name: data-analyzer description: Data analysis tool for Excel, CSV, Word, PDF, TXT, Markdown files. Use when user needs to analyze, summarize, or compare data from multiple files. Supports folder scanning, data aggregation, statistics, report generation in Markdown/Excel/Word/PDF. Multi-language support. 資料分析、資料夾分析、Excel分析。 version: 1.0.9 license: MIT-0 metadata: {"openclaw": {"emoji": "📊", "requires": {"bins": ["python3"], "env": []}}} dependencies: "pip install pandas openpyxl python-docx pymupdf matplotlib"

Data Analyzer

Analyze and summarize data from Excel, CSV, Word, and PDF files.

Features

小蔥技能7w4.net有完整的技能分類。

• 📊 Multi-Format Input: Excel, CSV, Word, PDF, TXT, Markdown
• 📁 Folder Scan: Analyze entire folders
• 📈 Statistics: Sum, average, trends
• 🔄 Data Merge: Combine multiple files
• 📉 Visualization: Generate charts
• 📋 Multi-Format Output: Markdown, Excel, Word, PDF
• 🌍 Multi-Language: English, Chinese output

Trigger Conditions

• "Analyze this folder" / "分析這個資料夾"
• "Compare these Excel files" / "對比這些Excel"
• "Summarize the data" / "彙總資料"
• "data-analyzer"

Python Code

import os
import pandas as pd
from pathlib import Path
from docx import Document
import fitz  # PyMuPDF

class DataAnalyzer:
    def __init__(self, folder_path):
        self.folder = Path(folder_path)
        self.files = self._scan_files()

    def _scan_files(self):
        """Scan folder for supported files"""
        files = {
            'excel': [], 'csv': [], 'word': [],
            'pdf': [], 'txt': [], 'markdown': []
        }

        for f in self.folder.rglob('*'):
            ext = f.suffix.lower()
            if ext in ['.xlsx', '.xls']:
                files['excel'].append(str(f))
            elif ext == '.csv':
                files['csv'].append(str(f))
            elif ext == '.docx':
                files['word'].append(str(f))
            elif ext == '.pdf':
                files['pdf'].append(str(f))
            elif ext == '.txt':
                files['txt'].append(str(f))
            elif ext in ['.md', '.markdown']:
                files['markdown'].append(str(f))

        return files

    def analyze_excel(self, file_path):
        """Analyze Excel file"""
        df = pd.read_excel(file_path)
        return {'rows': len(df), 'columns': len(df.columns), 'data': df}

    def analyze_csv(self, file_path):
        """Analyze CSV file"""
        df = pd.read_csv(file_path)
        return {'rows': len(df), 'columns': len(df.columns), 'data': df}

    def analyze_word(self, file_path):
        """Analyze Word file"""
        doc = Document(file_path)
        text = '\n'.join([p.text for p in doc.paragraphs if p.text.strip()])
        return {'paragraphs': len(doc.paragraphs), 'text': text}

    def analyze_pdf(self, file_path):
        """Analyze PDF file"""
        doc = fitz.open(file_path)
        text = ''
        for page in doc:
            text += page.get_text()
        result = {'pages': len(doc), 'text': text}
        doc.close()
        return result

    def analyze_txt(self, file_path):
        """Analyze TXT file"""
        with open(file_path, 'r', encoding='utf-8') as f:
            text = f.read()
        return {'lines': len(text.split('\n')), 'text': text}

    def analyze_markdown(self, file_path):
        """Analyze Markdown file"""
        with open(file_path, 'r', encoding='utf-8') as f:
            text = f.read()
        return {'lines': len(text.split('\n')), 'text': text}

    def analyze_file(self, file_path):
        """Auto-detect and analyze any supported file"""
        ext = Path(file_path).suffix.lower()

        if ext in ['.xlsx', '.xls']:
            return self.analyze_excel(file_path)
        elif ext == '.csv':
            return self.analyze_csv(file_path)
        elif ext == '.docx':
            return self.analyze_word(file_path)
        elif ext == '.pdf':
            return self.analyze_pdf(file_path)
        elif ext == '.txt':
            return self.analyze_txt(file_path)
        elif ext in ['.md', '.markdown']:
            return self.analyze_markdown(file_path)
        else:
            return {'error': f'Unsupported format: {ext}'}

    def generate_summary(self):
        """Generate analysis summary"""
        summary = {'total_files': 0, 'file_details': []}

        for ftype, flist in self.files.items():
            for fpath in flist:
                try:
                    analysis = self.analyze_file(fpath)
                    summary['file_details'].append({
                        'name': os.path.basename(fpath),
                        'type': ftype,
                        'analysis': analysis
                    })
                    summary['total_files'] += 1
                except Exception as e:
                    summary['file_details'].append({
                        'name': os.path.basename(fpath),
                        'type': ftype,
                        'error': str(e)
                    })

        return summary

Usage

User: "Analyze all Excel files in this folder"
Agent: 使用 DataAnalyzer 掃描並分析

User: "Compare these CSV files"
Agent: 讀取並對比資料

User: "Generate a data report"
Agent: 生成分析報告

Notes

• Supports .xlsx, .csv, .docx, .pdf
• Local processing, no data uploaded
• Cross-platform compatible

這個資料分析工具整體質量中等。優點是支援多種常見檔案格式，可以掃描資料夾批次分析，操作簡單，中英文都能用。但實際功能比較基礎，只做了檔案的讀取和基本資訊統計，並沒有實現文件中提到的資料合併、圖表生成、報告輸出等高階功能。如果需要複雜的資料分析或視覺化，可能會失望。建議開發者補充完整功能後再使用。