foundryts.functions.mean

foundryts.functions.mean()

Returns a function that computes the mean 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 time series, where each timestamp contains the means 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 mean of all points in the input time series that share a timestamp.
• Return type: (NodeCollection) -> FunctionNode

Dataframe schema

Examples

Copied!
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
>>> 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

Copied!
1
2
3
4
5
6
7
8
9
10
11
>>> mean_series = F.mean()([series_1, series_2, series_2])
>>> mean_series.to_pandas()
                      timestamp       value
0 1970-01-01 00:00:00.000000000    0.000000
1 1970-01-01 00:00:00.000000100  166.666667
2 1970-01-01 00:00:00.000000120  220.000000
3 1970-01-01 00:00:00.000000130  330.000000
4 1970-01-01 00:00:00.000000140  140.000000
5 1970-01-01 00:00:00.000000150  350.000000
6 1970-01-01 00:00:00.000000160  460.000000
7 1970-01-01 00:00:00.000000200  200.000000