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
RasgoTransforms/sliding_slope.sql at main · rasgointelligence/RasgoTransforms
GitHub

Name	Type	Description
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.

Select

Standard Scaler

Last modified 7mo ago