A Gantt chart is a horizontal bar chart that visualizes project schedules and timelines. Each task is represented as a horizontal bar spanning from its start date to end date, making it easy to see task durations, overlaps, and the overall project timeline at a glance. Gantt charts are essential for project management, helping teams understand task sequences and identify scheduling conflicts.
""" anyplot.ai
gantt-basic: Basic Gantt Chart
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 91/100 | Updated: 2026-05-10
"""
import os
from datetime import datetime
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD"]
# Data - Construction Project Timeline starting mid-February
tasks_data = {
"task": [
"Site Preparation",
"Foundation Work",
"Structural Framing",
"Roofing",
"Exterior Walls",
"Interior Framing",
"Electrical Work",
"Plumbing Installation",
"HVAC Installation",
"Drywall & Finishing",
"Painting",
"Final Inspection",
],
"start": [
"2026-02-15",
"2026-02-22",
"2026-03-15",
"2026-04-12",
"2026-03-22",
"2026-04-19",
"2026-05-03",
"2026-05-03",
"2026-05-10",
"2026-05-17",
"2026-06-07",
"2026-06-21",
],
"end": [
"2026-02-21",
"2026-03-14",
"2026-04-11",
"2026-05-02",
"2026-04-18",
"2026-05-02",
"2026-05-16",
"2026-05-30",
"2026-05-23",
"2026-06-06",
"2026-06-20",
"2026-06-28",
],
"category": [
"Foundation",
"Foundation",
"Structure",
"Structure",
"Exterior",
"Interior",
"Systems",
"Systems",
"Systems",
"Finishing",
"Finishing",
"Finalization",
],
}
df = pd.DataFrame(tasks_data)
df["start"] = pd.to_datetime(df["start"])
df["end"] = pd.to_datetime(df["end"])
df["duration"] = (df["end"] - df["start"]).dt.days
df = df.sort_values("start").reset_index(drop=True)
df["start_num"] = mdates.date2num(df["start"])
# Set seaborn style with theme-adaptive colors
sns.set_theme(
style="ticks",
rc={
"figure.facecolor": PAGE_BG,
"axes.facecolor": PAGE_BG,
"axes.edgecolor": INK_SOFT,
"axes.labelcolor": INK,
"text.color": INK,
"xtick.color": INK_SOFT,
"ytick.color": INK_SOFT,
"grid.color": INK,
"grid.alpha": 0.10,
"legend.facecolor": ELEVATED_BG,
"legend.edgecolor": INK_SOFT,
},
)
# Category palette using Okabe-Ito
category_order = ["Foundation", "Structure", "Exterior", "Interior", "Systems", "Finishing", "Finalization"]
category_palette = {
"Foundation": IMPRINT[0],
"Structure": IMPRINT[1],
"Exterior": IMPRINT[2],
"Interior": IMPRINT[3],
"Systems": IMPRINT[4],
"Finishing": IMPRINT[5],
"Finalization": INK_SOFT,
}
# Create plot
fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)
# Use seaborn barplot with hue for category coloring
sns.barplot(
data=df,
y="task",
x="duration",
hue="category",
hue_order=category_order,
palette=category_palette,
orient="h",
dodge=False,
ax=ax,
edgecolor=PAGE_BG,
linewidth=1.5,
alpha=0.9,
legend=False,
)
# Shift bars to start date positions
for bar, start_num in zip(ax.patches, df["start_num"], strict=True):
bar.set_x(start_num)
# Format x-axis as dates
ax.xaxis_date()
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %d"))
ax.xaxis.set_major_locator(mdates.WeekdayLocator(byweekday=0, interval=2))
# Add current date indicator
today = datetime(2026, 5, 10)
ax.axvline(x=mdates.date2num(today), color="#E74C3C", linestyle="--", linewidth=2.5, label="Today", alpha=0.8)
# Styling
ax.set_xlabel("Timeline", fontsize=20, color=INK)
ax.set_ylabel("Tasks", fontsize=20, color=INK)
ax.set_title("gantt-basic · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK, pad=20)
ax.tick_params(axis="x", labelsize=16, colors=INK_SOFT, rotation=45)
ax.tick_params(axis="y", labelsize=16, colors=INK_SOFT)
# Remove y-axis grid, keep x-axis grid subtle
ax.grid(axis="x", alpha=0.10, linestyle="-", linewidth=0.8)
# Create legend positioned outside plot area
legend_elements = [
plt.Rectangle((0, 0), 1, 1, facecolor=color, edgecolor=INK_SOFT, linewidth=1, label=cat)
for cat, color in category_palette.items()
if cat in df["category"].values
]
legend_elements.append(plt.Line2D([0], [0], color="#E74C3C", linestyle="--", linewidth=2.5, label="Today"))
ax.legend(handles=legend_elements, loc="upper left", bbox_to_anchor=(1.01, 1), fontsize=14, framealpha=0.95)
# Invert y-axis to have first task at top
ax.invert_yaxis()
# Set x-axis limits with padding
date_min = df["start"].min() - pd.Timedelta(days=3)
date_max = df["end"].max() + pd.Timedelta(days=3)
ax.set_xlim(mdates.date2num(date_min), mdates.date2num(date_max))
plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)
Part of Basic Gantt Chart on anyplot.ai.