A bullet chart displays a single measure against qualitative ranges and a target marker, designed by Stephen Few as a space-efficient alternative to gauge charts. The linear format shows actual performance as a bar, a target as a vertical marker, and background bands representing qualitative ranges (poor/satisfactory/good). Its compact design allows multiple bullet charts to fit on a single dashboard for easy comparison across metrics.
""" anyplot.ai
bullet-basic: Basic Bullet Chart
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 89/100 | Updated: 2026-05-29
"""
import os
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import seaborn as sns
# Theme tokens
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 palette — semantic exception: green = on-track (pass), red = below-target (fail)
ON_TRACK_COLOR = "#009E73" # Imprint position 1 — green maps to success/pass
BELOW_TARGET_COLOR = "#AE3030" # Imprint position 5 — matte red for fail/loss
# Grayscale range bands (theme-adaptive) — spec recommends grayscale to focus attention on bars
if THEME == "light":
BAND_GOOD = "#CECDC7"
BAND_SATISFACTORY = "#AEADA6"
BAND_POOR = "#888780"
else:
BAND_GOOD = "#525250"
BAND_SATISFACTORY = "#3D3D3B"
BAND_POOR = "#353532" # lightened for better dark-mode band differentiation
# Data — department KPI dashboard with varied performance scenarios
metrics = ["Revenue", "Customer\nSatisfaction", "Efficiency", "Quality\nScore"]
actuals = [78, 85, 35, 91]
targets = [90, 80, 75, 85]
ranges_list = [
[50, 75, 100], # Revenue
[60, 80, 100], # Customer Satisfaction
[40, 60, 100], # Efficiency
[70, 85, 100], # Quality Score
]
status = ["On Track" if a >= t else "Below Target" for a, t in zip(actuals, targets, strict=True)]
status_palette = {"On Track": ON_TRACK_COLOR, "Below Target": BELOW_TARGET_COLOR}
# Configure seaborn theme with theme-adaptive chrome
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": 0.15,
"legend.facecolor": ELEVATED_BG,
"legend.edgecolor": INK_SOFT,
},
)
fig, ax = plt.subplots(figsize=(8, 4.5), dpi=400, facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)
n_metrics = len(metrics)
range_height = 0.65
band_colors = [BAND_POOR, BAND_SATISFACTORY, BAND_GOOD]
# Qualitative range bands via ax.barh for reliable left-offset positioning
for i, ranges in enumerate(ranges_list):
prev = 0
for end, color in zip(ranges, band_colors, strict=True):
ax.barh(i, end - prev, left=prev, height=range_height, color=color, edgecolor="none", zorder=1)
prev = end
# Actual value bars — seaborn-native barplot, narrower than background bands
n_patches_before = len(ax.patches)
sns.barplot(
y=list(range(n_metrics)),
x=actuals,
hue=status,
palette=status_palette,
width=0.28,
orient="h",
ax=ax,
native_scale=True,
dodge=False,
errorbar=None,
saturation=1.0,
legend=False,
)
for patch in ax.patches[n_patches_before:]:
patch.set_zorder(3)
patch.set_edgecolor(PAGE_BG)
patch.set_linewidth(0.8)
# Target markers — thin vertical line spanning the full range-band height
for i, target in enumerate(targets):
ax.plot(
[target, target],
[i - range_height / 2 + 0.01, i + range_height / 2 - 0.01],
color=INK,
linewidth=2.5,
zorder=4,
solid_capstyle="butt",
)
# Value labels — positioned just past the actual bar, colored by status
for i, (actual, s) in enumerate(zip(actuals, status, strict=True)):
ax.text(
actual + 1.5, i, f"{actual}%", va="center", ha="left", fontsize=8, fontweight="bold", color=status_palette[s]
)
# Axes — title length 44 chars, ratio=1.0, title_fontsize=12
title = "bullet-basic · python · seaborn · anyplot.ai"
ax.set_xlim(0, 115)
ax.set_ylim(-0.55, n_metrics - 0.45)
ax.set_xlabel("Performance (%)", fontsize=10, color=INK)
ax.set_ylabel("")
ax.set_title(title, fontsize=12, fontweight="medium", color=INK, pad=12)
ax.set_yticks(range(n_metrics))
yticklabels = ax.set_yticklabels(metrics, fontsize=8, color=INK_SOFT)
for i, lbl in enumerate(yticklabels):
if i == 2: # Efficiency — most dramatic underperformance (35% vs 75% target)
lbl.set_fontweight("bold")
lbl.set_color(BELOW_TARGET_COLOR)
ax.tick_params(axis="y", length=0)
ax.tick_params(axis="x", labelsize=8)
sns.despine(left=True, top=True, right=True, ax=ax)
ax.xaxis.grid(True, alpha=0.15, linewidth=0.8, color=INK, zorder=2)
ax.yaxis.grid(False)
# Legend
legend_elements = [
mpatches.Patch(facecolor=BAND_POOR, label="Poor", edgecolor="none"),
mpatches.Patch(facecolor=BAND_SATISFACTORY, label="Satisfactory", edgecolor="none"),
mpatches.Patch(facecolor=BAND_GOOD, label="Good", edgecolor="none"),
mpatches.Patch(facecolor=ON_TRACK_COLOR, label="On Track", edgecolor=PAGE_BG, linewidth=0.8),
mpatches.Patch(facecolor=BELOW_TARGET_COLOR, label="Below Target", edgecolor=PAGE_BG, linewidth=0.8),
plt.Line2D([0], [0], color=INK, linewidth=2.5, label="Target"),
]
ax.legend(
handles=legend_elements, loc="lower right", fontsize=8, framealpha=0.9, facecolor=ELEVATED_BG, edgecolor=INK_SOFT
)
plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)
Part of Basic Bullet Chart on anyplot.ai.