Add Moving Average to Arrow Files Online
Add a moving average, rolling sum, rolling min, or rolling max column to Arrow files directly in your browser. Choose window size, order-by column, and optional partitioning — no upload required.
How to add Moving Average to Arrow files
- Drop your file onto the upload area. It is loaded into the in-browser engine and the first 200 rows are shown.
- Pick a window function: Moving Average (the default), Rolling Sum, Rolling Min or Rolling Max. The output column name changes to match, for example moving_avg or rolling_sum.
- Choose the value column (numeric columns only) and the window size in rows. The default is 3, and the window is the current row plus the rows before it.
- Choose an Order by column, usually a date, and optionally a Partition by column so each group gets its own series. Click Add Rolling Column.
- Check the preview, then download the file in the same format you uploaded.
Your file is processed locally in your browser and is never uploaded. The free limit is 50 MB per file; larger files work if your device has the memory for them.
Worked example
A café tracks cups of coffee sold each day. Daily figures jump around with the weather, so the owner wants a 3-day moving average to see the underlying trend.
Input (Arrow)
Arrow IPC file (binary, columnar) — shown as a table with its schema
| sale_date | weekday | cups_sold |
|---|---|---|
| 2026-05-04 | Mon | 120 |
| 2026-05-05 | Tue | 150 |
| 2026-05-06 | Wed | 90 |
| 2026-05-07 | Thu | 180 |
| 2026-05-08 | Fri | 210 |
| 2026-05-09 | Sat | 150 |
Schema: sale_date DATE, weekday VARCHAR, cups_sold BIGINT
Settings
- Window function: Moving Average
- Value column: cups_sold
- Window size: 3 rows
- Order by: sale_date
- Partition by: (none)
- Output column name: moving_avg
Result
| sale_date | weekday | cups_sold | moving_avg |
|---|---|---|---|
| 2026-05-04 | Mon | 120 | 120 |
| 2026-05-05 | Tue | 150 | 135 |
| 2026-05-06 | Wed | 90 | 120 |
| 2026-05-07 | Thu | 180 | 140 |
| 2026-05-08 | Fri | 210 | 160 |
| 2026-05-09 | Sat | 150 | 180 |
From Wednesday on, each value averages that day and the two before it: Thursday is (150 + 90 + 180) / 3 = 140. Monday and Tuesday do not have two earlier rows, so they average what is available: 120 alone, then (120 + 150) / 2 = 135. They are not left empty. Wednesday's dip is smoothed to 120, and the upward trend from Thursday is easy to see.
Frequently Asked Questions
How are the first rows handled when the window is not full yet?
They use whatever rows are available. With a window of 7, row 1 averages 1 value, row 2 averages 2, and from row 7 on every value covers 7 rows. No row is left empty for this reason.
Is the window centred or trailing?
Trailing. It covers the current row and the rows before it, up to the window size. Centred windows and exponential moving averages are not offered. Use the SQL Query tool with a custom window frame for those.
What is the difference between the four window functions?
Moving Average gives the mean of the window, Rolling Sum the total, and Rolling Min and Rolling Max the smallest and largest values. All four use the same window size, order and partition settings.
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