xlsx

```python

import pandas as pd

# Read Excel

df = pd.read_excel('file.xlsx') # Default: first sheet

all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict

# Analyze

df.head() # Preview data

df.info() # Column info

df.describe() # Statistics

# Write Excel

df.to_excel('output.xlsx', index=False)

```

```python

from openpyxl import Workbook

from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook()

sheet = wb.active

# Add data

sheet['A1'] = 'Hello'

sheet['B1'] = 'World'

sheet.append(['Row', 'of', 'data'])

# Add formula - ALWAYS use formulas, not hardcoded values

sheet['B2'] = '=SUM(A1:A10)'

# Formatting

sheet['A1'].font = Font(bold=True, color='FF0000')

sheet['A1'].fill = PatternFill('solid', start_color='FFFF00')

sheet['A1'].alignment = Alignment(horizontal='center')

# Column width

sheet.column_dimensions['A'].width = 20

wb.save('output.xlsx')

```

```python

from openpyxl import load_workbook

wb = load_workbook('existing.xlsx')

sheet = wb.active

# Modify cells

sheet['A1'] = 'New Value'

sheet.insert_rows(2)

sheet.delete_cols(3)

# Add new sheet

new_sheet = wb.create_sheet('NewSheet')

new_sheet['A1'] = 'Data'

wb.save('modified.xlsx')

```

```python

# BAD - Hardcoding calculated values

total = df['Sales'].sum()

sheet['B10'] = total # Hardcodes 5000

# GOOD - Using Excel formulas

sheet['B10'] = '=SUM(B2:B9)'

sheet['C5'] = '=(C4-C2)/C2' # Growth rate

sheet['D20'] = '=AVERAGE(D2:D19)'

```

• Blue text: Hardcoded inputs
• Black text: ALL formulas
• Green text: Links from other worksheets
• Yellow background: Key assumptions

• Use data_only=True to read calculated values
• For large files: Use read_only=True or write_only=True
• Formulas are preserved but not evaluated by openpyxl