.
• All anomalies are referenced by row ID or timestamp so I can trace them back in the raw file.
• Explanations are written in plain language I can share with non-technical team members.

If you have experience with mining or industrial sensor data that’s a bonus, but strong skills in statistical trend detection and anomaly identification are the main requirement. Let me know your preferred tooling and a realistic timeframe, and we can get started right away.