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This repository has been archived by the owner on Jun 9, 2020. It is now read-only.
Hi,
I really appreciate the effort of lowering the barrier of entry to crossfilter - in particular providing some kind of grammar for querying multivariate dataset. However, playing around the library is not extremely straightforward at the moment, and I found that its added value over defining your own dimensions and groups in crossfilter directly was not obvious from the provided code samples.
Maybe porting the Airline on-time performance example to universe could help a user like myself see/understand/delve into a more comprehensive usecase (e.g. filtering the dataset on multiple dimensions, see how we can add listeners to filtering actions, ... ).
I actually tried to port this example myself - without success (at least given the timeframe I allowed myself to test out the lib - and the available amount of brain cells...).
Hi,
I really appreciate the effort of lowering the barrier of entry to crossfilter - in particular providing some kind of grammar for querying multivariate dataset. However, playing around the library is not extremely straightforward at the moment, and I found that its added value over defining your own dimensions and groups in crossfilter directly was not obvious from the provided code samples.
Maybe porting the Airline on-time performance example to universe could help a user like myself see/understand/delve into a more comprehensive usecase (e.g. filtering the dataset on multiple dimensions, see how we can add listeners to filtering actions, ... ).
I actually tried to port this example myself - without success (at least given the timeframe I allowed myself to test out the lib - and the available amount of brain cells...).
Thanks anyway,
C.
P.S. There are some helpful hints/example in the gitter channel though - saw them a bit too late!
P.P.S. Oh - this should be highlighted ! http://hypercubed.github.io/Project-Chi/#/examples/universe
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