ClickHouse/docs/en/sql-reference/window-functions/lagInFrame.md

slug	sidebar_label	sidebar_position
/en/sql-reference/window-functions/lagInFrame	lagInFrame	9

lagInFrame

Returns a value evaluated at the row that is at a specified physical offset row before the current row within the ordered frame.

Syntax

lagInFrame(x[, offset[, default]])
  OVER ([[PARTITION BY grouping_column] [ORDER BY sorting_column] 
        [ROWS or RANGE expression_to_bound_rows_withing_the_group]] | [window_name])
FROM table_name
WINDOW window_name as ([[PARTITION BY grouping_column] [ORDER BY sorting_column])

For more detail on window function syntax see: Window Functions - Syntax.

Parameters

• x — Column name.
• offset — Offset to apply. (U)Int*. (Optional - 1 by default).
• default — Value to return if calculated row exceeds the boundaries of the window frame. (Optional - default value of column type when omitted).

Returned value

• Value evaluated at the row that is at a specified physical offset before the current row within the ordered frame.

Example

This example looks at historical data for a specific stock and uses the lagInFrame function to calculate a day-to-day delta and percentage change in the closing price of the stock.

Query:

CREATE TABLE stock_prices
(
    `date`   Date,
    `open`   Float32, -- opening price
    `high`   Float32, -- daily high
    `low`    Float32, -- daily low
    `close`  Float32, -- closing price
    `volume` UInt32   -- trade volume
)
Engine = Memory;

INSERT INTO stock_prices FORMAT Values
    ('2024-06-03', 113.62, 115.00, 112.00, 115.00, 438392000),
    ('2024-06-04', 115.72, 116.60, 114.04, 116.44, 403324000),
    ('2024-06-05', 118.37, 122.45, 117.47, 122.44, 528402000),
    ('2024-06-06', 124.05, 125.59, 118.32, 121.00, 664696000),
    ('2024-06-07', 119.77, 121.69, 118.02, 120.89, 412386000);

SELECT
    date,
    close,
    lagInFrame(close, 1, close) OVER (ORDER BY date ASC) AS previous_day_close,
    COALESCE(ROUND(close - previous_day_close, 2)) AS delta,
    COALESCE(ROUND((delta / previous_day_close) * 100, 2)) AS percent_change
FROM stock_prices
ORDER BY date DESC;

Result:

   ┌───────date─┬──close─┬─previous_day_close─┬─delta─┬─percent_change─┐
1. │ 2024-06-07 │ 120.89 │                121 │ -0.11 │          -0.09 │
2. │ 2024-06-06 │    121 │             122.44 │ -1.44 │          -1.18 │
3. │ 2024-06-05 │ 122.44 │             116.44 │     6 │           5.15 │
4. │ 2024-06-04 │ 116.44 │                115 │  1.44 │           1.25 │
5. │ 2024-06-03 │    115 │                115 │     0 │              0 │
   └────────────┴────────┴────────────────────┴───────┴────────────────┘