Pivoting/grouping multiple attributes after time-series feature extraction
Hello,
I extracted features of multiple time series batches (IDx) with multiple signal columns (signalx) using the extract aggregates block on these multiple signals.
I receive data in the form of:
ID1 - "signal1" - feat1 - feat2 - ...
ID1 - "signal2" - feat1 - feat2 - ...
ID2 - "signal1" - feat1 - feat2 - ...
ID2 - "signal2" - feat1 - feat2 - ...
...
How can I perform a pivoting/grouping-like operation (with multiple attributes) that gives me somthing like this:
ID1 - signal1_feat1 - signal1_feat2 - signal2_feat1 - signal2_feat2 - ...
ID2 - signal1_feat1 - signal1_feat2 - signal2_feat1 - signal2_feat2 - ...
...
Thanks for your help!
I extracted features of multiple time series batches (IDx) with multiple signal columns (signalx) using the extract aggregates block on these multiple signals.
I receive data in the form of:
ID1 - "signal1" - feat1 - feat2 - ...
ID1 - "signal2" - feat1 - feat2 - ...
ID2 - "signal1" - feat1 - feat2 - ...
ID2 - "signal2" - feat1 - feat2 - ...
...
How can I perform a pivoting/grouping-like operation (with multiple attributes) that gives me somthing like this:
ID1 - signal1_feat1 - signal1_feat2 - signal2_feat1 - signal2_feat2 - ...
ID2 - signal1_feat1 - signal1_feat2 - signal2_feat1 - signal2_feat2 - ...
...
Thanks for your help!
0
Best Answer
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MartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,454
RM Data Scientist