This is my first question and I'm also a very new learner to r so please bear with me. I am working on some gauge data from about 4 months and it took temperature readings every 15 minutes. I am wanting to get a daily average from this data and then graph it. I have looked some stuff up and tried to run what people have suggested, but keep running into this error:
library(lubridate)
library(dplyr)
DownGauge %>%
+ group_by(day = day(date)) %>%
+ summarise(mean_Temperature = mean(Temperature))
**Error in `group_by()`:
ℹ In argument: `day = day(date)`.
Caused by error in `as.POSIXlt.default()`:
! do not know how to convert 'x' to class “POSIXlt”**
Any help would be much appreciated. I am really struggling to find a good answer to this question. I have included the dput and head of my data below because I saw that is good policy to provide. Let me know if anything else is needed. Thanks.
dput(head(DownGauge))
structure(list(Date = structure(c(1709770500, 1709771400, 1709772300,
1709773200, 1709774100, 1709775000), tzone = "UTC", class = c("POSIXct",
"POSIXt")), Temperature = c(8, 7.9, 7.9, 7.9, 7.9, 7.9)), row.names = c(NA,
-6L), class = c("tbl_df", "tbl", "data.frame"))
head(DownGauge)
# A tibble: 6 × 2
Date Temperature
<dttm> <dbl>
1 2024-03-07 00:15:00 8
2 2024-03-07 00:30:00 7.9
3 2024-03-07 00:45:00 7.9
4 2024-03-07 01:00:00 7.9
5 2024-03-07 01:15:00 7.9
6 2024-03-07 01:30:00 7.9`
I tried to change the as.POSIXlt to as.POSIXct cause I thought that would fix it but when I created a new data frame with the changed date format, it just switched automatically back to as.POSIXlt. Not sure why.
You are interested in grouping the date. ie if you group by day(date) then 1st of every month would be grouped together and thats incorrect. Consider using the following:
DownGauge %>%
group_by(Date = as.Date(Date)) %>%
summarise(mean_temp = mean(Temperature))
# A tibble: 1 × 2
Date mean_temp
<date> <dbl>
1 2024-03-07 7.92