massive_variance_test¶
- hana_ml.algorithms.pal.preprocessing.massive_variance_test(data, sigma_num, group_key=None, thread_ratio=None, key=None, data_col=None)¶
Massive version of
variance_test().This function calls SAP HANA PAL function
PAL_MASSIVE_VARIANCE_TESTto run variance test in parallel across multiple independent datasets identified by a group id.- Parameters
- dataDataFrame
Input data for variance test in massive mode.
This DataFrame must be structured as follows:
1st column : GROUP ID, type INT, VARCHAR or NVARCHAR.
2nd column : ID, type INT, VARCHAR or NVARCHAR.
3rd column : raw data, type INTEGER, DOUBLE, or DECIMAL(p,s).
- sigma_numfloat
Multiplier for sigma.
- group_keystr, optional
Name of the group id column. If not provided, it defaults to:
the first index column of
dataifdatais indexed, otherwisethe first column of
data.
- thread_ratiofloat, optional
Same meaning as in
variance_test().- keystr, optional
Name of the ID column in
data.If not specified, it defaults to:
the second index column of
dataifdatahas multiple index columns and the first one is used asgroup_key, otherwisethe first non-
group_keycolumn ofdata.
- data_colstr, optional
Name of the raw data column in the dataframe.
If not specified, defaults to the last column of data excluding
group_keyandkey.
- Returns
- DataFrames
DataFrame 1 : result output with an additional group id column.
DataFrame 2 : statistics output with an additional group id column.
DataFrame 3 : error message table for massive execution.