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padr working with the upcoming R release. Appeasing an
issue with as.character.POSIXlt.When the specified interval is equal or lower than the interval
of the datetime variable, thicken will no longer throw an
error, but a warning. Request by Matus Goljer, issue #84.
Bug fix, pad did not work when
dplyr::group_by had irregular column names (using back
ticks). Bug spotted by Jason Hunter in issue #69.
Bug fix, thicken used to return a vector instead of
a data.frame when the drop argument was TRUE and the only column in the
data.frame was the datetime variable. It will now return a data frame
instead. issue #76.
Informative error thrown for Year 2038 problem when date time variable is POSIXt and the year is 2038 or greater. Problem detected by github users darneiri and Blundys. issue #51
The pad function used to break when the dt_var was
of calss POSIXt and the interval was week or day, when the period
crosses a switch from or to daylight savings time. This is fixed. Also,
an explicit warning is thrown when it is attempted to use “DSTday” as
interval, which does not work. Bugs spotted by Tyler Grant Smith. issue
#78
The pad function used to call the deprecated .dots
argument in dplyr::groups, which threw a warning when
pad was applied on a grouped tibble. This is updated.
Thanks to Matt Cowgill and Kristian Gjerde for spotting this. issue
#80
Patch release, adjusting the unit tests to play with R.4.* new time zone implementations.
Updated padr to make sure it will work with the upcoming
v1.0.0 release of dplyr.
Patch release requested by CRAN maintainers, so package is up-to-date
with latest version of tibble.
thicken preserves missing values in the datetime column
and adds them to the added column. The missing values were placed on the
wrong position. They were placed on NA position + nr of NAs earlier in
the datetime variable, instead of the NA position. Only the first
missing value was on the correct position. Bug reported by github user
github user levi-nagy.thicken has gained the ties_to_earlier
argument. Logical with FALSE as default value. By default
when the rounding argument in thicken is set
to “up” and the original observation is equal to a value in the higher
interval variable, the observation is mapped to the next value in the
new variable. (For example 2019-04-14 13:00:00 would be mapped to
2019-04-14 14:00:00 when rounding is “up” and interval is “hour”.) This
can be undesired. When this argument is set to TRUE tied
observations are mapped to their own value (thus to one value earlier in
the new variable). For completeness this argument also works when
rounding is “down”. Then, when original and new value are
tied, the original value is mapped to the previous value of the higher
level interval variable. (For example 2019-04-14 13:00:00 will be mapped
to 2019-04-14 12:00:00 when the interval is hour). Feature request by
github user stribstrib.
thicken has gained a drop argument.
Logical with FALSE as default value. If TRUE
the thickened datetime value is dropped from the data frame. Idea by
Adam Stone.
An informative error is now thrown in pad,
pad_cust, thicken, thicken_cust
when a data frame does not have any rows. Requested by Julian
During.
The functions thicken and thicken_cust
no longer throw a warning when the input datetime variable is unsorted.
The functions now silently return the a data frame with the same row
order as the input data frame.
Error within padr for break_above error
message is corrected. No longer prints the number of millions in
millions. Bug found by Sharla Gelfand.
Patch releases with no impact for the user of the software.
thicken is sped up significantly:
get_interval no longer applied to assess interval
validity (its slow on large variables because it converts a POSIX to
character). Rather validity is now compared after thickening by checking
if results differs from original. Makes function approximately four
times faster.
get_interval is sped up significantly:
to convert date to character format is used, instead
of as.character. For large vectors it 4 to 5 times
faster.
span_date and span_time are new
functions and they are wrappers around seq.Date and
seq.POSIXt respectively. Because of their default settings
(minimal specification of date and datetimes and interval inference)
they require very little inputs for straightforward spanning.
The closest_weekday function is introduced. It finds
the closest requested weekday around the start of a datetime variable.
This function helps to find quickly the start_val for
thicken when the interval is “week”.
Two new functions are introduced that help with visualising interval data.
center_interval shifts the datetime variable from
either the beginning or the end of the interval, to the center of the
interval. This will improve visualisations such as dot plots and bar
plots, where the timestamp is still considered to be
continuous.
format_interval takes the start_value of an interval
and infers the end. It uses strftime on both the start
value and the end value, to create a character vector that reflects the
full interval.
The _cust suite allows for user-specified spanning
to use in thickening and padding.
to create an asymmetric spanning, subset_span
subsets a datetime vector to the desired date and time points. These are
provided in a list.
span_around takes a datetime variable as input and
spans a variable around it of a desired interval. This automates finding
the min and the man of x manually, determining which values
are needed to create a span of a desired interval, and do the actual
spanning.
Both pad and thicken will no longer
break when there are missing values in the datetime variable. Rows
containing missing values will be retained in the returned data frame.
In the case of thicken they will remain on the same
position as the input data frame. The added column will have a missing
value as well. For pad all the rows with missing values
will be moved to the end of the dataframe, since there is no natural
position for them in the order of padded rows.
When time variable has NULL as timezone, also
posix_to_date used to break (related to #14). This made
thicken break when the desired interval is “day” or higher.
This is now fixed by don’t regarding the timezone.
get_interval now throws an informative error when
the datetime variable has missing values (#33).
pad now throws an informative error when the
datetime variable is used in the grouping (#38)
added “ByteCompile: true” to DESCRIPTION.
pad no longer throws a message when the interval is
specified (#31).
span around hours and minutes now start at the
current hour and minute. This to make span_around
sensible.
The interval is no longer limited to be of a single unit, for each of
the eight interval sizes. Every time span accepted by
seq.Date or seq.POSIXt is now accepted. Since
the original implementation was fully around single-unit-intervals, some
default behavior had to change. Because of it, this version is not
entirely backwards compatible with earlier versions of
padr. The following functions are affected:
thicken: the interval argument now has
to be specified. In earlier versions it was optional. When it was not
specified, the added variable was one interval level higher than that of
the input datetime variable. With the widening of the interval
definition, there is not longer a natural step up.
get_interval: does no longer only retrieve the
interval of a datetime variable, but also its unit (the step size). For
instance, the following would have returned “day” in the past, but will
now return “2 day”:
date_var <- as.Date(c(‘2017-01-01’, ‘2017-01-03’, ‘2017-01-05’)) get_interval(date_var)
pad: when the interval is not specified,
get_interval is applied on the datetime variable. Its
outcome might now be different. When get_interval returns a
different interval than it used to, pad will do the padding
at this different interval. Extending the above example, the have
resulted in a data frame with two padded rows:x <- data.frame(date_var, y = 1:3)
Since the interval of date_var used be “day”, there were
missing records for 2017-01-02 and 2017-01-04. These records were
inserted, with missing values for y. However, now the interval of
date_var is “2 day” and on this level there is no need for
padding. To get the original result the interval argument should be
specified with “day”.
padPad has been reimplemented
The function was slow when applied on many groups becuause it looped
over them. Function has been reimplemented so it needs only one join to
do the padding for all the groups simultaneously. dplyr
functions are used for this new implementation, both for speed and
coding clarity.
When applying pad to groups the interval is determined differently.
It used to determine the interval separately for each of the groups.
With the new interval definition this would often yield undesired
results. Now, the interval on the full datetime variable, ignoring the
groups. If the user would like to allow for differing intervals over the
groups it is advised to use dplyr::do. See also the final
example of pad.
dplyr::group_by
Besides its own argument for grouping, pad does now also
accepts the grouping from dplyr. Making the following two
results equal:
x %>% dplyr::group_by(z) %>% pad x %>% pad(group = ‘z’)
Moreover, both pad and thicken now maintain
the grouping of the input data_frame. The return from both functions
will have the exact same grouping.
break_above
This new argument to pad is a safety net for situations
where the returned dataframe is much larger than the user anticipated.
This would happen when the datetime variable is of a lower interval than
the user thought it was. Before doing the actual padding, the function
estimates the number of rows in the result. If these are above
break_above the function will break.
thickenstart_val are now removed from
the dataset (with a warning). They used to be all mapped to the
start_val.They used to require specification of all the column names that had to filled. This is annoying when many columns had to filled. The functions no longer break when no variable names are specified, but they fill all columns in the data frame.
The new function pad_int does padding of an integer field. Its working is very similar to the general pad. The by argument must always be specified, since a data.frame would almost alway contain multiple numeric columns. Instead of the interval, one can specify the step size by which the integer increases.
Issue #13 When the end_val is specified in
pad, it would mistakenly update the start_val with its
value. This resulted in the return of only the last line of the padded
data.frame, instead of the full padded data.frame.
Issue #14 When dt_var has NULL as timezone, to_posix
(helper of round_thicken, which itself is a helper of
thicken) used to break, and thereby thicken
itself broke.
Issue #24 In pad with grouping, the function will no
longer breaks if for one of the groups the start_val is behind its last
observation, or the end_val is before its first observation. Group is
omitted and warning is thrown. If all groups are omitted, function
breaks with an informative error. The same goes when there is no
grouping.
For determining the interval in pad the
start_val and/or the end_val are taken into
account, if specified. They are concatenated to the datetime variable
before the interval is determined.
Both pad and thicken now throw
informative errors when the start_val or end_val (pad only)
are of the wrong class.
pad has gained a group parameter. This takes a character vector that indicates the column names within which group padding must be done. The returned data frame is complete for the grouping variable(s). Leaving no longer the doubt which record belongs to which group member, especially when start_val and / or end_val was specified.
Issue #8: pad does no longer break when datetime variable contains one value only. Returns x and a warning, if start_val and end_val are NULL and will do proper padding when one or both are specified.
Issue #9: when forgetting to specify at least one column, on which to apply the fill_ function, the fill_ function will now throw a meaningful error.
Issue #10: pad was broken with an error the interval was quarter, month, or year. This was done by check_start_end, even when neither a start_val nor an end_val was specified. It appeared that when concatenating POSIX vectors, as happened in the check_start_end function, the result is enforced to the timezone of the locale (including daylight savings time). This breaks the interval if the original vectors were not of this timezone. Workaround is implemented.
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