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Module 3: Build Sprint 2

Understanding Your Second Ticket

Learn how to approach your second ticket in the Labs project and understand the development workflow.

Second Ticket Details

View your second ticket details and requirements on GitHub:

Second Ticket Documentation

Resources

Approaching Your Second Feature

Learn how to create dynamic visualizations using Altair and integrate them with your monster database.

Implementation Checklist

  • Create a Jupyter notebook for visualization exploration
  • Experiment with different chart types using monster data
  • Implement the chart function with proper typing
  • Configure chart properties for dark theme
  • Add interactive tooltips and encodings
  • Integrate the visualization with the API
  • Test the chart rendering in the web app
  • Ensure proper JSON serialization
# Example Visualization Implementation

from altair import Chart, Tooltip
from pandas import DataFrame


def chart(df: DataFrame, x: str, y: str, target: str) -> Chart:
    """Create an interactive scatter plot visualization.
    
    Args:
        df: DataFrame containing monster data
        x: Column name for x-axis
        y: Column name for y-axis
        target: Column name for color encoding
        
    Returns:
        Altair Chart object
    """
    # Configure chart properties for dark theme
    properties = {
        "width": 600,
        "height": 400,
        "background": "#2a303c",
        "padding": 20
    }
    
    # Create base chart with dark theme configuration
    graph = Chart(
        df,
        title=f"{y} by {x} for {target}",
    ).mark_circle(size=100).encode(
        x=x,
        y=y,
        color=target,
        tooltip=Tooltip(df.columns.to_list())
    ).properties(
        **properties
    ).configure(
        axis={'labelColor': '#ffffff', 'titleColor': '#ffffff'},
        title={'color': '#ffffff'},
        view={'stroke': 'transparent'},
        background='#2a303c'
    )
    
    return graph


# Example usage in FastAPI endpoint
@app.get("/view")
async def get_visualization():
    df = monster_db.dataframe()
    if df is not None:
        chart_obj = chart(df, "strength", "agility", "monster_type")
        return JSONResponse(content=chart_obj.to_dict())

Resources