dataScore: 91/100For Julius AI
Interactive Dashboard and Data Visualization Report

Creates a visual dashboard with relevant charts and data-driven narrative for decision-makers
Fill in the variables

Your personalized prompt

You are an expert in data visualization and storytelling. Create a complete visual dashboard/report from my data.

# BRIEF
Raw data: {{donnees_brutes}}
Business question to answer: {{question_business}}
Desired deliverable format: {{format_livrable}}
Target audience: {{audience_cible}}

# EXPECTED DASHBOARD

## 1. Dashboard Structure
Propose a clear organization:
- Overview (main KPIs)
- Detailed analysis section
- Temporal trends section
- Comparisons/segments section
- Insights and recommendations section

## 2. KPIs and Key Metrics
Identify 5-8 essential indicators:
- KPI name
- Calculation formula
- Why it matters for {{audience_cible}}
- Performance threshold (if applicable)
- Recommended display format

## 3. Recommended Visualizations
For each chart:

**Chart 1: [Descriptive Title]**
- Chart type (bar, line, scatter, heatmap, etc.)
- Variables to display (X and Y axes)
- Main insight to communicate
- Customization (colors, labels, annotations)

**Chart 2: [Descriptive Title]**
[...same structure]

Create 5-7 complementary visualizations.

## 4. Narrative and Storytelling
Write a 3-act narrative:

**Current Situation**
- What do the data show today?
- Key figures to remember

**Important Discoveries**
- Significant trends
- Anomalies or surprises
- Interesting correlations

**Actionable Recommendations**
- Top 3 actions to take
- Expected impact
- Prioritization

## 5. Python Code for Generation
```python
import pandas as pd
import plotly.express as px  # or matplotlib/seaborn
import plotly.graph_objects as go

# Loading and preparation
# ...

# Creating visualizations
# Figure 1
# Figure 2
# ...

# Dashboard assembly (Plotly Dash or Streamlit)
# ...

# Export to {{format_livrable}}
```

## 6. Interactivity (if applicable)
- Recommended filters (dates, categories, segments)
- Drill-down capabilities
- Informative tooltips
- Cross-filtering between charts

## 7. Design and Accessibility
- Color palette (consistent with brand or standards)
- Clear visual hierarchy
- Readability for {{audience_cible}}
- Mobile-friendly version if relevant

## 8. Quality Checklist
- [ ] All charts have a clear title
- [ ] Axes are properly labeled
- [ ] Units are displayed
- [ ] Data sources are mentioned
- [ ] Main insights are highlighted
- [ ] Dashboard answers {{question_business}}

Adapt the technical level to {{audience_cible}}. Prioritize clarity and actionability.
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