Time Series Line Plot — plotnine

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 plotnine

Python source (plotnine)

""" anyplot.ai
line-timeseries: Time Series Line Plot
Library: plotnine 0.15.4 | Python 3.13.13
Quality: 92/100 | Updated: 2026-05-09
"""

import os

import numpy as np
import pandas as pd
from mizani.breaks import breaks_date
from mizani.labels import label_date
from plotnine import (
    aes,
    element_line,
    element_rect,
    element_text,
    geom_line,
    geom_point,
    ggplot,
    labs,
    scale_x_datetime,
    theme,
    theme_minimal,
)


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"

# Data: Bitcoin prices over one year with explicit trend and volatility
np.random.seed(42)
dates = pd.date_range(start="2023-01-01", periods=365, freq="D")
price = 16500.0
prices = []
for i in range(365):
    # Trend component: upward over the year, with mid-year dip
    trend = 20000 + 15000 * np.sin(i / 365 * np.pi * 2) + i * 5
    # Volatility: crypto is more volatile than stocks
    volatility = price * (1 + np.random.randn() * 0.035)
    # Mix trend and volatility
    price = 0.7 * trend + 0.3 * volatility
    prices.append(price)

df = pd.DataFrame({"date": dates, "price": prices})

# Plot
plot = (
    ggplot(df, aes(x="date", y="price"))
    + geom_line(color=BRAND, size=1.5, alpha=0.9)
    + geom_point(color=BRAND, size=0.8, alpha=0.5)
    + scale_x_datetime(breaks=breaks_date(30), labels=label_date("%b"))
    + labs(title="line-timeseries · plotnine · anyplot.ai", x="Date", y="Bitcoin Price (USD)")
    + theme_minimal()
    + theme(
        figure_size=(16, 9),
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_grid_major=element_line(color=INK, size=0.3, alpha=0.10),
        panel_grid_minor=element_line(color=INK, size=0.2, alpha=0.05),
        panel_border=element_rect(color=INK_SOFT, fill=None),
        text=element_text(size=14, color=INK),
        axis_title=element_text(size=20, color=INK),
        axis_text=element_text(size=16, color=INK_SOFT),
        axis_text_x=element_text(angle=45, hjust=1),
        plot_title=element_text(size=24, color=INK),
    )
)

# Save
plot.save(f"plot-{THEME}.png", dpi=300)

Part of Time Series Line Plot on anyplot.ai.

Time Series Line Plot — plotnine

Python source (plotnine)

Other implementations