TakeFilter Class
Take N first rows of the dataset, allowing limiting input to a subset of rows.
- Inheritance
-
nimbusml.internal.core.preprocessing.filter._takefilter.TakeFilterTakeFilternimbusml.base_transform.BaseTransformTakeFiltersklearn.base.TransformerMixinTakeFilter
Constructor
TakeFilter(count, columns=None, **params)
Parameters
- columns
a string representing the column name to perform the transformation on.
Input column type: numeric.
Output column type: numeric.
The << operator can be used to set this value (see Column Operator)
For example
TakeFilter(columns='age')
TakeFilter() << {'age'}
For more details see Columns.
- count
number of rows to keep from the beginning of the dataset.
- params
Additional arguments sent to compute engine.
Examples
import numpy as np
from nimbusml import FileDataStream
from nimbusml.datasets import get_dataset
from nimbusml.preprocessing.filter import SkipFilter, TakeFilter
# data input (as a FileDataStream)
path = get_dataset('infert').as_filepath()
data = FileDataStream.read_csv(
path, sep=',', names={
0: 'id'}, dtype={
'id': str, 'age': np.float32})
print(data.head())
# age case education id induced parity pooled.stratum spontaneous ...
# 0 26.0 1 0-5yrs 1 1 6 3 2 ...
# 1 42.0 1 0-5yrs 2 1 1 1 0 ...
# 2 39.0 1 0-5yrs 3 2 6 4 0 ...
# 3 34.0 1 0-5yrs 4 2 4 2 0 ...
# 4 35.0 1 6-11yrs 5 1 3 32 1 ...
# fit and transform
print(TakeFilter(count=100).fit_transform(data).shape)
# (100, 9), first 100 rows are preserved
print(SkipFilter(count=100).fit_transform(data).shape)
# (148, 9), first 100 rows are deleted
Methods
get_params |
Get the parameters for this operator. |
get_params
Get the parameters for this operator.
get_params(deep=False)
Parameters
- deep
default value: False