Export Experiment Data to Excel

Overview

export_experiment_data_to_excel transforms heterogeneous experimental data — JSON from video analysis pipelines, pandas DataFrames, time-series arrays, nested protocol outputs — into clean, human-readable Excel workbooks. The skill auto-assigns logical sheet names (e.g., Raw Data, Growth Curves, Cell Counts, Population Metrics), prepends unit and metadata annotation rows, applies consistent column widths and header styling, and emits a single .xlsx file ready for lab notebooks, ELN attachment, regulatory submission, or downstream statistical analysis. It bridges the gap between machine-generated structured data and the Excel-centric workflows that many wet-lab researchers and collaborators expect.

When to Use This Skill

Use this skill when any of the following conditions are present:

LabOS pipeline export: Output from extract_experiment_data_from_video, analyze_lab_video_cell_behavior, or generate_cell_analysis_charts is in JSON or tabular form and must be shared as an Excel file for collaborators or PI review.
Multi-sheet report assembly: Several related datasets (raw counts, summary metrics, time-series curves, per-well results) must be organized into one workbook with clearly named sheets rather than scattered CSV files.
Unit and provenance documentation: Data columns require explicit unit headers (µL, h⁻¹, µm/h, %) and annotation rows (experiment ID, date, protocol version) so recipients understand the data without reading separate metadata files.
ELN or Benchling attachment: A Benchling ELN entry or protocols.io experiment record requires an Excel file as an attached data object; the skill produces a formatted file suitable for direct upload.
Regulatory or audit trail: GLP/GMP or audit documentation requires data in a fixed, non-editable (or track-changes) format; Excel with frozen headers and annotation rows meets many lab compliance requirements.
Collaborator handoff: A non-computational collaborator or external lab needs data in Excel for manual inspection, plotting in Excel/GraphPad, or import into proprietary analysis software.
Statistical analysis prep: Data will be imported into R, SPSS, GraphPad Prism, or pandas; the skill ensures column names are valid, units are explicit, and missing values are consistently encoded (e.g., NA, empty, or —).
Batch experiment export: Multiple experiments or conditions are consolidated into one workbook with one sheet per condition, or one sheet per time point, for side-by-side comparison.