(DEPRECATED) Returns a function that multiplies each timestamp of a single time series by the specified integer factor.
For a source time series with points (timestamp, value)
, upon scaling by factor
,
the resulting time-scaled time series will have points (timestamp * factor, value)
.
FunctionNode
) -> FunctionNode
Column name | Type | Description |
---|---|---|
timestamp | pandas.Timestamp | Timestamp of the point |
value | float | Scaled value of the point |
This operation is deprecated and performs a no-op, leaving the resulting time series unchanged. This function will be removed from future releases.
The backend will automatically unify different time-units to the same unit.
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>>> series = F.points( ... (1, 1.0), ... (101, 2.0), ... (200, 4.0), ... (201, 8.0), ... name="series", ... ) >>> series.to_pandas() timestamp value 0 1970-01-01 00:00:00.000000001 1.0 1 1970-01-01 00:00:00.000000101 2.0 2 1970-01-01 00:00:00.000000200 4.0 3 1970-01-01 00:00:00.000000201 8.0
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>>> timescaled_series = F.timestamp_scale(99)(series) # NO-OP, DEPRECATED OPERATION >>> timescaled_series.to_pandas() # resulting series is unchanged timestamp value 0 1970-01-01 00:00:00.000000001 1.0 1 1970-01-01 00:00:00.000000101 2.0 2 1970-01-01 00:00:00.000000200 4.0 3 1970-01-01 00:00:00.000000201 8.0