Gantt charts

Download notebookView on GitHubRun when the site was built.

This tutorial demonstrates how to create Gantt charts using maxplotlib across different backends.

Gantt charts are useful for visualizing project schedules, task timelines, and resource allocation.

from maxplotlib import Canvas

Basic Gantt Chart

Let’s create a simple project timeline with 5 tasks.

# Define project tasks
tasks = ["Planning", "Design", "Development", "Testing", "Deployment"]
start_times = [0, 5, 10, 25, 35]  # Days from project start
durations = [5, 5, 15, 10, 5]  # Duration in days

# Create canvas and add gantt chart
canvas = Canvas(nrows=1, ncols=1, figsize=(12, 6))
canvas.gantt(
    tasks=tasks,
    start_times=start_times,
    durations=durations,
    color="skyblue",
    edgecolor="navy",
    alpha=0.8,
)

canvas.set_xlabel("Time (days)")
canvas.set_title("Project Timeline")
canvas.render(backend="matplotlib")

(<Figure size 1200x600 with 1 Axes>,
 array([[<Axes: title={'center': 'Project Timeline'}, xlabel='Time (days)'>]],
       dtype=object))

Multiple Project Phases

Visualize different project phases with different colors using layers.

# Phase 1: Planning and Design
phase1_tasks = ["Requirements", "Architecture", "UI Design"]
phase1_starts = [0, 3, 6]
phase1_durations = [3, 3, 4]

# Phase 2: Implementation
phase2_tasks = ["Backend Dev", "Frontend Dev", "Integration"]
phase2_starts = [10, 10, 20]
phase2_durations = [10, 10, 5]

# Phase 3: Quality Assurance
phase3_tasks = ["Unit Tests", "Integration Tests", "UAT"]
phase3_starts = [25, 28, 32]
phase3_durations = [3, 4, 3]

canvas = Canvas(nrows=1, ncols=1, figsize=(14, 8))

# Add each phase with different colors
canvas.gantt(
    phase1_tasks,
    phase1_starts,
    phase1_durations,
    color="lightblue",
    edgecolor="blue",
    label="Planning",
)
canvas.gantt(
    phase2_tasks,
    phase2_starts,
    phase2_durations,
    color="lightgreen",
    edgecolor="green",
    label="Development",
)
canvas.gantt(
    phase3_tasks,
    phase3_starts,
    phase3_durations,
    color="lightyellow",
    edgecolor="orange",
    label="Testing",
)

canvas.set_xlabel("Time (days)")
canvas.set_title("Multi-Phase Project Timeline")
canvas.set_legend(True)
canvas.render(backend="matplotlib")

(<Figure size 1400x800 with 1 Axes>,
 array([[<Axes: title={'center': 'Multi-Phase Project Timeline'}, xlabel='Time (days)'>]],
       dtype=object))

Resource Allocation

Show how different team members are allocated across tasks.

# Team member assignments
team_members = ["Alice", "Bob", "Charlie", "Diana", "Eve"]
task_starts = [0, 5, 3, 8, 10]
task_durations = [8, 6, 10, 7, 5]

canvas = Canvas(nrows=1, ncols=1, figsize=(12, 6))
canvas.gantt(
    tasks=team_members,
    start_times=task_starts,
    durations=task_durations,
    color="coral",
    edgecolor="darkred",
    alpha=0.7,
)

canvas.set_xlabel("Week")
canvas.set_title("Team Resource Allocation")
canvas.render(backend="matplotlib")

(<Figure size 1200x600 with 1 Axes>,
 array([[<Axes: title={'center': 'Team Resource Allocation'}, xlabel='Week'>]],
       dtype=object))

Interactive Gantt Chart with Plotly

Create an interactive version that allows zooming and hovering.

tasks = ["Research", "Prototype", "Development", "Testing", "Launch"]
start_times = [0, 10, 20, 40, 50]
durations = [10, 10, 20, 10, 5]

canvas = Canvas(nrows=1, ncols=1, figsize=(12, 6))
canvas.gantt(
    tasks=tasks,
    start_times=start_times,
    durations=durations,
    color="steelblue",
    alpha=0.8,
)

canvas.set_xlabel("Days")
canvas.set_title("Interactive Project Timeline")
fig = canvas.render(backend="plotly")
fig.show()

Milestones and Dependencies

Visualize project milestones (zero-duration tasks) alongside regular tasks.

# Regular tasks
tasks = ["Phase 1", "Milestone: Review", "Phase 2", "Milestone: Demo", "Phase 3"]
start_times = [0, 10, 10, 25, 25]
durations = [10, 0, 15, 0, 10]  # Milestones have zero duration

canvas = Canvas(nrows=1, ncols=1, figsize=(12, 6))
canvas.gantt(
    tasks=tasks,
    start_times=start_times,
    durations=durations,
    color="lightseagreen",
    edgecolor="teal",
)

canvas.set_xlabel("Days")
canvas.set_title("Project with Milestones")
canvas.render(backend="matplotlib")

(<Figure size 1200x600 with 1 Axes>,
 array([[<Axes: title={'center': 'Project with Milestones'}, xlabel='Days'>]],
       dtype=object))

Comparison: Different Backends

The same Gantt chart rendered with different backends.

tasks = ["Task A", "Task B", "Task C", "Task D"]
start_times = [0, 5, 8, 12]
durations = [5, 6, 8, 4]

# Matplotlib
canvas_mpl = Canvas(nrows=1, ncols=1, figsize=(10, 5))
canvas_mpl.gantt(tasks, start_times, durations, color="skyblue")
canvas_mpl.set_title("Matplotlib Backend")
canvas_mpl.render(backend="matplotlib")

# Plotly
canvas_plotly = Canvas(nrows=1, ncols=1, figsize=(10, 5))
canvas_plotly.gantt(tasks, start_times, durations, color="skyblue")
canvas_plotly.set_title("Plotly Backend")
fig = canvas_plotly.render(backend="plotly")
fig.show()

Summary

Gantt charts in maxplotlib support:

• Simple task timelines
• Multiple phases with different colors
• Resource allocation visualization
• Milestones (zero-duration tasks)
• All backends: matplotlib, plotly, plotext, tikzfigure
• Customizable colors, transparency, and edge colors