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Sliding Slope

Calculates the linear slope on a given row, looking backwards for a user-defined window of periods.

Pass in a partition_col, an order_col, and a lookback window size.

NOTE: Your data should be a properly formatted timeseries dataset before applying this transformation. In other words, each period should only appear once, and periods considered zero should be imputed with 0 already. NOTE: Slope calculations are notoriously sensitive to large outliers, especially with smaller windows.

Example use case: On daily stock data, calculate SLOPE by TICKER, with a 14-period lookback window.

Parameters

Name
Type
Description
Is Optional

partition_col

column

Grouping column to calculate the slope within.

order_col

column

Column to order rows by when calculating the agg window. Slope automatically sorts ascending.

value_col

column

Column to calulate slope for.

window

int

Number of periods to use as a lookback period, to calculate slope.

Example

ds = rasgo.get.dataset(fqtn="RASGOCOMMUNITY.PUBLIC.ZEPL_DAILY_STOCK_FEATURES")

ds2 = ds.sliding_slope(partition_col = 'TICKER', 
              order_col = 'DATE', 
              value_col = 'CLOSE', 
              window = 14)

Source Code

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