Data Analysis

作者 claude-office-skills9c4c7d5cd281MIT499 个星标收录于 2026年10月8日更新于 2026年10月8日仓库8个月前更新

Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel/CSV data.

仅含说明Data & Analytics
AI 生成的概览

分析电子表格数据，产出洞察、统计结果、图表建议和 Markdown 报告。

功能
引导智能体对 Excel、XLS 或 CSV 数据进行探索性和统计分析，涵盖数据概览、关键指标、趋势、群组分析和数据透视表设计。它会生成包含数据概览、统计摘要、洞察报告、公式建议和图表规格的 Markdown 报告。它还会推荐合适的图表类型，并给出销售、客户和财务数据的分析流程。
适用场景
当需要探索、汇总或统计分析电子表格或 CSV 数据集时使用。它适合关键指标、趋势、相关性、数据透视表、群组分析或图表建议等请求。它也适用于生成 Excel 或 Google Sheets 公式以及结构化分析报告。
运行要求
需要 xlsx、csv 或 xls 格式的电子表格输入。元数据引用了 office-mcp 服务器及 read_xlsx、analyze_spreadsheet、create_chart、pivot_table 等工具，以及可选的 create_xlsx 和 xlsx_to_json。它不附带脚本，并说明无法直接对数据执行代码。

Data Analysis Assistant

Analyze data in spreadsheets, uncover insights, and create compelling visualizations.

Overview

This skill helps you:

  • Understand and explore your data
  • Perform statistical analysis
  • Generate insights and recommendations
  • Create charts and visualizations
  • Write formulas and queries

How to Use

Getting Started

  1. Share your spreadsheet or data file
  2. Describe what you want to analyze
  3. Get insights, formulas, or visualizations

Analysis Types

Exploratory Analysis

"What patterns do you see in this data?""Give me an overview of this dataset""What are the key statistics?"

Specific Questions

"What was the total revenue by region?""Which products had the highest growth?""Is there a correlation between X and Y?"

Visualization Requests

"Create a chart showing sales trends""Make a comparison chart of Q1 vs Q2""Show the distribution of customer ages"

Output Formats

Data Overview

markdown
## Dataset Overview
**Rows**: 1,234**Columns**: 15**Date Range**: Jan 2025 - Dec 2025
### Column Summary| Column | Type | Non-null | Unique | Sample Values ||--------|------|----------|--------|---------------|| date | Date | 100% | 365 | 2025-01-01 || revenue | Number | 98% | 890 | $1,234.56 || region | Text | 100% | 5 | North, South |
### Data Quality Issues- [X] rows have missing values in [column]- [Y] potential duplicates detected

Statistical Analysis

markdown
## Statistical Summary
### [Metric Name]- **Mean**: X- **Median**: Y- **Std Dev**: Z- **Min/Max**: A / B
### Key Findings1. [Finding with statistical support]2. [Finding with statistical support]
### Recommendations- [Action based on analysis]

Insight Report

markdown
## Analysis Report: [Topic]
### Executive Summary[2-3 sentence overview of key findings]
### Key Metrics| Metric | Value | Change ||--------|-------|--------|| Total Revenue | $X | +Y% || Avg Order Value | $Z | -W% |
### Trends1. **[Trend 1]**: [Description with data]2. **[Trend 2]**: [Description with data]
### Recommendations1. [Actionable recommendation]2. [Actionable recommendation]

Common Analysis Workflows

Sales Analysis

1. "Show total sales by month"2. "Which products are top performers?"3. "What's the customer segment breakdown?"4. "Compare this year vs last year"5. "Forecast next quarter based on trends"

Customer Analysis

1. "What's the customer distribution by segment?"2. "Calculate customer lifetime value"3. "Which customers are at risk of churning?"4. "What's the acquisition cost vs LTV ratio?"

Financial Analysis

1. "Calculate profit margins by product"2. "What's the expense breakdown?"3. "Show cash flow trends"4. "Compare budget vs actual"

Formula Generation

Request Formulas

"Write a formula to calculate year-over-year growth""Create a VLOOKUP to match customer data""Make a dynamic sum based on criteria"

Formula Output

markdown
## Formula: [Purpose]
### Excel/Google Sheets```excel=SUMIFS(Sales[Amount], Sales[Region], "North", Sales[Date], ">="&DATE(2025,1,1))

Explanation

  • SUMIFS: Sums values meeting multiple criteria
  • First argument: Column to sum
  • Subsequent pairs: Criteria column + criteria value

Usage

Place in cell [X] where you want the result.


## Visualization Recommendations
### Choose the Right Chart| Data Type | Best Chart ||-----------|------------|| Trends over time | Line chart || Part of whole | Pie/Donut chart || Comparison | Bar chart || Distribution | Histogram || Correlation | Scatter plot || Geographic | Map chart |
### Chart Specifications```markdown## Recommended Chart: [Type]
**Data Series**:- X-axis: [Column] (e.g., Date)- Y-axis: [Column] (e.g., Revenue)- Series: [Column] (e.g., Region)
**Formatting**:- Title: "[Descriptive title]"- Colors: Use consistent color scheme- Labels: Show values on data points
**Chart Description**:[What this chart shows and why it's useful]

Advanced Analysis

Pivot Table Design

markdown
## Pivot Table: [Purpose]
**Rows**: [Field 1], [Field 2]**Columns**: [Field 3]**Values**: SUM of [Field 4], AVG of [Field 5]**Filters**: [Field 6]
Expected Output:| Region | Q1 | Q2 | Q3 | Q4 | Total ||--------|----|----|----|----|-------|| North | $X | $X | $X | $X | $X || South | $X | $X | $X | $X | $X |

Cohort Analysis

markdown
## Cohort Analysis
**Cohort Definition**: Customers grouped by [first purchase month]**Metric**: [Retention rate / Revenue / etc.]**Time Period**: [12 months]
| Cohort | M0 | M1 | M2 | M3 | ... ||--------|-----|-----|-----|-----|-----|| Jan 25 | 100%| 45% | 32% | 28% | ... || Feb 25 | 100%| 48% | 35% | 30% | ... |

Best Practices

For Better Analysis

  1. Clean data first: Handle missing values, duplicates
  2. Define metrics clearly: What exactly are you measuring?
  3. Consider context: Industry benchmarks, seasonality
  4. Validate findings: Cross-check with other data sources

For Better Visualizations

  1. Keep it simple: One main message per chart
  2. Label clearly: Title, axes, legend
  3. Use appropriate scale: Don't truncate misleadingly
  4. Consider colorblind users: Use patterns or distinct colors

Limitations

  • Cannot directly execute code on your data
  • Large datasets may need sampling
  • Complex statistical models need specialized tools
  • Real-time data requires live connections
  • Cannot guarantee 100% accuracy on OCR'd data

来源与署名

来源：claude-office-skills/skills位于data-analysis提交9c4c7d5

许可证： MIT

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

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