I need to use only the last day available in my dataset to aggregate later on but I didn´t have success...
library(tibbletime)
dataset <- data.frame(
timestamp = c("2010-01-01", "2010-01-03", "2010-01-23")
var = c( 1, 4, 11)
)
monthly_dataset <- as_tbl_time(dataset, index = timestamp) %>%
as_period("1 month")
How can I use some function or R package to aggregate my dataset only for using the last day avaiable ?
CodePudding user response:
An option could be the lubridate
package, e.g.
library(lubridate)
library(dplyr)
dataset <- data.frame(
timestamp = c("2010-01-01", "2010-01-03",
"2010-01-23", "2010-02-01", "2010-02-03", "2010-02-23"),
var = c(1, 4, 11, 1, 4, 11)
)
dataset %>%
mutate(month = timestamp %>% ymd() %>% month()) %>%
group_by(month) %>%
slice_tail()
Outcome:
# A tibble: 2 x 3
# Groups: month [2]
timestamp var month
<chr> <dbl> <dbl>
1 2010-01-23 11 1
2 2010-02-23 11 2
CodePudding user response:
The answer from Julian is a nice start, but it won't work across multiple years because the grouping variable doesn't include information about the year.
The typical way to do this is to group on year-month, and then filter to the max date per year-month group.
Also, as the creator of tibbletime I would highly suggest that you no longer use it. It is deprecated and is no longer being supported. You should just use clock/lubridate for date handling alongside the tidyverse packages like dplyr, or you should use tsibble if you really need to go all in on time series.
library(lubridate)
library(dplyr)
dataset <- tibble(
timestamp = c(
"2010-01-01", "2010-01-03", "2010-01-23",
"2010-02-01", "2010-02-03", "2011-02-23"
),
var = c(1, 4, 11, 1, 4, 11)
)
dataset <- mutate(dataset, timestamp = ymd(timestamp))
dataset <- dataset %>%
mutate(
year_month = floor_date(timestamp, "month"),
day = day(timestamp)
)
dataset %>%
group_by(year_month) %>%
filter(day == max(day)) %>%
ungroup()
#> # A tibble: 3 × 4
#> timestamp var year_month day
#> <date> <dbl> <date> <int>
#> 1 2010-01-23 11 2010-01-01 23
#> 2 2010-02-03 4 2010-02-01 3
#> 3 2011-02-23 11 2011-02-01 23
Created on 2022-05-18 by the reprex package (v2.0.1)