Time Series Graph - Definition, Examples, and Best Practices

What is a time series graph?

A time series graph plots data points at successive, equally spaced time intervals. The x-axis always represents time - hours, days, weeks, months, quarters, or years. The y-axis shows the measured variable. While a standard line graph can plot any two variables against each other, a time series graph is specifically designed for temporal data, making it the default choice for tracking anything that changes over time.

Time series graphs are optimized for revealing three patterns: trends (long-term direction), seasonality (repeating cycles), and anomalies (unexpected spikes or drops).

When to use a time series graph

Any time your data has a timestamp and you want to understand how a metric evolves. Typical use cases:

• Financial reporting - tracking revenue, costs, or margin over months or quarters. The backbone of most FP&A dashboards
• Operational monitoring - visualizing daily order volume, response times, or system uptime to catch anomalies early
• Marketing performance - plotting website traffic, conversion rates, or ad spend over time to evaluate campaign effectiveness
• Forecasting - overlaying historical actuals with projected values to show whether current trajectory aligns with targets
• Seasonal analysis - identifying recurring patterns (holiday sales peaks, end-of-quarter spikes) that inform planning

Time series graph vs line graph

Every time series graph is a line graph, but not every line graph is a time series graph. The distinction matters because time series data comes with specific considerations - consistent intervals, seasonality, and trend decomposition - that don't apply to a generic line graph plotting two unrelated variables.

Best practices

• Keep time intervals consistent. If you're plotting monthly data, every month should be equally spaced on the x-axis. Mixing intervals (monthly for some periods, quarterly for others) distorts the visual trend
• Mark important events directly on the chart. If revenue dipped in March because of a pricing change, annotate it. Context transforms a chart from data display into a narrative
• Use reference lines for targets, budgets, or prior year comparisons. A horizontal target line or a faded "last year" series gives the reader a benchmark
• Be careful with very long time horizons. A chart showing daily data over five years will have too many points to read. Aggregate to weekly or monthly where appropriate
• For multiple series, keep the number manageable (3-4 maximum) and use distinct colors. Highlight the most important series and mute secondary ones