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CPT data cleaning workflow

A reproducible starter path for importing, checking, and plotting cone penetration test data.

Author
Stratum Commons EditorVerified
Visibility
public
Published
May 16, 2026
Revision
Revision 1

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Why it matters

Cone penetration test data often arrives with inconsistent headers, unit drift, and depth gaps that make early interpretation harder than it should be.

Workflow

  1. Import the raw CPT export without altering column names.
  2. Validate units, depth ordering, and null runs before plotting.
  3. Record assumptions beside the cleaned dataset so downstream readers can reproduce the choices.

Output expectations

  • A cleaned tabular dataset with preserved provenance.
  • A first-pass qc plot for tip resistance, sleeve friction, and pore pressure.
  • Notes that explain where automated cleaning stopped and engineering judgement began.

Limitations

This seeded notebook is a starter read path, not a substitute for project-specific review, calibration, or site interpretation.

Executable runtimeNotebookbrowser0.29.4

Interactive execution shell

This Phase 2 slice runs a reviewed, browser-safe Python contract entirely in the client and reuses the published executable manifest as the runtime description.

Runtime contract

Manifest inputs

Seeded browser runtime ready.

Run completecpt_cleaning_workflow.py

Run summary

Clipped qc values at 9.0 MPa and rendered a first-pass profile.

Cleaned rows
3
Mean qc
8.33MPa
depth_mqc_mpa
17.8
28.2
39

Chart preview

Tip resistance profile

X: Depth (m)Y: qc (MPa)

Stdout

Loaded 3 CPT files
Validated units
Rendered qc plot