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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)
<- data.frame(
coffee 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') %>%
::group_by(time_stamp_day) %>%
dplyr::summarise(day_amount = sum(amount)) %>%
dplyrpad() %>%
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.