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Don't enforce names on input datasets (source, target, value) #56
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Hi, thanks for your comment and sorry for the slow response. I like the suggestion in principle, but I don't know if would actually be worth the extra complexity? Currently you can do something like this: dataset = floweaver.Dataset(my_data_frame.rename(columns={
'my_source': 'source',
'my_target': 'target',
})) while what you're suggesting I guess would look like this? dataset = floweaver.Dataset(my_data_frame,
source_column='my_source',
target_column='my_target') which is probably worthwhile though not all that much neater. Is that what you mean? Note that the |
I didn't know about the I believe it is worth it because of the following situations:
|
There's a difference between the flows in the dataset, and the way they're visualised. In this case why don't you change the partition of the source? nodes = {
'x': ProcessGroup(['a', 'b', 'c'], partition1),
'y': Waypoint(partition2),
'z': ProcessGroup(['end'], partition3),
}
bundles = [
Bundle('x', 'z', waypoints=['y'])
] To make it look like it starts with the first waypoint (partition2) it would become nodes = {
'x': ProcessGroup(['a', 'b', 'c'], partition2),
'z': ProcessGroup(['end'], partition3),
}
bundles = [
Bundle('x', 'z', waypoints=[])
] You don't have to change the |
But generally, ok, I think it'd be reasonable to add this. But it's not trivial as |
I can try but not in the short term, I really like the framework and I think it's worth doing. Is there any way to quickly test the code? I don't want to introduce new errors |
Thanks, see my reply in #55 |
When working with pre-processed datasets it may be the case where there is no column name
source
ortarget
orvalue
and even worse, they may be present with a completely different meaning!I suggest to add optional parameters to set the name of the columns corresponding to this function, this way one shouldn't be "renaming" columns just to fit the library specs.
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