I have a data frame with hourly data running over 5 years. I want to calculate the hourly mean (ie, the mean value for every hour of the day, 1:24) of values between two dates (eg, 15-March to 15-Apr) over several years, and compare that to the hourly mean of the last year.
Here is an example of the data:
start = as.POSIXct(strptime("2011-01-01 01:00", "%Y-%m-%d %H:%M"))
end = as.POSIXct(strptime("2016-01-01 01:00", "%Y-%m-%d %H:%M"))
df = data.frame(DateTime = seq(from = start, to = end,by = "hours"))
df$value = runif(nrow(df))
Start_Period = "03-15"
End_Period = "04-15"
The output should look like:
Hour mean(2011-2014) mean(2015)
1 0.3 0.5
...
24 0.8 0.6
We can filter
based on the 'start', 'end' date, then do a group by 'hour' 'year' and get the mean
library(lubridate)
library(dplyr)
df %>%
filter((day(DateTime) >= 15 & month(DateTime) == 3)|
(day(DateTime) <= 15 & month(DateTime) == 4)) %>%
group_by(hour = hour(DateTime), year = year(DateTime)) %>%
summarise(value = mean(value))
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.