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Optimization for heatmap aggregation with pandas #1174
A 5-10x speedup for HeatMap aggregation when using a pandas/dask interface.
data = [(i, j, np.random.rand()) for i in range(500) for j in range(500)] %%timeit hv.HeatMap(data)
1 loop, best of 3: 8.61 s per loop
1 loop, best of 3: 800 ms per loop
That's not really a safe assumption, by default dask will simple use a single partition and may therefore actually be slower than pandas and their lazy nature is probably a bit surprising/confusing for a user who doesn't know anything about them.