Aggregating minutes data to hour

[Shubhradev]

Hello there,
I have a dataset looking like that mentions below

I want to transform the minute's data to hourly data by adding the values having the same hour on their time index. In one word, I need to group them according to an hour. I have tried several aggregate functions but can't find the desired value. Some of them are giving only integer values and some of them are giving wrong. How can I get the aggregate value according to an hour from here?

Thanks in advance.

**I am in the learning phase of R programming

[williaml]

Hi, you can use lubridate and do something like this:
Aggregation of 15-min to hourly for each day-month-year - tidyverse - RStudio Community

Also, next time please post your code and a reproducible example (not a screenshot).

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[duringju211]

library(tidyverse)
library(lubridate)

tibble(
  timestamp = now() - dminutes(sample(1:1440, 100))) |>
  mutate(hour = floor_date(timestamp, "hours")) |>
  count(hour)
#> # A tibble: 24 × 2
#>    hour                    n
#>    <dttm>              <int>
#>  1 2022-09-28 09:00:00     3
#>  2 2022-09-28 10:00:00     6
#>  3 2022-09-28 11:00:00     2
#>  4 2022-09-28 12:00:00     3
#>  5 2022-09-28 13:00:00     8
#>  6 2022-09-28 14:00:00     1
#>  7 2022-09-28 15:00:00     2
#>  8 2022-09-28 16:00:00     9
#>  9 2022-09-28 17:00:00     3
#> 10 2022-09-28 18:00:00     6
#> # … with 14 more rows

^{Created on 2022-09-29 with reprex v2.0.2}