tk_augment_timeseries: Add many time series features to the data

tk_augment_timeseriesR Documentation

Add many time series features to the data

Description

Add many time series features to the data

Usage

tk_augment_timeseries_signature(.data, .date_var = NULL)

Arguments

.data

A time-based tibble or time-series object.

.date_var

For tibbles, a column containing either date or date-time values. If NULL, the time-based column will interpret from the object (tibble, xts, zoo, etc).

Details

tk_augment_timeseries_signature() adds 25+ time series features including:

  • Trend in Seconds Granularity: index.num

  • Yearly Seasonality: Year, Month, Quarter

  • Weekly Seasonality: Week of Month, Day of Month, Day of Week, and more

  • Daily Seasonality: Hour, Minute, Second

  • Weekly Cyclic Patterns: 2 weeks, 3 weeks, 4 weeks

Value

Returns a tibble object describing the timeseries.

See Also

Augment Operations:

  • tk_augment_timeseries_signature() - Group-wise augmentation of timestamp features

  • tk_augment_holiday_signature() - Group-wise augmentation of holiday features

  • tk_augment_slidify() - Group-wise augmentation of rolling functions

  • tk_augment_lags() - Group-wise augmentation of lagged data

  • tk_augment_differences() - Group-wise augmentation of differenced data

  • tk_augment_fourier() - Group-wise augmentation of fourier series

Underlying Function:

  • tk_get_timeseries_signature() - Returns timeseries features from an index

Examples

library(dplyr)

m4_daily %>%
    group_by(id) %>%
    tk_augment_timeseries_signature(date)


timetk documentation built on Nov. 2, 2023, 6:18 p.m.