Skip to content

README.md

Latest commit

 

History

History
84 lines (53 loc) · 2.06 KB

README.md

File metadata and controls

84 lines (53 loc) · 2.06 KB

CSV → Excel Report Builder (with Summary + Charts)

This script converts labeled transaction data from CSV into a multi-sheet Excel report with summaries and charts.

It builds on PyFi’s new AI for Finance demo, extending it into a full reporting pipeline that exports a polished Excel workbook with embedded visualizations and summary statistics.

Click here to learn more about PyFi's Python <> OpenAI integration, and register for the next live demo

Background

PyFi’s AI for Finance demo executes logic technically impossible in Excel, injects intelligence into the workflow via the OpenAI API, and automates a multi-hour financial analysis, in just a few seconds.

This project takes the output of that demo and produces a stakeholder-ready Excel report:

  • Raw labeled data
  • Human-readable summaries
  • Embedded chart images
  • Native Excel charts built directly from the data

This makes it suitable for finance, ops, or audit-style reporting workflows.

What it generates

Output workbook (example: labeled_data.xlsx) includes:

1) labeled_data

Full import of labeled_data.csv produced by the PyFi demo pipeline.

2) Summary

If these files exist, they are added as formatted sections:

  • summary.csv
    • expected column: Summary
  • summary_stats.csv
    • expected columns: Metric, Value

3) Charts

Embeds pre-rendered PNG charts:

  • spending_by_spender.png
  • spending_by_category.png
  • spending_by_vendor.png

Charts are scaled and positioned side-by-side with titles.

4) Native Charts

Creates Excel-native charts from aggregated data:

  • Pie — Spending by Spender
  • Pie — Spending by Category
  • Bar (top 15) — Spending by Vendor

All charts are generated directly inside Excel using openpyxl.

Input expectations

Required

  • labeled_data.csv (from PyFi demo output)

Expected columns:

  • amount
  • spender
  • category
  • vendor

Optional

  • summary.csv
  • summary_stats.csv
  • PNG chart files listed above

Installation

pip install pandas openpyxl