|
| 1 | +--- |
| 2 | +sheet: Sheet |
| 3 | +--- |
| 4 | +# Create a window over consecutive rows |
| 5 | + |
| 6 | +Window functions enable computations that relate the current window to surrounding rows, like cumulative sum, rolling averages or lead/lag computations. |
| 7 | + |
| 8 | +{help.commands.addcol-window} |
| 9 | + |
| 10 | +With large window sizes, [:code]g'[/] (`freeze-sheet`) to calculate all cells and copy the entire sheet into a new source sheet, which will conserve CPU. |
| 11 | + |
| 12 | +## Examples |
| 13 | + |
| 14 | + date color price |
| 15 | + ---------- ----- ----- |
| 16 | + 2024-09-01 R 30 |
| 17 | + 2024-09-02 B 28 |
| 18 | + 2024-09-03 R 100 |
| 19 | + 2024-09-03 B 33 |
| 20 | + 2024-09-03 B 99 |
| 21 | + |
| 22 | + |
| 23 | +1. [:keys]#[/] (`type-int`) on the **price** column to type as int. |
| 24 | +2. [:keys]w[/] (`addcol-window`) on the **price** column, followed by `1 2`, to create a window consisting of 4 rows: 1 row before the current row, and 2 rows after. |
| 25 | +3. To create a moving average of the values in the window, add a new column with a python expression: [:keys]=[/] (`addcol-expr`) |
| 26 | +followed by `sum(price_window)/len(price_window)` |
| 27 | + |
| 28 | +date color price price_window sum(price_window)/len(price_window) |
| 29 | +---------- ----- ----- ------------------- ----------------------------------- |
| 30 | +2024-09-01 R 38 [4] ; 38; 28; 100 41.5 |
| 31 | +2024-09-02 B 28 [4] 38; 28; 100; 33 49.75 |
| 32 | +2024-09-03 R 100 [4] 28; 100; 33; 99 65.0 |
| 33 | +2024-09-03 B 33 [4] 100; 33; 99; 58.0 |
| 34 | +2024-09-03 B 99 [4] 33; 99; ; 33.0 |
| 35 | + |
| 36 | + |
| 37 | +## Workflows |
| 38 | + |
| 39 | +### Create a cumulative sum |
| 40 | + |
| 41 | +1. Set the before window size to the total number of rows in the table, and the after rows to 0. In the above example that would be `w 5 0` (`addcol-window`). |
| 42 | +2. Add an expression ([:keys]=[/] (`addcol-expr`) of `sum(window)` where `window` is the name of the window function column. |
| 43 | + |
| 44 | +### Compute the change between rows |
| 45 | + |
| 46 | +1. `w 1 0` on the `foo` column to create a window function of size 1 before and 0 after. |
| 47 | +2. Add a python expression. The window function column is 'foo_window': |
| 48 | + `=foo_window[1] - foo_window[0] if len(foo_window) > 1 else None` |
| 49 | + |
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