Returns a function that computes the sum of all points sharing a timestamp for multiple input time series.
The resulting time series is a union of all timestamps for all the input series, where each timestamp contains the sum of values that exist across the input set for that timestamp.
Column name | Type | Description |
---|---|---|
timestamp | pandas.Timestamp | Timestamp of the point |
value | float | Value of the point |
This function is only applicable to numeric series.
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>>> series_1 = F.points( ... (0, 0.0), ... (100, 100.0), ... (140, 140.0), ... (200, 200.0), ... name="series-1" ... ) >>> series_2 = F.points( ... (100, 200.0), ... (120, 220.0), ... (130, 330.0), ... (150, 350.0), ... (160, 460.0), ... name="series-2" ... ) >>> series_1.to_pandas() timestamp value 0 1970-01-01 00:00:00.000000000 0.0 1 1970-01-01 00:00:00.000000100 100.0 2 1970-01-01 00:00:00.000000140 140.0 3 1970-01-01 00:00:00.000000200 200.0 >>> series_2.to_pandas() timestamp value 0 1970-01-01 00:00:00.000000100 200.0 1 1970-01-01 00:00:00.000000120 220.0 2 1970-01-01 00:00:00.000000130 330.0 3 1970-01-01 00:00:00.000000150 350.0 4 1970-01-01 00:00:00.000000160 460.0
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>>> sum_series = F.sum()([series_1, series_2]) >>> sum_series.to_pandas() timestamp value 0 1970-01-01 00:00:00.000000000 0.0 1 1970-01-01 00:00:00.000000100 300.0 2 1970-01-01 00:00:00.000000120 220.0 3 1970-01-01 00:00:00.000000130 330.0 4 1970-01-01 00:00:00.000000140 140.0 5 1970-01-01 00:00:00.000000150 350.0 6 1970-01-01 00:00:00.000000160 460.0 7 1970-01-01 00:00:00.000000200 200.0