Window supported APIs¶

The following table is structured as follows: The first column contains the method name. The second column is a flag for whether or not there is an implementation in Snowpark for the method in the left column.

Note

Y stands for yes, i.e., supports distributed implementation, N stands for no and API simply errors out, P stands for partial (meaning some parameters may not be supported yet), and D stands for defaults to single node pandas execution via UDF/Sproc. engine and engine_kwargs are always ignored in Snowpark pandas. The execution engine will always be Snowflake.

Rolling window functions

Rolling window functions	Snowpark implemented? (Y/N/P/D)	Notes for current implementation
`aggregate`	N
`apply`	N
`corr`	P	`N` for non-integer `window`, `axis = 1`, `pairwise = True`, `other = None`, or `min_periods != window`
`count`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`cov`	N
`kurt`	N
`max`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`mean`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`median`	N
`min`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`quantile`	N
`rank`	N
`sem`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`skew`	N
`std`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`sum`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.
`var`	P	`N` for `axis = 1` or `min_periods = 0`. `N` for string `window` with `center = True`. `N` for Timedelta or BaseIndexer `window`.

Weighted window functions

Weighted window functions	Snowpark implemented? (Y/N/P/D)	Notes for current implementation
`mean`	N
`std`	N
`sum`	N
`var`	N

Expanding window functions

Expanding window functions	Snowpark implemented? (Y/N/P/D)	Notes for current implementation
`aggregate`	N
`apply`	N
`corr`	N
`count`	P	`N` if `axis = 1`
`cov`	N
`kurt`	N
`max`	P	`N` if `axis = 1`
`mean`	P	`N` if `axis = 1`
`median`	N
`min`	P	`N` if `axis = 1`
`quantile`	N
`rank`	N
`sem`	P	`N` if `axis = 1`
`skew`	N
`std`	P	`N` if `axis = 1` or `ddof` is not 0 or 1
`sum`	P	`N` if `axis = 1`
`var`	P	`N` if `axis = 1` or `ddof` is not 0 or 1

Exponentially-weighted window functions

Exponential moving window functions	Snowpark implemented? (Y/N/P/D)	Notes for current implementation
`corr`	N
`cov`	N
`mean`	N
`std`	N
`sum`	N
`var`	N

Window indexer

Window Functions	Snowpark implemented? (Y/N/P/D)	Notes for current implementation
`api.indexers.BaseIndexer`	N
`api.indexers.FixedForwardWindowIndexer`	N
`api.indexers.VariableOffsetWindowIndexer`	N