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timefully

The goal of timefully is to facilitate the management of time-series data frames to adapt the timezone, time resolution, and date range, as well as filling gaps and visualisation.

You can see its main functionalities through the Get started article.

Installation

You can install the development version of timefully like so:

pak::pak("resourcefully-dev/timefully")

Getting help

If you encounter a clear bug, please open an issue with a minimal reproducible example on GitHub.

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Version

Install

install.packages('timefully')

Version

0.1.0

License

GPL-3

Issues

0

Pull Requests

0

Stars

0

Forks

0

Maintainer

Marc Cañigueral

Last Published

December 10th, 2025

Functions in timefully (0.1.0)

change_timeseries_resolution

Change time resolution of a time-series data frame
fill_down_until

Fill down tibble columns until a maximum number of time slots
aggregate_timeseries

Aggregate multiple timeseries columns to a single one
get_week_from_datetime

Week date from datetime value
fill_from_past

Fill from past values
increase_datetime_resolution

Increase datetime vector resolution
to_hhmm

Convert a number of minutes in string format "HH:MM"
get_timeseries_resolution

Return the time resolution of a time series dataframe
interpolation

Interpolate n values between two numeric values
get_yearly_datetime_seq

Yearly date time sequence with time zone and resolution
get_week_total

Summarise dataframe with weekly total column values
increase_timeseries_resolution

Increase time resolution of a timeseries data frame
toc

Time difference end function
increase_numeric_resolution

Increase numeric vector resolution
ywday

Year-weekday occurrence identifier
plot_ts

Interactive plot for time-series tibbles
tic

Time difference start function
decrease_timeseries_resolution

Decrease time resolution of timeseries data frame
adapt_timeseries

Adapt time-series dataframe to timezone, date range and fill gaps
check_timeseries_gaps

Check if there are any gaps in the datetime sequence
change_timeseries_tzone

Adapt the timezone of a time series dataframe
date_to_timestamp

Convert date or datetime value to timestamp number
convert_time_num_to_period

Convert numeric time value to a datetime period (hour-based)
add_extra_days

Add an extra day at the beginning and the end of datetime sequence using the last and first day of the data
fill_na

Fill gaps with a specific value
get_timeseries_tzone

Get the time zone of a time series dataframe
get_datetime_seq

Date time sequence with time zone and resolution
fill_datetime

Fill NA values of a datetime sequence vector
dhours

Decimal hours from datetime
get_time_resolution

Return the time resolution of a datetime sequence
dtf

Time-series profiles of consumption and production energy data