Line Plot with Markers — Seaborn

A line plot with visible markers at each data point, combining line and scatter plot features. This is particularly useful for sparse data where individual observations are significant.

Line Plot with Markers rendered with Seaborn

Python source (Seaborn)

""" anyplot.ai
line-markers: Line Plot with Markers
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 95/100 | Updated: 2026-05-12
"""

import os

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
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"

# Okabe-Ito palette - first series always #009E73
IMPRINT = ["#009E73", "#C475FD", "#4467A3"]

# Data - Stock price tracking with different patterns
np.random.seed(42)
days = np.arange(0, 60)

# Three stocks with distinct patterns:
# Stock A - steady upward trend (growth stock)
stock_a = 100 + 0.5 * days + np.random.normal(0, 1, 60)

# Stock B - high volatility (volatile stock)
stock_b = 95 + np.cumsum(np.random.normal(0, 2, 60))

# Stock C - relatively stable (dividend stock)
stock_c = 110 + 0.1 * days + np.random.normal(0, 0.8, 60)

df = pd.DataFrame(
    {
        "Day": np.tile(days, 3),
        "Price ($)": np.concatenate([stock_a, stock_b, stock_c]),
        "Stock": ["Stock A"] * 60 + ["Stock B"] * 60 + ["Stock C"] * 60,
    }
)

# Set theme-adaptive styling
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,
    },
)

# Plot
fig, ax = plt.subplots(figsize=(16, 9), facecolor=PAGE_BG)

sns.lineplot(
    data=df,
    x="Day",
    y="Price ($)",
    hue="Stock",
    style="Stock",
    markers=True,
    dashes=False,
    markersize=10,
    linewidth=2.5,
    palette=IMPRINT,
    ax=ax,
)

# Styling
ax.set_title("line-markers · seaborn · anyplot.ai", fontsize=24, fontweight="medium")
ax.set_xlabel("Day", fontsize=20, color=INK)
ax.set_ylabel("Price ($)", fontsize=20, color=INK)
ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)

# Remove top and right spines
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["left"].set_color(INK_SOFT)
ax.spines["bottom"].set_color(INK_SOFT)

# Subtle grid on y-axis
ax.yaxis.grid(True, alpha=0.10, linewidth=0.8, color=INK)

# Legend with lower framealpha for visual appeal
ax.legend(fontsize=16, framealpha=0.5, loc="upper left", frameon=True)

plt.tight_layout()
plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)

Part of Line Plot with Markers on anyplot.ai.

Line Plot with Markers — Seaborn

Python source (Seaborn)

Other implementations