What data formats are supported?

You can upload CSV, JSON, or Excel files, or paste raw CSV/JSON text directly into the input field.

What is the difference between Z-Score and IQR?

Z-Score measures how many standard deviations a data point is from the mean, which is great for normally distributed data. IQR uses quartiles to find outliers and is more robust against extreme values.

How does the seasonality window work?

The seasonality window allows the tool to account for recurring patterns over a specified number of periods, helping to separate normal seasonal fluctuations from true anomalies.

Can I customize the sensitivity of the detection?

Yes, you can adjust the Z-Score threshold between 1 and 6. A lower threshold flags more points as anomalies, while a higher threshold only flags extreme outliers.

What does the output report include?

The tool generates an HTML report containing a visual chart of your time series, highlighted anomaly markers, trend slopes, and a summary of contiguous anomaly segments.

Time Series Anomaly Detector | Online Free Tool

Examples

1. Flagging a Suspicious Revenue Spike

E-commerce Analyst

Background

An analyst is reviewing daily revenue data and notices an unusually high total for a specific week.

Problem

Needs to mathematically confirm which specific day is a statistical outlier compared to the rest of the week.

How to use

Paste the daily revenue CSV data, set the timestamp and value columns, and select 'Z-Score + IQR' as the detection method.

Detection Method: Z-Score + IQR, Z-Score Threshold: 2.5, Seasonality Window: 0

Outcome

The tool generates a chart highlighting the exact day the revenue spiked to 315, confirming it as a statistical anomaly.

2. Reviewing Server Latency Drift

DevOps Engineer

Background

A DevOps engineer is investigating intermittent slow response times on a web server.

Problem

Needs to separate ordinary traffic fluctuations from actual latency incidents using hourly monitoring data.

How to use

Upload the server latency logs, select the Z-Score method, and apply a seasonality window to account for normal traffic patterns.

Detection Method: Z-Score, Z-Score Threshold: 2, Seasonality Window: 3

Time Series Anomaly Detector | Online Free Tool | Elysia Tools

Time Series Anomaly Detector

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Examples

1. Flagging a Suspicious Revenue Spike

2. Reviewing Server Latency Drift

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