R: Add many time series features to the data

tk_augment_timeseries {timetk} | R 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)
    library(timetk)

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

[Package timetk version 2.4.0 Index]