make_numerical¶
-
getml.datasets.
make_numerical
(n_rows_population=500, n_rows_peripheral=125000, random_state=None, population_name='', peripheral_name='', aggregation='COUNT')[source]¶ Generate a random dataset with continous numerical variables
The dataset consists of a population table and one peripheral table.
The peripheral table has 3 columns:
column_01: random number between -1 and 1
join_key: random integer in the range from 0 to
n_rows_population
time_stamp: random number between 0 and 1
The population table has 4 columns:
column_01: random number between -1 and 1
join_key: unique integer in the range from 0 to
n_rows_population
time_stamp: random number between 0 and 1
targets: target variable. Defined as the number of matching entries in the peripheral table for which
time_stamp_peripheral < time_stamp_population < time_stamp_peripheral + 0.5
SELECT aggregation( column_01 ) FROM POPULATION t1 LEFT JOIN PERIPHERAL t2 ON t1.join_key = t2.join_key WHERE ( ( t1.time_stamp - t2.time_stamp <= 0.5 ) ) AND t2.time_stamp <= t1.time_stamp GROUP BY t1.join_key, t1.time_stamp;
- Args:
- n_rows_population (int, optional):
Number of rows in the population table.
- n_row_peripheral (int, optional):
Number of rows in the peripheral table.
- random_state (Union[int, None], optional):
Seed to initialize the random number generator used for the dataset creation. If set to None, the seed will be the ‘microsecond’ component of
datetime.datetime.now()
.- population_name (string, optional):
Name assigned to the create
DataFrame
holding the population table. If set to a name already existing on the getML engine, the correspondingDataFrame
will be overwritten. If set to an empty string, a unique name will be generated by concatenating numerical_population_ and the seed of the random number generator.- peripheral_name (string, optional):
Name assigned to the create
DataFrame
holding the peripheral table. If set to a name already existing on the getML engine, the correspondingDataFrame
will be overwritten. If set to an empty string, a unique name will be generated by concatenating numerical_peripheral_ and the seed of the random number generator.- aggregation(string, optional):
aggregations
used to generate the ‘target’ column.
- Returns:
- tuple:
tuple containing:
population (
getml.DataFrame
): Population tableperipheral (
getml.DataFrame
): Peripheral table