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Cast

Cast

In some cases It's useful to cast the datatype of subset of columns

CastTo

Bases: TransformerStep

Cast to a given datatype

Example

step = CastTo(type='float32')

Parameters:

Name Type Description Default
type str

Data Type to cast to

 required
name Optional[str]

Name of the step, by default None

 None
Source code in ceruleo/transformation/features/cast.py 
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class CastTo(TransformerStep):
    """Cast to a given datatype

    Example:
        step = CastTo(type='float32')

    Parameters:
        type: Data Type to cast to
        name: Name of the step, by default None

    """

    def __init__(self, *, type: str, name: Optional[str] = None):
        super().__init__(name=name)
        self.type = type

    def transform(self, X: pd.DataFrame) -> pd.DataFrame:
        """
        Cast to a given datatype

        Parameters:
            X: DataFrame to transform

        Returns:
            Transformed DataFrame
        """
        return X.astype(self.type)

transform(X)

Cast to a given datatype

Parameters:

Name Type Description Default
X DataFrame

DataFrame to transform

 required

Returns:

Type Description
DataFrame

Transformed DataFrame
Source code in ceruleo/transformation/features/cast.py 
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def transform(self, X: pd.DataFrame) -> pd.DataFrame:
    """
    Cast to a given datatype

    Parameters:
        X: DataFrame to transform

    Returns:
        Transformed DataFrame
    """
    return X.astype(self.type)

ToDateTime

Bases: TransformerStep

Cast to a datetime

Example

step = ToDateTime()

Parameters:

Name Type Description Default
name Optional[str]

Name of the step, by default None

 None
Source code in ceruleo/transformation/features/cast.py 
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class ToDateTime(TransformerStep):
    """Cast to a datetime

    Example:
        step = ToDateTime()

    Parameters:
        name: Name of the step, by default None

    """

    def __init__(
        self,
        *,
        units: str = "s",
        name: Optional[str] = None,
        columns: Optional[List[any]] = None,
        index: bool = False,

    ):
        """Cast to a datetime

        Parameters
        ----------
        units : str, optional
            The units to transform, by default "s"
        name : Optional[str], optional
            Name of the step, by default None
        columns : Optional[List[any]], optional
            Columns to transform, by default None
        index : bool, optional
            Wether to transform the index or not, by default False

        Raises
        ------
        ValueError
            _description_
        ValueError
            _description_
        """
        super().__init__(name=name)
        if index is False and columns is None:
            raise ValueError("You must specify the columns to transform")
        if columns is not None and index is True:
            raise ValueError("You can't specify columns and index at the same time")
        self.index = index
        self.columns = columns
        self.units = units

    def transform(self, X: pd.DataFrame) -> pd.DataFrame:
        """
        Cast to a datetime

        Parameters:
            X: DataFrame to transform

        Returns:
            Transformed DataFrame
        """
        X = X.copy()
        if self.index:
            X.index = pd.to_datetime(X.index, unit=self.units)
        else:
            X[self.columns] = X[self.columns].apply(pd.to_datetime)
        return X

__init__(*, units='s', name=None, columns=None, index=False)

Cast to a datetime

Parameters

units : str, optional The units to transform, by default "s" name : Optional[str], optional Name of the step, by default None columns : Optional[List[any]], optional Columns to transform, by default None index : bool, optional Wether to transform the index or not, by default False

Raises

ValueError description ValueError description

Source code in ceruleo/transformation/features/cast.py 
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def __init__(
    self,
    *,
    units: str = "s",
    name: Optional[str] = None,
    columns: Optional[List[any]] = None,
    index: bool = False,

):
    """Cast to a datetime

    Parameters
    ----------
    units : str, optional
        The units to transform, by default "s"
    name : Optional[str], optional
        Name of the step, by default None
    columns : Optional[List[any]], optional
        Columns to transform, by default None
    index : bool, optional
        Wether to transform the index or not, by default False

    Raises
    ------
    ValueError
        _description_
    ValueError
        _description_
    """
    super().__init__(name=name)
    if index is False and columns is None:
        raise ValueError("You must specify the columns to transform")
    if columns is not None and index is True:
        raise ValueError("You can't specify columns and index at the same time")
    self.index = index
    self.columns = columns
    self.units = units

transform(X)

Cast to a datetime

Parameters:

Name Type Description Default
X DataFrame

DataFrame to transform

 required

Returns:

Type Description
DataFrame

Transformed DataFrame
Source code in ceruleo/transformation/features/cast.py 
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def transform(self, X: pd.DataFrame) -> pd.DataFrame:
    """
    Cast to a datetime

    Parameters:
        X: DataFrame to transform

    Returns:
        Transformed DataFrame
    """
    X = X.copy()
    if self.index:
        X.index = pd.to_datetime(X.index, unit=self.units)
    else:
        X[self.columns] = X[self.columns].apply(pd.to_datetime)
    return X