How to deal with hourly data in r

[helen1124]

Hi, I am now handling the hourly data in RStudio which is from 2018 and 2022 and the date of my data is like 01/01/2018 HOUR1, 01/01/2018 HOUR2. 01/01/2018 HOUR3 and so on. I would like to ask if I want to plot a boxplot in r, then is it I need to convert my data into yearly data? If I would like to do so, how can I do it? Thanks.

[nirgrahamuk]

Hi, welcome!

We don't really have enough info to help you out. Could you ask this with a minimal REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

If you've never heard of a reprex before, you might want to start by reading this FAQ:

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.…

[rene_at_coco]

Generally speaking, if you had a data table resembling the one I have created below, then you could create a box plot for each hour.

library(tidyverse)

# create sample data
set.seed(234)
(sample_data <- tibble(
  id = seq(1, 100, 1),
  value = rnorm(n = 100, mean = 50, sd = 5),
  date_time = sample(
    seq(ymd_hms("2000-01-01 00:00:01"), ymd_hms("2001-12-31 23:59:59"), 1), 
    size = 100, 
    replace = TRUE)
))
#> # A tibble: 100 × 3
#>       id value date_time          
#>    <dbl> <dbl> <dttm>             
#>  1     1  53.3 2001-10-07 17:43:52
#>  2     2  39.7 2001-12-28 14:13:51
#>  3     3  42.5 2001-04-26 03:33:53
#>  4     4  57.4 2000-12-23 00:36:11
#>  5     5  57.3 2001-09-07 09:27:33
#>  6     6  50.7 2000-12-09 04:38:09
#>  7     7  51.0 2000-08-02 15:33:13
#>  8     8  34.8 2000-06-22 20:12:39
#>  9     9  47.6 2001-10-02 14:31:58
#> 10    10  44.6 2001-01-17 06:22:01
#> # ℹ 90 more rows

# boxplot of value for each hour
sample_data %>%
  mutate(
    hourly = hour(date_time)
  ) %>%
  ggplot() +
  geom_boxplot(
    mapping = aes(
      group = hourly,
      x = hourly,
      y = value
    )
  ) +
  ylim(0, NA)

^{Created on 2024-02-13 with reprex v2.0.2}