filter_time() attempts to make filtering data frames by date much easier
dplyr::filter(). It includes a flexible shorthand notation that allows
you to specify entire date ranges with very little typing. The general form
time_formula that you will use to filter rows is
from ~ to, where
the left hand side (LHS) is the character start date, and the right hand side (RHS) is
the character end date. Both endpoints are included in the result.
Each side of the
time_formula can be maximally specified as
library(tibbletime) library(dplyr) # Facebook stock prices. data(FB) # Convert FB to tbl_time FB <- as_tbl_time(FB, index = date) # FANG stock prices data(FANG) # Convert FANG to tbl_time and group FANG <- as_tbl_time(FANG, index = date) %>% group_by(symbol)
dplyr, if you wanted to get the dates for
2013 in the
FB dataset, you
might do something like this:
filter(FB, date >= as.Date("2013-01-01"), date <= as.Date("2013-12-31"))
That's a lot of typing for one filter step. With
index was specified at creation, we can do this:
filter_time(FB, time_formula = '2013-01-01' ~ '2013-12-31')
At first glance, this might not look like less code, but this is before any
shorthand is applied. Note how the filtering condition is specified as a
formula separated by a
filter_time shorthand, this can be written:
filter_time(FB, '2013' ~ '2013')
Or even more succinctly as:
The shorthand notation works as follows. In the first example,
'2013' ~ '2013' is
'2013-01-01 + 00:00:00' ~ '2013-12-31 + 23:59:59'. It works by
identifying the periodicity of the provided input (yearly), and expanding it
to the beginning and end of that period. The one sided formula
similarly, and is useful when you want to select every date inside a period.
As another example of this shorthand, if you wanted to select every date in March, 2015:
filter_time(FB, ~'2015-03') # In dplyr it looks like this # (and you have to think, does March have 30 or 31 days?) # filter(FB, date >= as.Date("2015-03-01"), date <= as.Date("2015-03-31"))
Two keywords are available to assist with filtering:
'start'- The start of the series
'end'- The end of the series
This filters from the start of the series to the end of 2015.
filter_time(FB, 'start' ~ '2015')
Working with grouped
tbl_time objects is just as you might expect.
FANG %>% filter_time('2013-01-01' ~ '2013-01-04')
Filtering can also be done by hour / minute / second. Note that the form of this
is slightly different than the standard,
# Dummy example. Every second in a day example <- create_series(~'2013-01-01', period = 's') # The first 2 minutes of the day example %>% filter_time('2013-01-01' ~ '2013-01-01 00:02') # 3 specific hours of the day # Equivalent to: # '2013-01-01 + 03:00:00' ~ '2013-01-01 + 06:59:59' example %>% filter_time('2013-01-01 3' ~ '2013-01-01 6')
For interactive use, to get an even quicker look at a dataset you can use
the traditional extraction operator
[ with the formula syntax.
Each side of the time formula is unquoted and evaluated in the environment
that is was created using
rlang. This means that you can use variables inside
the call the
date_var <- as.Date("2014-01-01") filter_time(FB, 'start' ~ date_var) date_char <- "2014-02" filter_time(FB, ~ date_char)
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