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jk-data-table

Data & analytics

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Updated 10-16 02:32

About this skill

Jinkō Data Table SDK Workflows

Use this skill for data-table mechanics through the SDK. Data tables can support trial overlays and calibration objectives; the row schema is the same, and fitness-function compatibility is reported by metadata when available.

Scope

  • Use client.create_data_table_from_csv() for CSV files or bytes.
  • Use client.create_data_table_from_sqlite() for SQLite files or bytes.
  • Use client.create_data_table_from_dataframe() for pandas DataFrames.
  • Inspect existing data tables with get_data_table(), content(), summary(), validate(), and export().
  • Check metadata.public.validForFitnessFunction after creation or inspection when available if the data table needs to be attached through trial/calibration dataTableDesigns.
  • For trial workflows that attach data tables through jk-trial, use a data table with validForFitnessFunction: True; point-value overlay tables may upload successfully but fail trial launch sanity.

Project Folder Hygiene

  • Prefer creating data tables inside a dedicated Jinkō folder instead of the project root. At the start of a workflow, ask for or propose a folder name, for example YYYY-MM-DD-<experiment-name>.
  • Reuse an existing exact-match folder when possible: client.folders.get_by_name(name, exact_match_only=True).
  • If the folder does not exist, create it only after user confirmation or when a script is run with --apply.
  • Resolve one folder object or folder id, then pass folder=folder to SDK creation calls that support it.

Row Schema

Read assets/data-table.json before changing CSV structure.

Supported row shapes:

  • Point-value row: obsId, time, value, plus optional unit, armScope, ranges, weight, and reference.
  • Range row: obsId, time, narrowRangeLowBound, narrowRangeHighBound, plus optional unit, armScope, wide ranges, weight, and reference.

Use ISO-8601 duration strings for time, for example PT0S, PT6H, or P1D.

Bundled Assets

  • assets/toy_data_table_values.csv: point-value observations for trial overlays.
  • assets/toy_data_table_ranges.csv: range observations suitable for calibration objective workflows.
  • assets/data-table.json: schema subset for supported data-table rows.

Bundled Scripts

  • scripts/create_data_table.py: dry-run-validates a source file and creates a data table with --apply.
  • scripts/inspect_data_table.py: inspects existing data tables, summaries, validation results, and fitness-function metadata.

Examples:

python skills/jk-data-table/scripts/create_data_table.py --source skills/jk-data-table/assets/toy_data_table_ranges.csv --method csv
python skills/jk-data-table/scripts/create_data_table.py --source skills/jk-data-table/assets/toy_data_table_ranges.csv --method csv --apply
python skills/jk-data-table/scripts/create_data_table.py --source skills/jk-data-table/assets/toy_data_table_ranges.csv --method csv --folder 2026-06-15-fit-data --create-folder --apply
python skills/jk-data-table/scripts/create_data_table.py --source skills/jk-data-table/assets/toy_data_table_values.csv --method dataframe --apply
python skills/jk-data-table/scripts/inspect_data_table.py --data-table-sid dt-... --fitness --validate

Reference Routing

  • Read references/data-table-schema.md for row shape and fitness-function notes.
  • Read assets/data-table.json when checking required columns.