Column structures

CategoricalColumnStructure

__init__

__init__(
    categories: Sequence[str] | None = None,
    null_values: Sequence = (),
) -> None

Structure for a categorical column.

Parameters:

Name	Type	Description	Default
categories	Sequence[str] | None	Categories of the column. If None, the column needs to be fitted.	None
null_values	Sequence	Values to be considered as null.	()

fit

fit(x: Series) -> None

Fit the column structure on the input data.

Parameters:

Name	Type	Description	Default
x	Series	The column data to fit on.	required

IntegerColumnStructure

__init__

__init__(
    min_digits: int | None = None,
    max_digits: int | None = None,
    positive: bool = False,
    null_values: Sequence = (),
) -> None

Structure for a column that contains integer values.

Parameters:

Name	Type	Description	Default
min_digits	int | None	The minimum number of digits.	None
max_digits	int | None	The maximum number of digits.	None
positive	bool	Whether the values are positive.	False
null_values	Sequence	Values to be considered as null.	()

FloatColumnStructure

__init__

__init__(
    min_int_digits: int | None = None,
    max_int_digits: int | None = None,
    min_decimal_digits: int | None = None,
    max_decimal_digits: int | None = None,
    positive: bool = False,
    has_ints: bool = False,
    null_values: Sequence = (),
) -> None

Structure for a column that contains float values.

Parameters:

Name	Type	Description	Default
min_int_digits	int | None	The minimum number of digits in the integer part.	None
max_int_digits	int | None	The maximum number of digits in the integer part.	None
min_decimal_digits	int | None	The minimum number of digits in the decimal part.	None
max_decimal_digits	int | None	The maximum number of digits in the decimal part.	None
positive	bool	Whether the values are positive.	False
has_ints	bool	Whether the values have an integer part.	False
null_values	Sequence	Values to be considered as null.	()

fit

fit(x: Series) -> None

Fit the column structure on the input data.

Parameters:

Name	Type	Description	Default
x	Series	The column data to fit on.	required

WordSequenceColumnStructure

__init__

__init__(
    min_word_len: int = 0,
    max_word_len: int = 100,
    min_n_words: int = 1,
    max_n_words: int = 15,
    allow_digits: bool = False,
    null_values: Sequence = (),
) -> None

Structure for a column that contains a sequence of words.

Parameters:

Name	Type	Description	Default
min_word_len	int	The minimum length of a word.	0
max_word_len	int	The maximum length of a word.	100
min_n_words	int	The minimum number of words.	1
max_n_words	int	The maximum number of words.	15
allow_digits	bool	Whether digits are allowed in the words.	False
null_values	Sequence	Values to be considered as null.	()

fit

fit(x: Series) -> None

Fit the column structure on the input data.

Parameters:

Name	Type	Description	Default
x	Series	The column data to fit on.	required

CustomRegexColumnStructure

__init__

__init__(regex: str, null_values: Sequence = ()) -> None

Structure for a column that contains values that match a custom regex.

Parameters:

Name	Type	Description	Default
regex	str	The regex that the values must match.	required
null_values	Sequence	Values to be considered as null	()

fit

fit(x: Series) -> None

Fit the column structure on the input data.

Parameters:

Name	Type	Description	Default
x	Series	The column data to fit on.	required