TRAIN_TEST_SPLIT

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Split an input dataframe into test and training dataframes according to a size parameter. Params: test_size : float The size of testing data specified. Returns: train : DataFrame A dataframe of training data. test : DataFrame A dataframe of test data.

Python Code

from typing import TypedDict
from flojoy import flojoy, DataFrame
from sklearn.model_selection import train_test_split


class TrainTestSplitOutput(TypedDict):
    train: DataFrame
    test: DataFrame


@flojoy(deps={"scikit-learn": "1.2.2"})
def TRAIN_TEST_SPLIT(
    default: DataFrame, test_size: float = 0.2
) -> TrainTestSplitOutput:
    """Split an input dataframe into test and training dataframes according to a size parameter.

    Parameters
    ----------
    test_size : float
        The size of testing data specified.

    Returns
    -------
    train: DataFrame
        A dataframe of training data.
    test: DataFrame
        A dataframe of test data.
    """

    df = default.m

    train, test = train_test_split(df, test_size=test_size)

    return TrainTestSplitOutput(train=DataFrame(df=train), test=DataFrame(df=test))

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Example App

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In this example, the READ_CSV node loads a local .csv file and passes it to our TRAIN_TEST_SPLIT node which divides up the data file according to the test size specified which then can be used for training and testing for ML models. The information is displayed with TABLE node.