time_grid {timeplyr} | R Documentation |
Vector date and datetime functions
Description
These are atomic vector-based functions of the tidy equivalents which all have a "v" suffix to denote this. These are more geared towards programmers and allow for working with date and datetime vectors.
Usage
time_grid(x, timespan = granularity(x), from = NULL, to = NULL)
time_complete_missing(x, timespan = granularity(x))
time_grid_size(x, timespan = granularity(x), from = NULL, to = NULL)
Arguments
x |
Time vector. |
timespan |
|
from |
Start time. |
to |
End time. |
Value
Vectors (typically the same class as x
) of varying lengths depending
on the arguments supplied.
Examples
library(timeplyr)
library(dplyr)
library(lubridate)
library(nycflights13)
x <- unique(flights$time_hour)
# Number of missing hours
time_num_gaps(x)
# Same as above
time_grid_size(x) - length(unique(x))
# Time sequence that spans the data
length(time_grid(x)) # Automatically detects hour granularity
time_grid(x, "month")
time_grid(x, from = floor_date(min(x), "month"), to = today(),
timespan = timespan("month"))
# Complete missing gaps in time using time_complete
y <- time_complete_missing(x, "hour")
identical(y[!y %in% x], time_gaps(x))
# Summarise time into higher intervals
quarters <- time_cut_width(y, "quarter")
interval_count(quarters)
[Package timeplyr version 1.1.0 Index]