vamseeachanta
vamseeachanta/workspace-hub
相关职业SOC
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
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npx skills add https://github.com/vamseeachanta/workspace-hub --skill openpyxl-3-chart-generation命令会保持在同一行。复制前请横向滚动并检查完整内容。
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Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
正在显示 SKILL.md
基于 SOC 职业分类
| name | openpyxl-3-chart-generation |
| description | Sub-skill of openpyxl: 3. Chart Generation. |
| version | 1.0.0 |
| category | data |
| type | reference |
| scripts_exempt | true |
"""
Create various chart types in Excel.
"""
from openpyxl import Workbook
from openpyxl.chart import (
BarChart, LineChart, PieChart, AreaChart, ScatterChart,
Reference, Series
)
from openpyxl.chart.label import DataLabelList
from openpyxl.chart.layout import Layout, ManualLayout
def create_charts_workbook(output_path: str) -> None:
"""Create workbook with various chart examples."""
wb = Workbook()
ws = wb.active
ws.title = "Chart Data"
# Sample data for charts
data = [
["Month", "Sales", "Expenses", "Profit"],
["Jan", 15000, 12000, 3000],
["Feb", 18000, 13000, 5000],
["Mar", 22000, 14500, 7500],
["Apr", 20000, 14000, 6000],
["May", 25000, 15000, 10000],
["Jun", 28000, 16000, 12000],
]
for row in data:
ws.append(row)
# Bar Chart
bar_chart = BarChart()
bar_chart.type = "col"
bar_chart.grouping = "clustered"
bar_chart.title = "Monthly Financial Overview"
bar_chart.y_axis.title = "Amount ($)"
bar_chart.x_axis.title = "Month"
# Data references
data_ref = Reference(ws, min_col=2, max_col=4, min_row=1, max_row=7)
cats_ref = Reference(ws, min_col=1, min_row=2, max_row=7)
bar_chart.add_data(data_ref, titles_from_data=True)
bar_chart.set_categories(cats_ref)
bar_chart.shape = 4 # Rounded corners
# Style the chart
bar_chart.style = 10
bar_chart.width = 15
bar_chart.height = 10
ws.add_chart(bar_chart, "F2")
# Line Chart
line_chart = LineChart()
line_chart.title = "Profit Trend"
line_chart.y_axis.title = "Profit ($)"
line_chart.x_axis.title = "Month"
line_chart.style = 12
profit_data = Reference(ws, min_col=4, min_row=1, max_row=7)
line_chart.add_data(profit_data, titles_from_data=True)
line_chart.set_categories(cats_ref)
# Add markers
line_chart.series[0].marker.symbol = "circle"
line_chart.series[0].marker.size = 7
line_chart.series[0].graphicalProperties.line.width = 25000 # in EMUs
ws.add_chart(line_chart, "F18")
# Pie Chart on new sheet
pie_ws = wb.create_sheet("Pie Chart")
pie_data = [
["Category", "Value"],
["Product A", 35],
["Product B", 25],
["Product C", 20],
["Product D", 15],
["Other", 5],
]
for row in pie_data:
pie_ws.append(row)
pie_chart = PieChart()
pie_chart.title = "Sales by Product Category"
pie_data_ref = Reference(pie_ws, min_col=2, min_row=2, max_row=6)
pie_labels_ref = Reference(pie_ws, min_col=1, min_row=2, max_row=6)
pie_chart.add_data(pie_data_ref)
pie_chart.set_categories(pie_labels_ref)
# Add data labels with percentages
pie_chart.dataLabels = DataLabelList()
pie_chart.dataLabels.showPercent = True
pie_chart.dataLabels.showVal = False
pie_chart.dataLabels.showCatName = True
pie_ws.add_chart(pie_chart, "D2")
# Stacked Area Chart
area_ws = wb.create_sheet("Area Chart")
area_data = [
["Quarter", "Region A", "Region B", "Region C"],
["Q1", 5000, 4000, 3000],
["Q2", 6000, 4500, 3500],
["Q3", 7000, 5000, 4000],
["Q4", 8000, 5500, 4500],
]
for row in area_data:
area_ws.append(row)
area_chart = AreaChart()
area_chart.title = "Regional Sales Growth"
area_chart.style = 13
area_chart.grouping = "stacked"
area_data_ref = Reference(area_ws, min_col=2, max_col=4, min_row=1, max_row=5)
area_cats_ref = Reference(area_ws, min_col=1, min_row=2, max_row=5)
area_chart.add_data(area_data_ref, titles_from_data=True)
area_chart.set_categories(area_cats_ref)
area_ws.add_chart(area_chart, "F2")
# Scatter Chart
scatter_ws = wb.create_sheet("Scatter Chart")
scatter_data = [
["X", "Y"],
[1, 2.5],
[2, 4.1],
[3, 5.8],
[4, 8.2],
[5, 10.1],
[6, 12.5],
[7, 14.8],
]
for row in scatter_data:
scatter_ws.append(row)
scatter_chart = ScatterChart()
scatter_chart.title = "Correlation Analysis"
scatter_chart.x_axis.title = "X Values"
scatter_chart.y_axis.title = "Y Values"
scatter_chart.style = 13
x_values = Reference(scatter_ws, min_col=1, min_row=2, max_row=8)
y_values = Reference(scatter_ws, min_col=2, min_row=2, max_row=8)
series = Series(y_values, x_values, title="Data Points")
scatter_chart.series.append(series)
# Add trendline
from openpyxl.chart.trendline import Trendline
series.trendline = Trendline(trendlineType='linear')
scatter_ws.add_chart(scatter_chart, "D2")
wb.save(output_path)
print(f"Charts workbook saved to {output_path}")
create_charts_workbook("charts_example.xlsx")