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area-basic: Basic Area Chart

A fundamental area chart that visualizes data as a filled region between the line and the axis, ideal for showing magnitude and trends over time or ordered categories.

Data Requirements

  • x: Numeric or categorical column for x-axis values (often time or sequence)
  • y: Numeric column for y-axis values (the values to plot)

Optional Parameters

  • figsize: Figure size as (width, height) tuple (default: (10, 6))
  • alpha: Transparency level for fill (default: 0.5)
  • color: Fill color (default: "steelblue")
  • title: Plot title (default: None)
  • xlabel: X-axis label (default: uses column name)
  • ylabel: Y-axis label (default: uses column name)
  • line_color: Color of the line on top of area (default: same as color)
  • line_width: Width of the line (default: 2)

Expected Output

An area chart with:

  • X and Y axes labeled with column names (or custom labels)
  • Filled area between the line and the x-axis
  • Visible line on top of the filled area
  • Grid visible but subtle (alpha ≤ 0.3)
  • Professional appearance with proper spacing
  • Smooth transitions between data points

Quality Criteria

  • Axes labeled clearly
  • Grid visible but subtle
  • Area fill clearly visible with appropriate transparency
  • Line visible on top of area
  • No overlapping labels
  • Appropriate figure size
  • Type hints and validation present

Examples

Example 1: Basic Usage

import pandas as pd
data = pd.DataFrame({
    'month': [1, 2, 3, 4, 5, 6],
    'sales': [100, 150, 130, 180, 200, 220]
})
fig = create_plot(data, 'month', 'sales')

Example 2: Custom Styling

fig = create_plot(
    data,
    'month',
    'sales',
    alpha=0.3,
    color='green',
    title='Monthly Sales'
)

Implementation Notes

  • Use appropriate alpha value for fill visibility
  • Ensure the line is visible above the filled area
  • Handle missing/NaN values gracefully
  • Validate that y column contains numeric data

Tags

area, trend, time-series, basic, 2d

Use Cases

  • Visualizing stock price trends over time
  • Showing website traffic patterns by hour or day
  • Displaying cumulative sales or revenue data
  • Monitoring resource usage (CPU, memory) over time