Data Analysis

作者 claude-office-skills9c4c7d5cd281MIT499 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫8 個月前更新

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

僅含說明Data & Analytics
AI 產生的概覽

分析試算表資料，產出洞察、統計結果、圖表建議和 Markdown 報告。

功能
引導代理對 Excel、XLS 或 CSV 資料進行探索性與統計分析，涵蓋資料概覽、關鍵指標、趨勢、同群分析和樞紐分析表設計。它會產生包含資料概覽、統計摘要、洞察報告、公式建議和圖表規格的 Markdown 報告。它也會推薦合適的圖表類型，並提供銷售、客戶和財務資料的分析流程。
適用情境
當需要探索、彙總或統計分析試算表或 CSV 資料集時使用。它適合關鍵指標、趨勢、相關性、樞紐分析表、同群分析或圖表建議等需求。它也適用於產生 Excel 或 Google Sheets 公式以及結構化分析報告。
執行需求
需要 xlsx、csv 或 xls 格式的試算表輸入。中繼資料引用了 office-mcp 伺服器及 read_xlsx、analyze_spreadsheet、create_chart、pivot_table 等工具，以及選用的 create_xlsx 和 xlsx_to_json。它不附帶指令碼，並說明無法直接對資料執行程式碼。

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

來源與署名

來源：claude-office-skills/skills位於data-analysis提交9c4c7d5

授權條款： MIT

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

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