xlsx-manipulation（XLSX manipulation 图表绘制）

XLSX Manipulation Skill

Overview

This skill enables programmatic creation, editing, and manipulation of Microsoft Excel (.xlsx) spreadsheets using the openpyxl library. Create professional spreadsheets with formulas, formatting, charts, and data validation without manual editing.

How to Use

1. Describe the spreadsheet you want to create or modify
2. Provide data, formulas, or formatting requirements
3. I'll generate openpyxl code and execute it

Example prompts:

• "Create a budget spreadsheet with monthly tracking"
• "Add conditional formatting to highlight values above threshold"
• "Generate a pivot-table-like summary from this data"
• "Create a dashboard with charts and KPIs"

Domain Knowledge

openpyxl Fundamentals

from openpyxl import Workbook, load_workbook
from openpyxl.styles import Font, Fill, Border, Alignment
from openpyxl.chart import BarChart, Reference

# Create new workbook
wb = Workbook()
ws = wb.active

# Or open existing
wb = load_workbook('existing.xlsx')
ws = wb.active

Workbook Structure

Workbook
├── worksheets (sheets/tabs)
│   ├── cells (data storage)
│   ├── rows/columns (formatting)
│   ├── merged_cells
│   └── charts
├── defined_names (named ranges)
└── styles (formatting templates)

Working with Cells

Basic Cell Operations

# By cell reference
ws['A1'] = 'Header'
ws['B1'] = 42

# By row, column
ws.cell(row=1, column=3, value='Data')

# Multiple cells
ws['A1:C1'] = [['Col1', 'Col2', 'Col3']]

# Append rows
ws.append(['Row', 'Data', 'Here'])

Reading Cells

# Single cell
value = ws['A1'].value

# Cell range
for row in ws['A1:C3']:
    for cell in row:
        print(cell.value)

# Iterate rows
for row in ws.iter_rows(min_row=1, max_row=10, min_col=1, max_col=3):
    for cell in row:
        print(cell.value)

Formulas

# Basic formulas
ws['D1'] = '=SUM(A1:C1)'
ws['D2'] = '=AVERAGE(A2:C2)'
ws['E1'] = '=IF(D1>100,"High","Low")'

# Named ranges
from openpyxl.workbook.defined_name import DefinedName
ref = "Sheet!$A$1:$C$10"
defn = DefinedName("SalesData", attr_text=ref)
wb.defined_names.add(defn)

# Use named range
ws['F1'] = '=SUM(SalesData)'

Formatting

Cell Styles

from openpyxl.styles import Font, Fill, PatternFill, Border, Side, Alignment

# Font
ws['A1'].font = Font(
    name='Arial',
    size=14,
    bold=True,
    italic=False,
    color='FF0000'  # Red
)

# Fill (background)
ws['A1'].fill = PatternFill(
    start_color='FFFF00',  # Yellow
    end_color='FFFF00',
    fill_type='solid'
)

# Border
thin_border = Border(
    left=Side(style='thin'),
    right=Side(style='thin'),
    top=Side(style='thin'),
    bottom=Side(style='thin')
)
ws['A1'].border = thin_border

# Alignment
ws['A1'].alignment = Alignment(
    horizontal='center',
    vertical='center',
    wrap_text=True
)

Number Formats

# Currency
ws['B2'].number_format = '$#,##0.00'

# Percentage
ws['C2'].number_format = '0.00%'

# Date
ws['D2'].number_format = 'YYYY-MM-DD'

# Custom
ws['E2'].number_format = '#,##0.00 "units"'

Conditional Formatting

from openpyxl.formatting.rule import ColorScaleRule, CellIsRule, FormulaRule
from openpyxl.styles import PatternFill

# Color scale (heatmap)
color_scale = ColorScaleRule(
    start_type='min', start_color='FF0000',
    end_type='max', end_color='00FF00'
)
ws.conditional_formatting.add('A1:A10', color_scale)

# Cell value rule
red_fill = PatternFill(start_color='FFCCCC', end_color='FFCCCC', fill_type='solid')
rule = CellIsRule(operator='greaterThan', formula=['100'], fill=red_fill)
ws.conditional_formatting.add('B1:B10', rule)

Charts

from openpyxl.chart import BarChart, LineChart, PieChart, Reference

# Prepare data
data = Reference(ws, min_col=2, min_row=1, max_col=3, max_row=5)
categories = Reference(ws, min_col=1, min_row=2, max_row=5)

# Bar Chart
chart = BarChart()
chart.type = "col"  # or "bar" for horizontal
chart.title = "Sales by Region"
chart.add_data(data, titles_from_data=True)
chart.set_categories(categories)
chart.shape = 4
ws.add_chart(chart, "E1")

# Line Chart
line = LineChart()
line.title = "Trend Analysis"
line.add_data(data, titles_from_data=True)
line.set_categories(categories)
ws.add_chart(line, "E15")

# Pie Chart
pie = PieChart()
pie.add_data(data, titles_from_data=True)
pie.set_categories(categories)
ws.add_chart(pie, "M1")

Data Validation

from openpyxl.worksheet.datavalidation import DataValidation

# Dropdown list
dv = DataValidation(
    type="list",
    formula1='"Option1,Option2,Option3"',
    allow_blank=True
)
dv.error = "Please select from list"
dv.errorTitle = "Invalid Input"
ws.add_data_validation(dv)
dv.add('A1:A100')

# Number range
dv_num = DataValidation(
    type="whole",
    operator="between",
    formula1="1",
    formula2="100"
)
ws.add_data_validation(dv_num)
dv_num.add('B1:B100')

Sheet Operations

# Create new sheet
ws2 = wb.create_sheet("Data")
ws3 = wb.create_sheet("Summary", 0)  # At position 0

# Rename
ws.title = "Main Report"

# Delete
del wb["Sheet2"]

# Copy
source = wb["Template"]
target = wb.copy_worksheet(source)

Row/Column Operations

# Set column width
ws.column_dimensions['A'].width = 20

# Set row height
ws.row_dimensions[1].height = 30

# Hide column
ws.column_dimensions['C'].hidden = True

# Freeze panes
ws.freeze_panes = 'B2'  # Freeze row 1 and column A

# Auto-filter
ws.auto_filter.ref = "A1:D100"

Best Practices

1. Use Templates: Start with a.xlsx template for complex formatting
2. Batch Operations: Minimize cell-by-cell operations for speed
3. Named Ranges: Use defined names for clearer formulas
4. Data Validation: Add validation to prevent input errors
5. Save Incrementally: For large files, save periodically

Common Patterns

Data Import

def import_csv_to_xlsx(csv_path, xlsx_path):
    import csv
    wb = Workbook()
    ws = wb.active

    with open(csv_path) as f:
        reader = csv.reader(f)
        for row in reader:
            ws.append(row)

    wb.save(xlsx_path)

Report Template

def create_monthly_report(data, output_path):
    wb = Workbook()
    ws = wb.active
    ws.title = "Monthly Report"

    # Headers
    headers = ['Date', 'Revenue', 'Expenses', 'Profit']
    ws.append(headers)

    # Style headers
    for col in range(1, 5):
        cell = ws.cell(1, col)
        cell.font = Font(bold=True)
        cell.fill = PatternFill('solid', fgColor='4472C4')
        cell.font = Font(bold=True, color='FFFFFF')

    # Data
    for row in data:
        ws.append(row)

    # Add totals
    last_row = len(data) + 1
    ws.cell(last_row + 1, 1, 'TOTAL')
    ws.cell(last_row + 1, 2, f'=SUM(B2:B{last_row})')
    ws.cell(last_row + 1, 3, f'=SUM(C2:C{last_row})')
    ws.cell(last_row + 1, 4, f'=SUM(D2:D{last_row})')

    wb.save(output_path)

Examples

Example 1: Budget Tracker

from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.utils import get_column_letter

wb = Workbook()
ws = wb.active
ws.title = "Budget 2024"

# Headers
months = ['Category', 'Jan', 'Feb', 'Mar', 'Q1 Total']
ws.append(months)

# Categories and data
budget_data = [
    ['Salary', 5000, 5000, 5000],
    ['Rent', -1500, -1500, -1500],
    ['Utilities', -200, -180, -220],
    ['Food', -400, -450, -380],
    ['Transport', -150, -160, -140],
    ['Entertainment', -200, -250, -200],
]

for row in budget_data:
    ws.append(row + [f'=SUM(B{ws.max_row + 1}:D{ws.max_row + 1})'])

# Total row
ws.append(['TOTAL',
    f'=SUM(B2:B{ws.max_row})',
    f'=SUM(C2:C{ws.max_row})',
    f'=SUM(D2:D{ws.max_row})',
    f'=SUM(E2:E{ws.max_row})'
])

# Formatting
header_fill = PatternFill('solid', fgColor='366092')
header_font = Font(bold=True, color='FFFFFF')

for cell in ws[1]:
    cell.fill = header_fill
    cell.font = header_font
    cell.alignment = Alignment(horizontal='center')

# Currency format
for row in ws.iter_rows(min_row=2, min_col=2, max_col=5):
    for cell in row:
        cell.number_format = '$#,##0.00'

# Column widths
ws.column_dimensions['A'].width = 15
for col in range(2, 6):
    ws.column_dimensions[get_column_letter(col)].width = 12

wb.save('budget_2024.xlsx')

Example 2: Sales Dashboard

from openpyxl import Workbook
from openpyxl.chart import BarChart, PieChart, Reference
from openpyxl.styles import Font, PatternFill

wb = Workbook()
ws = wb.active
ws.title = "Sales Dashboard"

# Data
ws.append(['Region', 'Q1', 'Q2', 'Q3', 'Q4'])
data = [
    ['North', 150000, 165000, 180000, 195000],
    ['South', 120000, 125000, 140000, 155000],
    ['East', 180000, 190000, 210000, 225000],
    ['West', 95000, 110000, 125000, 140000],
]
for row in data:
    ws.append(row)

# Bar Chart
data_ref = Reference(ws, min_col=2, min_row=1, max_col=5, max_row=5)
cats_ref = Reference(ws, min_col=1, min_row=2, max_row=5)

bar = BarChart()
bar.type = "col"
bar.title = "Quarterly Sales by Region"
bar.add_data(data_ref, titles_from_data=True)
bar.set_categories(cats_ref)
bar.height = 10
bar.width = 15
ws.add_chart(bar, "A8")

# Pie Chart - Q4 breakdown
pie_data = Reference(ws, min_col=5, min_row=1, max_row=5)
pie = PieChart()
pie.title = "Q4 Market Share"
pie.add_data(pie_data, titles_from_data=True)
pie.set_categories(cats_ref)
ws.add_chart(pie, "J8")

wb.save('sales_dashboard.xlsx')

Limitations

• Cannot execute VBA macros
• Complex pivot tables not fully supported
• Limited sparkline support
• External data connections not supported
• Some advanced chart types unavailable

Installation

pip install openpyxl

Resources

• openpyxl Documentation
• GitHub Repository
• Working with Styles