A vertical bar chart showing the time spent in each heart rate training zone (Z1–Z5) during a workout or training period. Each bar uses the conventional zone color semantics (grey for Z1 recovery, blue for Z2 endurance, green for Z3 aerobic, orange for Z4 threshold, red for Z5 maximum) and is annotated with its duration, making the distribution of training intensity immediately readable. This is the standard summary chart found in fitness platforms such as Garmin, Strava, and Polar, and it reveals at a glance whether a session was easy, balanced, or high-intensity.
""" anyplot.ai
bar-heart-rate-zones: Time in Heart Rate Zones Bar Chart
Library: plotnine 0.15.7 | Python 3.13.13
Quality: 88/100 | Created: 2026-06-14
"""
import os
import pandas as pd
from plotnine import (
aes,
element_blank,
element_line,
element_rect,
element_text,
geom_bar,
geom_text,
ggplot,
labs,
scale_alpha_manual,
scale_fill_manual,
scale_y_continuous,
theme,
)
# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
GRID = "#1A1A171E" if THEME == "light" else "#F0EFE81E"
# Heart rate zone colors — semantic exception to Imprint canonical order:
# Z1–Z5 carry strong fitness conventions (grey/blue/green/orange/red),
# mapped to the nearest Imprint palette members.
# Z1 uses fixed #6B6A63 (not theme-adaptive INK_MUTED) so data colors
# stay identical across light and dark renders.
ZONE_COLORS = ["#6B6A63", "#4467A3", "#009E73", "#BD8233", "#AE3030"]
# Data — 75-minute endurance run with threshold intervals
zones = ["Z1\nRecovery", "Z2\nEndurance", "Z3\nAerobic", "Z4\nThreshold", "Z5\nMaximum"]
minutes = [12.0, 38.0, 14.0, 9.0, 2.0]
df = pd.DataFrame({"zone": zones, "minutes": minutes})
df["zone"] = pd.Categorical(df["zone"], categories=zones, ordered=True)
df["duration_label"] = df["minutes"].apply(lambda m: f"{int(m)} min")
# Z2 (Endurance) dominates at 51% — map emphasis aesthetic to guide reader focus
df["emphasis"] = ["secondary", "primary", "secondary", "secondary", "secondary"]
title = "bar-heart-rate-zones · python · plotnine · anyplot.ai"
caption = "HR bounds: Z1 < 120 | Z2: 120–139 | Z3: 140–154 | Z4: 155–169 | Z5: ≥ 170 bpm"
plot = (
ggplot(df, aes(x="zone", y="minutes"))
+ geom_bar(aes(fill="zone", alpha="emphasis"), stat="identity", width=0.65, show_legend=False)
+ geom_text(aes(label="duration_label"), va="bottom", nudge_y=0.8, size=4.0, color=INK)
+ scale_fill_manual(values=dict(zip(zones, ZONE_COLORS, strict=True)))
+ scale_alpha_manual(values={"primary": 1.0, "secondary": 0.7})
+ scale_y_continuous(limits=(0, 45), expand=(0, 0), breaks=[0, 10, 20, 30, 40])
+ labs(title=title, caption=caption, x=None, y="Duration (minutes)")
+ theme(
figure_size=(8, 4.5),
text=element_text(size=7),
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
panel_background=element_rect(fill=PAGE_BG),
panel_grid_major_y=element_line(color=GRID, size=0.3),
panel_grid_major_x=element_blank(),
panel_grid_minor=element_blank(),
panel_border=element_blank(),
axis_line_x=element_line(color=INK_SOFT, size=0.5),
axis_line_y=element_blank(),
axis_ticks=element_blank(),
axis_title_x=element_blank(),
axis_title_y=element_text(color=INK, size=10),
axis_text_x=element_text(color=INK_SOFT, size=8),
axis_text_y=element_text(color=INK_SOFT, size=8),
plot_title=element_text(color=INK, size=12, ha="center"),
plot_caption=element_text(color=INK_MUTED, size=8, ha="right"),
legend_position="none",
)
)
plot.save(f"plot-{THEME}.png", dpi=400, width=8, height=4.5, units="in")
Part of Time in Heart Rate Zones Bar Chart on anyplot.ai.