Dask Dataframes with query optimization.
This is a proof-of-concept rewrite of Dask dataframe that includes query optimization and generally improved organization.
import dask_expr as dx
df = dx.datasets.timeseries()
df.head()
df.groupby("name").x.mean().compute()Dask-expr encodes user code in an expression tree:
>>> df.x.mean().pprint()
Mean:
Projection: columns='x'
Timeseries: seed=1896674884This expression tree will be optimized and modified before execution:
>>> df.x.mean().optimize().pprint()
Div:
Sum:
Fused(375f9):
| Projection: columns='x'
| Timeseries: dtypes={'x': <class 'float'>} seed=1896674884
Count:
Fused(375f9):
| Projection: columns='x'
| Timeseries: dtypes={'x': <class 'float'>} seed=1896674884This project is a work in progress and will be changed without notice or deprecation warning. Please provide feedback, but it's best to avoid use in production settings.
dask_expr.DataFrame
absadd_prefixadd_sufixalignallanyapplyassignastypeclipcombine_firstcopycountdaskdropdrop_duplicatesdropnaevalexplodefillnagroupbyheadidxmaxidxminindexisinisnajoinmapmap_partitionsmaxmemory_usagemergeminminmodenlargestnsmallestnunique_approxpartitionspivot_tableprodrenamerename_axisrepartitionreplacereset_indexroundsamplesort_valuesselect_dtypesset_indexshufflestdsumtailto_parquetto_timestampvarvisualize
dask_expr.Series
absalignallanyapplyastypebetweenclipcombine_firstcopycountdaskdrop_duplicatesdropnaexplodefillnagroupbyheadidxmaxidxminindexisinisnamapmap_partitionsmaxmemory_usageminminmodenlargestnsmallestnunique_approxpartitionsprodrename_axisrepartitionreplacereset_indexroundshufflestdsumtailto_frameto_timestampuniquevalue_countsvarvisualize
dask_expr.Index
absalignallanyapplyastypeclipcombine_firstcopycountdaskfillnagroupbyheadidxmaxidxminindexisinisnamap_partitionsmaxmemory_usageminminmodenunique_approxpartitionsprodrename_axisrepartitionreplacereset_indexroundshufflestdsumtailto_frameto_timestampvarvisualize
dask_expr._groupby.GroupBy
aggaggregatecountfirstlastmaxmeanminprodsizestdsumvalue_countsvar
Binary operators (DataFrame, Series, and Index):
__add____radd____sub____rsub____mul____rmul____truediv____rtruediv____lt____rlt____gt____rgt____le____rle____ge____rge____eq____ne____and____rand____or____ror____xor____rxor__
Unary operators (DataFrame, Series, and Index):
__invert____neg____pos__
Accessors:
CategoricalAccessorDatetimeAccessorStringAccessor