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ronnycoding
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consolidate-statements

Consolidate CSV and Excel transaction files into a standardized CSV.

12|3|Updated Oct 26, 2025
Search Tags:#financial data#Excel#deduplication#data cleaning#reconciliation#CSV#consolidate
One-click install
npx skills add https://github.com/ronnycoding/my-personal-assistant --skill consolidate-statements
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: consolidate-statements
Source: https://github.com/ronnycoding/my-personal-assistant/tree/main/.claude/skills/finance-process/consolidate-statements
Command: npx skills add https://github.com/ronnycoding/my-personal-assistant --skill consolidate-statements

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl, python-dateutil, numpy, and includes scripts (resource) components.

What problem does it solve?

This Skill consolidates transaction data from multiple files: CSV and Excel, standardizing formats, removing duplicates, and producing a clean, consolidated dataset for easy analysis and reconciliation.

Core Features & Use Cases

  • Multi-file processing: Ingests CSV and Excel files from multiple sources and consolidates them into one dataset.
  • Duplicate detection: Removes exact and fuzzy duplicates to ensure clean data.
  • Column standardization: Maps different column names to a unified schema (date, description, amount, balance, category, account).
  • Date sorting & reconciliation: Sorts by date and validates balances when available.
  • Summary statistics: Generates metrics on loaded files, duplicates removed, and total rows.

Quick Start

Run a consolidation across your statements to create a single CSV: /finance-process consolidate --input="~/Documents/Finance/checking-*.csv" --output="~/Documents/Finance/combined-2024.csv"

Frequently Asked Questions about consolidate-statements

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I consolidate transaction data from multiple CSV and Excel files?▼

Consolidate multiple transaction files by ingesting CSV and Excel sources, standardizing column names to a unified schema, removing duplicates, sorting by date, and outputting a single cleaned CSV file with reconciliation metrics.

Can I remove duplicate transactions when combining bank statements?▼

Yes, the consolidation process detects and removes both exact duplicates and fuzzy duplicates with configurable tolerance, ensuring each transaction appears only once in your combined dataset.

What column standardization happens during financial data consolidation?▼

Different source files are automatically mapped to standard fields: date, description, amount, balance, category, account, and source_file, enabling consistent analysis across diverse bank and transaction exports.

How do I handle transaction files with inconsistent date formats?▼

The consolidation process uses python-dateutil to parse varied date formats from different sources, then outputs all transactions sorted chronologically in a standardized format.

Does this work with data from multiple banks or financial institutions?▼

Yes, it's designed for financial datasets from diverse sources; multi-file ingestion via glob patterns accepts CSV and Excel exports from any bank or institution with automatic column mapping and deduplication.

What validation and reconciliation checks are performed on consolidated data?▼

The process validates data types, reconciles balances when available, generates summary statistics including file count and duplicate removal metrics, and ensures data integrity across all consolidated transactions.

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