A line plot with annotations at key points marking important events or milestones. This visualization enhances time series data by highlighting significant occurrences such as product launches, policy changes, or market events directly on the chart. Vertical lines, markers, and text labels draw attention to specific moments in time, making it easy to correlate data trends with real-world events.
""" anyplot.ai
line-annotated-events: Annotated Line Plot with Event Markers
Library: letsplot 4.9.0 | Python 3.13.13
Quality: 89/100 | Updated: 2026-05-16
"""
import numpy as np
import pandas as pd
from lets_plot import *
LetsPlot.setup_html()
# Data - Daily product metrics with feature launch events
np.random.seed(42)
dates = pd.date_range("2024-01-01", periods=365, freq="D")
# Create realistic user growth pattern with trend and seasonality
trend = np.linspace(1000, 5000, 365)
seasonality = 300 * np.sin(np.arange(365) * 2 * np.pi / 30)
noise = np.random.normal(0, 150, 365)
daily_users = trend + seasonality + noise
# Create jumps at event dates to show impact
daily_users[45:] += 400 # After Feature A launch
daily_users[120:] += 600 # After Feature B launch
daily_users[200:] += 800 # After Mobile App launch
daily_users[280:] += 500 # After API release
daily_users[330:] += 300 # After Integration launch
df = pd.DataFrame({"date": dates, "users": daily_users})
# Convert date to numeric for plotting
df["date_num"] = (df["date"] - df["date"].min()).dt.days
# Event data - Feature launches throughout the year
events = pd.DataFrame(
{
"event_date": pd.to_datetime(["2024-02-15", "2024-05-01", "2024-07-20", "2024-10-07", "2024-11-20"]),
"event_label": ["Feature A", "Feature B", "Mobile App", "API v2.0", "Partners"],
"y_offset": [4800, 5200, 5600, 6000, 6400], # Alternating heights to avoid overlap
}
)
events["event_num"] = (events["event_date"] - df["date"].min()).dt.days
# Create the plot
plot = (
ggplot()
# Main line - daily active users
+ geom_line(aes(x="date_num", y="users"), data=df, color="#306998", size=1.5, alpha=0.9)
# Vertical lines for events
+ geom_vline(aes(xintercept="event_num"), data=events, color="#DC2626", linetype="dashed", size=1.0, alpha=0.7)
# Event markers at the line
+ geom_point(aes(x="event_num", y="y_offset"), data=events, color="#DC2626", size=5, shape=18)
# Event labels
+ geom_text(
aes(x="event_num", y="y_offset", label="event_label"),
data=events,
color="#333333",
size=14,
hjust=0,
nudge_x=5,
fontface="bold",
)
# Labels and title
+ labs(x="Day of Year 2024", y="Daily Active Users", title="line-annotated-events · letsplot · pyplots.ai")
# Styling
+ theme_minimal()
+ theme(
plot_title=element_text(size=24, face="bold"),
axis_title=element_text(size=20),
axis_text=element_text(size=16),
panel_grid_major=element_line(color="#CCCCCC", size=0.5),
panel_grid_minor=element_blank(),
)
# Set axis limits to show all data and labels
+ scale_x_continuous(
breaks=[0, 60, 120, 180, 240, 300, 360], labels=["Jan", "Mar", "May", "Jul", "Sep", "Nov", "Jan"]
)
+ scale_y_continuous(limits=[0, 7500])
# Figure size (scaled 3x on export = 4800 × 2700 px)
+ ggsize(1600, 900)
)
# Save as PNG and HTML
ggsave(plot, "plot.png", scale=3)
ggsave(plot, "plot.html")
Part of Annotated Line Plot with Event Markers on anyplot.ai.