Add a five-year trailing mean without hiding annual temperatures

Compute each trailing mean from the current year and previous four annual observations.

Add a five-year trailing mean without hiding annual temperatures. Explore the public-data example; methods and data notes are below.
Explore the public-data example; methods and data notes are below.Download chart SVG

The direct answer

Compute each trailing mean from the current year and previous four annual observations. Keep the annual series beside it so the reader can see variability that smoothing removes. The first four years have no full five-year window.

Prepare the observation table

Use complete NASA annual values through 2023 and calculate the mean before import. Leave the first four rolling cells blank. Map year to X and anomaly_c plus trailing_5y_c to Y. Label the line as trailing, rather than centered, and keep both series in the same units.

Public dataset and a reproducible example

The download is a prepared extract, not a live data connection. The source links below include the original query, observation period and reuse policy. Keep an original copy when you update the data; revised source values can change the result.

NASA GISTEMP v4 Land–Ocean Temperature Index, complete annual J-D values through 2023, in °C relative to 1951–1980. The CSV description row was removed; no baseline conversion was applied. Cite GISTEMP Team and the source link.

Snapshot retrieved: 2026-10-26. Prepared rows: 144.

Download the prepared CSVDownload the reference SVG

First five rows from the prepared public-data extract; blank cells remain missing.
yearanomaly_ctrailing_5y_c
1880-0.17Missing
1881-0.09Missing
1882-0.11Missing
1883-0.18Missing
1884-0.28-0.166

Build it in Datamon

Sign in with Google to create an editable visualization. Public articles and examples can be read without an account. The prepared CSV already contains the joins, filters or aggregations described above; do those steps in a spreadsheet first when using your own data.

  1. Open Data and choose a file, or paste the table with its header row. Check the detected numeric columns, decimal separator and dates. The current importer accepts files below 20 MB; these examples are smaller. Keep blanks distinct from recorded zeros.
  2. In Visualize, select Line chart. Connect the roles exactly as listed below. Review the preview against at least two rows in the example table rather than relying only on automatic mapping.
  3. In Refine, add a title that states the question, the unit, observation period and source. Check labels and contrast at the size your reader will see. Keep a table when exact values matter.
  4. Use the export controls for SVG, PNG, PDF or PowerPoint, then inspect the actual file. Save an editable project backup. Publish only after checking the underlying values: a public link makes the published data available to anyone possessing the URL.

Calculation and column mapping

The rule below is pseudocode. The downloadable CSV already contains the prepared values; spreadsheet functions and cell references depend on your sheet layout.

trailing_5y_c[t] = MEAN(anomaly_c[t-4:t]); first four windows remain blank
X
year
Y
anomaly_c, trailing_5y_c

Read the result

In this extract, anomaly_c ranges from -0.48 (1909) to 1.17 (2023).

Use the preview to check the structure and the CSV to check exact values. Its styling is a reference; your Datamon rendering can look different. Follow the mapping and preparation above to reproduce the analytical meaning.

Mistakes that change the meaning

A trailing mean lags turning points and describes the past. It is not a forecast or a statistical confidence interval. Do not fill its first four cells with shorter-window means while labeling every point as a five-year calculation.

Questions before sharing

Do these calculations require an AI service?

No. The prepared CSV and reference calculation are deterministic. Optional AI can help draft an explanation when configured, but it does not replace checking source values or choosing a valid comparison.

Can I use this example with my own spreadsheet?

Yes. Keep the same observation unit, column types and calculation. Replace the source attribution and time period, recompute derived columns, then compare several output values with your original sheet before sharing.

What is free and what needs an account?

Reading this guide and downloading its CSV and chart images are free. Datamon currently has no paid checkout or subscription plans in this deployment. Creating and saving an editable visualization requires Google sign-in. Provider-backed AI, cloud analysis, publishing and video depend on configured services; this guide does not promise unlimited free connected services.

Sources and further reading

Report a correction or an access barrier: Email the editorial contact.

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