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. 数据分析、文件夹分析、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"
Analyze and summarize data from Excel, CSV, Word, and PDF files.
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小葱技能站7w4.net发现了升级插件。
User: "Analyze all Excel files in this folder"
Agent: 使用 DataAnalyzer 扫描并分析
User: "Compare these CSV files"
Agent: 读取并对比数据
User: "Generate a data report"
Agent: 生成分析报告
这个数据分析工具整体质量中等。优点是支持多种常见文件格式,可以扫描文件夹批量分析,操作简单,中英文都能用。但实际功能比较基础,只做了文件的读取和基本信息统计,并没有实现文档中提到的数据合并、图表生成、报告输出等高级功能。如果需要复杂的数据分析或可视化,可能会失望。建议开发者补充完整功能后再使用。