foundryts.functions.sum¶
foundryts.functions.sum()¶
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.
- Returns: A function that accepts multiple time series as inputs and generates a single time series contains a union of all timestamps with the values as the sum of all points in the input time series that share a timestamp.
- Return type: (NodeCollection) -> FunctionNode
Dataframe schema¶
| Column name | Type | Description |
|---|---|---|
| timestamp | pandas.Timestamp | Timestamp of the point |
| value | float | Value of the point |
:::callout{theme="success" title="See Also"}
mean()
:::
:::callout{theme="warning" title="Note"} This function is only applicable to numeric series. :::
Examples¶
>>> 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
>>> 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
中文翻译¶
foundryts.functions.sum¶
foundryts.functions.sum()¶
返回一个函数，用于计算多个输入时间序列中共享同一时间戳的所有数据点的总和。
生成的时间序列是所有输入序列时间戳的并集，其中每个时间戳包含该时间戳下输入集合中存在的所有值的总和。
- 返回值： 一个函数，接受多个时间序列作为输入，并生成一个单一的时间序列，该序列包含所有时间戳的并集，其值为输入时间序列中共享同一时间戳的所有数据点的总和。
- 返回类型： (NodeCollection) -> FunctionNode
数据框模式 (Dataframe schema)¶
| 列名 (Column name) | 类型 (Type) | 描述 (Description) |
|---|---|---|
| timestamp | pandas.Timestamp | 数据点的时间戳 |
| value | float | 数据点的值 |
:::callout{theme="success" title="另请参阅 (See Also)"}
mean()
:::
:::callout{theme="warning" title="注意 (Note)"} 此函数仅适用于数值型序列。 :::
示例 (Examples)¶
>>> 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
>>> 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