Gauge Chart

Customer NPS Score

Net Promoter Score with lime green satisfaction indicator

Output
Customer NPS Score
Python
import matplotlib.pyplot as plt
from matplotlib.patches import Wedge, Circle, Polygon
import numpy as np

# Data
nps = 78
max_value = 100

# Colors
bg_color = '#0a0a0f'
track_color = '#1a1a2e'
arc_color = '#6CF527'
text_color = '#ffffff'
dim_color = '#6b7280'

start_angle, end_angle = -30, 210
sweep = end_angle - start_angle

fig, ax = plt.subplots(figsize=(10, 8), facecolor=bg_color)
ax.set_facecolor(bg_color)
ax.set_xlim(-1.4, 1.4)
ax.set_ylim(-0.5, 1.4)
ax.set_aspect('equal')
ax.axis('off')

# Track with sentiment zones
zones = [(0, 30, '#F54927', 'Detractors'), (30, 70, '#F5B027', 'Passives'), (70, 100, '#6CF527', 'Promoters')]
for z_start, z_end, z_color, _ in zones:
    z_s_ang = end_angle - (z_start / 100) * sweep
    z_e_ang = end_angle - (z_end / 100) * sweep
    ax.add_patch(Wedge((0, 0), 1.0, z_e_ang, z_s_ang, width=0.15,
                       facecolor=z_color, edgecolor='none', alpha=0.15))

# Value arc
value_pct = nps / 100
value_angle = start_angle + (1 - value_pct) * sweep
for r_off, w_off, alpha in [(0.05, 0.06, 0.1), (0.03, 0.04, 0.2), 
                             (0.015, 0.02, 0.4), (0, 0, 0.95)]:
    ax.add_patch(Wedge((0, 0), 1.0 + r_off, value_angle, end_angle,
                       width=0.15 + w_off, facecolor=arc_color, edgecolor='none', alpha=alpha))

# Ticks
for i in range(11):
    pct = i / 10
    angle = np.radians(end_angle - pct * sweep)
    r1, r2 = (0.87, 0.80) if i % 5 == 0 else (0.87, 0.83)
    ax.plot([r1*np.cos(angle), r2*np.cos(angle)], 
            [r1*np.sin(angle), r2*np.sin(angle)], color='#3a3a4a', linewidth=2 if i%5==0 else 1)
    if i % 5 == 0:
        ax.text(0.72*np.cos(angle), 0.72*np.sin(angle), f'{int(pct*100)}',
                fontsize=11, color=dim_color, ha='center', va='center')

# Needle
needle_angle = np.radians(end_angle - value_pct * sweep)
nx, ny = 0.62 * np.cos(needle_angle), 0.62 * np.sin(needle_angle)
perp = needle_angle + np.pi/2
bx1, by1 = 0.035 * np.cos(perp), 0.035 * np.sin(perp)

for scale, alpha in [(1.6, 0.1), (1.3, 0.2)]:
    ax.add_patch(Polygon([(nx*scale, ny*scale), (bx1*2, by1*2), (-bx1*2, -by1*2)],
                         facecolor=arc_color, edgecolor='none', alpha=alpha))
ax.add_patch(Polygon([(nx, ny), (bx1, by1), (-bx1, -by1)], facecolor='#ffffff', edgecolor='none'))

# Hub
for r, c, a in [(0.11, arc_color, 0.3), (0.09, arc_color, 0.5), (0.07, bg_color, 1), (0.05, arc_color, 0.9)]:
    ax.add_patch(Circle((0, 0), r, facecolor=c, edgecolor='none', alpha=a))

# Text
ax.text(0, -0.22, f'{nps}', fontsize=56, fontweight='bold', color=text_color, ha='center', va='center')
ax.text(0, -0.40, 'NPS SCORE', fontsize=14, color=dim_color, ha='center', va='center', fontweight='500')
sentiment = 'EXCELLENT' if nps >= 70 else 'GOOD' if nps >= 50 else 'NEEDS WORK'
ax.text(0, -0.56, sentiment, fontsize=13, color=arc_color, ha='center', va='center', fontweight='bold')
ax.text(0, 1.22, 'Customer Satisfaction', fontsize=18, fontweight='bold', color=text_color, ha='center', va='center')

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Part-to-Whole

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