Time Series Line Plot — Seaborn

A time series line plot displays data points connected by lines over a datetime x-axis, with smart date formatting that automatically adjusts tick labels based on the time scale (days, months, years). This plot type is essential for temporal data analysis where proper date formatting and readability are critical. Unlike basic line plots, time series plots handle datetime parsing, timezone awareness, and intelligent tick label formatting.

Time Series Line Plot rendered with Seaborn

Python source (Seaborn)

""" anyplot.ai
line-timeseries: Time Series Line Plot
Library: seaborn 0.13.2 | Python 3.13.13
Quality: 88/100 | Updated: 2026-05-09
"""

import os

import matplotlib.dates as mdates
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"
BRAND = "#009E73"  # Okabe-Ito position 1

# Theme-adaptive seaborn configuration
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,
    },
)

# Data: Daily temperature readings over 3 months
np.random.seed(42)
dates = pd.date_range(start="2024-01-01", periods=90, freq="D")

day_of_year = np.arange(90)
base_temp = 5 + 10 * np.sin(2 * np.pi * (day_of_year + 10) / 365)
noise = np.random.randn(90) * 3
temperature = base_temp + noise

df = pd.DataFrame({"Date": dates, "Temperature (°C)": temperature})

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

sns.lineplot(data=df, x="Date", y="Temperature (°C)", color=BRAND, linewidth=3, ax=ax, errorbar=("ci", 95))

# Style
ax.set_xlabel("Date", fontsize=20, color=INK)
ax.set_ylabel("Temperature (°C)", fontsize=20, color=INK)
ax.set_title("line-timeseries · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK)
ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)

# Smart date formatting
ax.xaxis.set_major_locator(mdates.MonthLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %Y"))
ax.xaxis.set_minor_locator(mdates.WeekdayLocator(byweekday=mdates.MO))

# Rotate labels to prevent overlap
plt.setp(ax.get_xticklabels(), rotation=45, ha="right")

# Grid on both axes for readability
ax.grid(True, alpha=0.15, linewidth=0.8, color=INK)

# Remove top and right spines
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
for spine in ["left", "bottom"]:
    ax.spines[spine].set_color(INK_SOFT)

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

Part of Time Series Line Plot on anyplot.ai.

Time Series Line Plot — Seaborn

Python source (Seaborn)

Other implementations