Temporal feature extraction

Feature extraction for temporal columns

ExpandDate

ExpandDate(self, inputs, components=('dow', 'month', 'year'))

A step for expanding date columns into one or more features.

New features will be named {input_column}_{component}. For example, if expanding a "year" component from column "x", the feature column would be named "x_year".

Parameters

Name Type Description Default
inputs SelectionType A selection of date columns to expand into new features. required
components Sequence[Literal['day', 'week', 'month', 'year', 'dow', 'doy']] A sequence of components to expand. Options include - day: the day of the month as a numeric value - week: the week of the year as a numeric value - month: the month of the year as a categorical value - year: the year as a numeric value - dow: the day of the week as a categorical value - doy: the day of the year as a numeric value Defaults to ["dow", "month", "year"]. ('dow', 'month', 'year')

Examples

>>> import ibis_ml as ml

Expand date columns using the default components

>>> step = ml.ExpandDate(ml.date())

Expand specific columns using specific components

>>> step = ml.ExpandDate(["x", "y"], ["day", "year"])

ExpandTime

ExpandTime(self, inputs, components=('hour', 'minute', 'second'))

A step for expanding time columns into one or more features.

New features will be named {input_column}_{component}. For example, if expanding an "hour" component from column "x", the feature column would be named "x_hour".

Parameters

Name Type Description Default
inputs SelectionType A selection of time columns to expand into new features. required
components Sequence[Literal['hour', 'minute', 'second', 'millisecond']] A sequence of components to expand. Options include hour, minute, second, and millisecond. Defaults to ["hour", "minute", "second"]. ('hour', 'minute', 'second')

Examples

>>> import ibis_ml as ml

Expand time columns using the default components

>>> step = ml.ExpandTime(ml.time())

Expand specific columns using specific components

>>> step = ml.ExpandTime(["x", "y"], ["hour", "minute"])

ExpandTimestamp

ExpandTimestamp(
    self,
    inputs,
    components=('dow', 'month', 'year', 'hour', 'minute', 'second'),
)

A step for expanding timestamp columns into one or more features.

New features will be named {input_column}_{component}. For example, if expanding a "year" component from column "x", the feature column would be named "x_year".

Parameters

Name Type Description Default
inputs SelectionType A selection of timestamp columns to expand into new features. required
components list[Literal['day', 'week', 'month', 'year', 'dow', 'doy', 'hour', 'minute', 'second', 'millisecond']] A sequence of date or time components to expand. Options include - day: the day of the month as a numeric value - week: the week of the year as a numeric value - month: the month of the year as a categorical value - year: the year as a numeric value - dow: the day of the week as a categorical value - doy: the day of the year as a numeric value - hour: the hour as a numeric value - minute: the minute as a numeric value - second: the second as a numeric value - millisecond: the millisecond as a numeric value Defaults to ["dow", "month", "year", "hour", "minute", "second"]. ('dow', 'month', 'year', 'hour', 'minute', 'second')

Examples

>>> import ibis_ml as ml

Expand timestamp columns using the default components

>>> step = ml.ExpandTimestamp(ml.timestamp())

Expand specific columns using specific components

>>> step = ml.ExpandTimestamp(["x", "y"], ["day", "year", "hour"])
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