time_frequency {anomalize}  R Documentation 
Generate a time series frequency from a periodicity
Description
Generate a time series frequency from a periodicity
Usage
time_frequency(data, period = "auto", message = TRUE)
time_trend(data, period = "auto", message = TRUE)
Arguments
data 
A 
period 
Either "auto", a timebased definition (e.g. "14 days"),
or a numeric number of observations per frequency (e.g. 10).
See 
message 
A boolean. If 
Details
A frequency is loosely defined as the number of observations that comprise a cycle
in a data set. The trend is loosely defined as time span that can
be aggregated across to visualize the central tendency of the data.
It's often easiest to think of frequency and trend in terms of the timebased units
that the data is already in. This is what time_frequency()
and time_trend()
enable: using timebased periods to define the frequency or trend.
Frequency:
As an example, a weekly cycle is often 5days (for working
days) or 7days (for calendar days). Rather than specify a frequency of 5 or 7,
the user can specify period = "1 week"
, and
time_frequency()' will detect the scale of the time series and return 5 or 7
based on the actual data.
The period
argument has three basic options for returning a frequency.
Options include:

"auto"
: A target frequency is determined using a predefined template (seetemplate
below). 
timebased duration
: (e.g. "1 week" or "2 quarters" per cycle) 
numeric number of observations
: (e.g. 5 for 5 observations per cycle)
The template
argument is only used when period = "auto"
. The template is a tibble
of three features: time_scale
, frequency
, and trend
. The algorithm will inspect
the scale of the time series and select the best frequency that matches the scale and
number of observations per target frequency. A frequency is then chosen on be the
best match. The predefined template is stored in a function time_scale_template()
.
However, the user can come up with his or her own template changing the values
for frequency in the data frame and saving it to anomalize_options$time_scale_template
.
Trend:
As an example, the trend of daily data is often best aggregated by evaluating
the moving average over a quarter or a month span. Rather than specify the number
of days in a quarter or month, the user can specify "1 quarter" or "1 month",
and the time_trend()
function will return the correct number of observations
per trend cycle. In addition, there is an option, period = "auto"
, to
autodetect an appropriate trend span depending on the data. The template
is used to define the appropriate trend span.
Value
Returns a scalar numeric value indicating the number of observations in the frequency or trend span.
Examples
library(dplyr)
data(tidyverse_cran_downloads)
#### FREQUENCY DETECTION ####
# period = "auto"
tidyverse_cran_downloads %>%
filter(package == "tidyquant") %>%
ungroup() %>%
time_frequency(period = "auto")
time_scale_template()
# period = "1 month"
tidyverse_cran_downloads %>%
filter(package == "tidyquant") %>%
ungroup() %>%
time_frequency(period = "1 month")
#### TREND DETECTION ####
tidyverse_cran_downloads %>%
filter(package == "tidyquant") %>%
ungroup() %>%
time_trend(period = "auto")