Tentative categories were assigned with moderate confidence (0.5 to 0.75): they are shown, but they do not count toward a category’s momentum. How categories work
Install
pip install jackpots
Adoption
Adoption
—Not published by PyPI
Not published
Popularity
—Not published by PyPI
Not published
Dependents
—Not published by PyPI
Not published
Maintenance
0.36
DerivedRelease cadence and recency, 0 to 1
Releases per year
365
1 version over its life
Growth by period
PyPI publishes no adoption figure, so there is no growth to derive. Nothing is estimated in its place.
7 days
—Not published by PyPI
Not published
30 days
—Not published by PyPI
Not published
90 days
—Not published by PyPI
Not published
1 year
—Not published by PyPI
Not published
Adoption history
Adoption history
PyPI publishes no adoption count, so there is no history to chart. That is a fact about the registry, not a gap in ours: the package’s releases and maintenance are measured instead.
A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values
