Skip to main content

Chapter 3: Data Analysis and Summarization

Data Analysis Prompts​

Analyze this \{DATA_TYPE\} data:

\{DATA\}

Questions:
1. \{QUESTION_1\}
2. \{QUESTION_2\}
3. \{QUESTION_3\}

Output format:
- Executive summary (2-3 sentences)
- Key findings (bullet points)
- Data table (if applicable)
- Visualization recommendations
- Limitations/caveats

Document Summarization​

Summarize this \{DOCUMENT_TYPE\}:

\{TEXT\}

Requirements:
- Length: \{LENGTH\}
- Focus: \{FOCUS_AREAS\}
- Audience: \{AUDIENCE\}

Structure:
1. One-sentence summary
2. Key points (\{NUMBER\})
3. Notable quotes (if relevant)
4. Action items (if applicable)

Information Extraction​

Extract the following from this text:

\{TEXT\}

Extract:
- Names: [list]
- Dates: [list]  
- Locations: [list]
- Key facts: [list]
- Numbers/statistics: [list]

Return as JSON:
{
  "names": [],
  "dates": [],
  "locations": [],
  "facts": [],
  "statistics": []
}

Comparative Analysis​

Compare \{ITEM_A\} vs \{ITEM_B\}:

Data:
\{DATA\}

Comparison criteria:
1. \{CRITERION_1\}
2. \{CRITERION_2\}
3. \{CRITERION_3\}

Output:
| Criterion | \{ITEM_A\} | \{ITEM_B\} | Winner |
|-----------|----------|----------|--------|

Final recommendation with reasoning.

Key Takeaways​

Summary
  1. Define specific questions for analysis
  2. Request structured outputs (tables, JSON)
  3. Include audience and purpose
  4. Ask for limitations/caveats

← Previous: Code Generation | Take the Quiz β†’