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padr is an R package that assists with preparing time series data. It
provides two main functions that will quickly get the data in the format
you want. When data is observed on too low a level, thicken will add a
column of a higher interval to the data frame, after which the user can
apply the appropriate aggregation. When there are missing records for
time points where observations were absent, pad will automatically
insert these records. A number of fill_ functions help to subsequently
fill the missing values.
library(padr)
library(tidyverse)
coffee <- data.frame(
time_stamp = as.POSIXct(c(
'2016-07-07 09:11:21', '2016-07-07 09:46:48',
'2016-07-09 13:25:17',
'2016-07-10 10:45:11'
)),
amount = c(3.14, 2.98, 4.11, 3.14)
)
coffee %>%
thicken('day') %>%
dplyr::group_by(time_stamp_day) %>%
dplyr::summarise(day_amount = sum(amount)) %>%
pad() %>%
fill_by_value(day_amount, value = 0)## # A tibble: 4 × 2
## time_stamp_day day_amount
## <date> <dbl>
## 1 2016-07-07 6.12
## 2 2016-07-08 0
## 3 2016-07-09 4.11
## 4 2016-07-10 3.14
See the the general introduction Vignette for more examples. The
implementation details Vignette describes how padr handles different
time zones and daylight savings time.