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Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel/CSV data.
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| name | data-analysis |
| description | Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel/CSV data. |
| version | 1.0.0 |
| author | claude-office-skills |
| license | MIT |
| category | finance |
| tags | ["data","analysis","spreadsheet","excel","visualization","insights"] |
| department | All |
| models | {"recommended":["claude-sonnet-4","claude-opus-4"],"compatible":["claude-3-5-sonnet","gpt-4","gpt-4o"]} |
| mcp | {"server":"office-mcp","tools":["read_xlsx","analyze_spreadsheet","create_chart","pivot_table"],"optional_tools":["create_xlsx","xlsx_to_json"]} |
| capabilities | ["data_analysis","statistical_analysis","visualization","trend_detection","reporting"] |
| input | {"required":[{"type":"file","formats":["xlsx","csv","xls"],"description":"The spreadsheet data to analyze"}],"optional":[{"type":"text","name":"analysis_goal","description":"Specific questions or analysis goals"},{"type":"text","name":"output_format","description":"Preferred output format (report, chart, summary)"}]} |
| output | {"primary":{"type":"report","format":"markdown","sections":["data_overview","key_insights","visualizations","recommendations"]}} |
| languages | ["en","zh"] |
| related_skills | ["excel-automation","report-generator","xlsx-manipulation"] |
Analyze data in spreadsheets, uncover insights, and create compelling visualizations.
This skill helps you:
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"
## 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 Summary
### [Metric Name]
- **Mean**: X
- **Median**: Y
- **Std Dev**: Z
- **Min/Max**: A / B
### Key Findings
1. [Finding with statistical support]
2. [Finding with statistical support]
### Recommendations
- [Action based on analysis]
## 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% |
### Trends
1. **[Trend 1]**: [Description with data]
2. **[Trend 2]**: [Description with data]
### Recommendations
1. [Actionable recommendation]
2. [Actionable recommendation]
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"
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?"
1. "Calculate profit margins by product"
2. "What's the expense breakdown?"
3. "Show cash flow trends"
4. "Compare budget vs actual"
"Write a formula to calculate year-over-year growth"
"Create a VLOOKUP to match customer data"
"Make a dynamic sum based on criteria"
## Formula: [Purpose]
### Excel/Google Sheets
```excel
=SUMIFS(Sales[Amount], Sales[Region], "North", Sales[Date], ">="&DATE(2025,1,1))
SUMIFS: Sums values meeting multiple criteriaPlace 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]
## 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
**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% | ... |