timefully0.1.0 package

Time-Series Management Made Easy

adapt_timeseries

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

add_extra_days

Add an extra day at the beginning and the end of datetime sequence usi...

aggregate_timeseries

Aggregate multiple timeseries columns to a single one

change_timeseries_resolution

Change time resolution of a time-series data frame

change_timeseries_tzone

Adapt the timezone of a time series dataframe

check_timeseries_gaps

Check if there are any gaps in the datetime sequence

convert_time_num_to_period

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

date_to_timestamp

Convert date or datetime value to timestamp number

decrease_timeseries_resolution

Decrease time resolution of timeseries data frame

dhours

Decimal hours from datetime

fill_datetime

Fill NA values of a datetime sequence vector

fill_down_until

Fill down tibble columns until a maximum number of time slots

fill_from_past

Fill from past values

fill_na

Fill gaps with a specific value

get_datetime_seq

Date time sequence with time zone and resolution

get_time_resolution

Return the time resolution of a datetime sequence

get_timeseries_resolution

Return the time resolution of a time series dataframe

get_timeseries_tzone

Get the time zone of a time series dataframe

get_week_from_datetime

Week date from datetime value

get_week_total

Summarise dataframe with weekly total column values

get_yearly_datetime_seq

Yearly date time sequence with time zone and resolution

increase_datetime_resolution

Increase datetime vector resolution

increase_numeric_resolution

Increase numeric vector resolution

increase_timeseries_resolution

Increase time resolution of a timeseries data frame

interpolation

Interpolate n values between two numeric values

plot_ts

Interactive plot for time-series tibbles

tic

Time difference start function

to_hhmm

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

toc

Time difference end function

ywday

Year-weekday occurrence identifier

Manage time-series data frames across time zones, resolutions, and date ranges, while filling gaps using weekday/hour patterns or simple fill helpers or plotting them interactively. It is designed to work seamlessly with the tidyverse and dygraphs environments.

  • Maintainer: Marc Cañigueral
  • License: GPL-3
  • Last published: 2025-12-10