A sparkline is a small, condensed line chart designed to be embedded inline with text or in dashboard cells. It shows trends at a glance without axes, labels, or detailed scales - pure data visualization in minimal space. The defining characteristic is extreme minimalism: a single continuous line that conveys the shape of data without any chart chrome.
""" anyplot.ai
sparkline-basic: Basic Sparkline
Library: matplotlib 3.11.0 | Python 3.13.13
Quality: 91/100 | Updated: 2026-06-16
"""
import os
import matplotlib.pyplot as plt
import numpy as np
# Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome")
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"
# Imprint palette — single hue for every sparkline (one metric "family")
BRAND = "#009E73" # Imprint position 1 — the line, ALWAYS first series
LOW = "#AE3030" # Imprint position 5 — marks each series minimum
HIGH = "#4467A3" # Imprint position 3 — marks each series maximum
# Data — a KPI dashboard of small-multiple sparklines (60-day trends).
# Sparklines shine as small multiples in table/dashboard cells (see spec
# "Applications"): each row is one metric, drawn axis-free and compact.
np.random.seed(42)
n_points = 60
x = np.arange(n_points)
# Each metric: a distinct trend shape, its current-value format, and unit.
visitors = 1200 + 16 * x + 130 * np.sin(x / 3.0) + np.random.randn(n_points) * 55
revenue = 38 + 0.55 * x + 6 * np.sin(x / 5.0 + 1) + np.random.randn(n_points) * 2.2
conversion = 2.0 + 1.4 * (x / n_points) ** 1.5 + np.random.randn(n_points) * 0.12
active = 1500 - 9 * x + 180 * np.sin(x / 4.0) + np.random.randn(n_points) * 70
session = 4.6 + 1.2 * np.sin(x / 8.0) + np.random.randn(n_points) * 0.25
signups = 30 + 80 * (x / n_points) ** 2 + 14 * np.sin(x / 2.5) + np.random.randn(n_points) * 6
metrics = [
("Website Visitors", visitors, "{:,.0f}"),
("Daily Revenue", revenue, "${:.1f}k"),
("Conversion Rate", conversion, "{:.2f}%"),
("Active Users", active, "{:,.0f}"),
("Avg. Session", session, "{:.1f} min"),
("Newsletter Signups", signups, "{:,.0f}"),
]
# Plot — one slim, chrome-free axes per metric, stacked vertically
fig, axes = plt.subplots(len(metrics), 1, figsize=(8, 4.5), dpi=400, facecolor=PAGE_BG)
fig.subplots_adjust(left=0.20, right=0.86, top=0.86, bottom=0.05, hspace=0.7)
for ax, (name, values, fmt) in zip(axes, metrics, strict=True):
ax.set_facecolor(PAGE_BG)
# Thin line + faint area fill — the defining sparkline look
ax.plot(x, values, color=BRAND, linewidth=1.6, solid_capstyle="round")
ax.fill_between(x, values, values.min(), color=BRAND, alpha=0.10)
# Highlight the extremes and the latest point
i_min, i_max = int(values.argmin()), int(values.argmax())
ax.scatter(i_min, values[i_min], s=22, color=LOW, zorder=5)
ax.scatter(i_max, values[i_max], s=22, color=HIGH, zorder=5)
ax.scatter(x[-1], values[-1], s=28, color=BRAND, zorder=6)
# Strip all chart chrome — pure sparkline
ax.set_xticks([])
ax.set_yticks([])
for spine in ax.spines.values():
spine.set_visible(False)
# Breathing room so the line never touches the cell edges
pad = (values.max() - values.min()) * 0.28
ax.set_ylim(values.min() - pad, values.max() + pad)
ax.set_xlim(-1.5, n_points + 0.5)
# Metric name (left) and current value (right), table-cell style
ax.text(-0.025, 0.5, name, transform=ax.transAxes, ha="right", va="center", fontsize=9, color=INK_SOFT)
ax.text(
1.02,
0.5,
fmt.format(values[-1]),
transform=ax.transAxes,
ha="left",
va="center",
fontsize=10,
fontweight="medium",
color=INK,
)
# Title (mandated format)
fig.suptitle("sparkline-basic · python · matplotlib · anyplot.ai", fontsize=13, fontweight="medium", color=INK, y=0.96)
# Save (figsize 8x4.5 @ dpi 400 → 3200x1800; no bbox_inches — see library prompt)
plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)
Part of Basic Sparkline on anyplot.ai.