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# XLSX Toolkit
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization.
## Prerequisites
- Python 3.8+
- Libraries: openpyxl, pandas
- Optional: LibreOffice (for formula recalculation)
## Instructions
1. **Read and analyze Excel data with pandas**
```python
import pandas as pd
df = pd.read_excel('file.xlsx')
all_sheets = pd.read_excel('file.xlsx', sheet_name=None)
df.describe() # Statistics
```
2. **Create new Excel files with openpyxl**
```python
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill
wb = Workbook()
sheet = wb.active
sheet['A1'] = 'Hello'
sheet['B2'] = '=SUM(A1:A10)' # Use formulas, not hardcoded values
sheet['A1'].font = Font(bold=True)
wb.save('output.xlsx')
```
3. **Edit existing files preserving formulas**
```python
from openpyxl import load_workbook
wb = load_workbook('existing.xlsx')
sheet = wb.active
sheet['A1'] = 'New Value'
wb.save('modified.xlsx')
```
4. **Always use Excel formulas instead of hardcoding**
```python
# WRONG: sheet['B10'] = total
# CORRECT:
sheet['B10'] = '=SUM(B2:B9)'
sheet['C5'] = '=(C4-C2)/C2'
sheet['D20'] = '=AVERAGE(D2:D19)'
```
5. **Financial model color standards**
- Blue text: Hardcoded inputs
- Black text: All formulas
- Green text: Links from other sheets
- Yellow background: Key assumptions
6. **Number formatting**
- Currency: $#,##0 with units in headers
- Percentages: 0.0% format
- Negative numbers: Use parentheses (123) not -123
## Error Handling
- If formulas show errors (#REF!, #DIV/0!), verify cell references
- Use `data_only=True` to read calculated values (but formulas are lost)
- For large files, use `read_only=True` or `write_only=True`
## Notes
- Use pandas for data analysis and bulk operations
- Use openpyxl for formulas, formatting, and Excel-specific features
- Cell indices are 1-based in openpyxl
- Recalculate formulas with LibreOffice if needed
Source: anthropics/skills