Data Analyzer
Analyze and summarize data from Excel, CSV, Word, and PDF files.
Features
- 📊 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" / "分析这个文件夹"
- "Compare these Excel files" / "对比这些Excel"
- "Summarize the data" / "汇总数据"
- "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 summaryUsage
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Notes
- Supports.xlsx,.csv,.docx,.pdf
- Local processing, no data uploaded
- Cross-platform compatible