Try Pandas dataframe.

https://www.ncl.ucar.edu/Document/Functions/Contributed/calculate_daily_values.shtml

The two main ways are using the Len() and Sum() in-built functions and using the mean() function from the statistics module.

Example: aggregate(cbind(Min_daily, Max_daily, Rain_daily) ~ day, data=yourData)

Using the tidyverse in R is also an option:

library(tidyverse)

library(lubridate) # great for working with date types

data %>%

# if necessary pull the day of the year out of the full date

mutate(monthday = format(as_date(date), "%d %B")) %>%

# group by the day

group_by(monthday) %>%

# summarise by taking the average across days (omit NA values if necessary)

summarise(mean_temp = mean(temperature))

note:

# if your data is wide (each year a column), you will have to make it long first, e.g.:

pivot_longer(names_to="year", values_to="temperature")

You can do it easily with CDO. "ydaymean" function do exactly what you want. It can be used as "cdo -ydaymean infile.nc outfile.nc". You can check cdo documentation for further functions.