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monthly mean for each month and each year in the data frame

5 messages · Jim Lemon, Rui Barradas, Stefano Sofia

Stefano Sofia
# 
Dear R-list users,
I know that this is a trivial question, but I already wasted quite a large amount of time on that.
I have a data frame with daily data of snow fall. I need to evaluate the monthly mean for each month and each year in the data frame.
Could you help me to find an eficient way for these calculations?

Thank you for your help
Stefano

Here a reproducibile code:

first_day_1 <- as.POSIXct("2019-01-19-00-00", format="%Y-%m-%d-%H-%M")
last_day_1 <- as.POSIXct("2019-03-20-00-00", format="%Y-%m-%d-%H-%M")
df1 <- data.frame(data_POSIX=seq(first_day_1, last_day_1, by="1 days"))
df1$value <- runif(nrow(df1), 0, 10)


first_day_2 <- as.POSIXct("2020-02-19-00-00", format="%Y-%m-%d-%H-%M")
last_day_2 <- as.POSIXct("2020-04-20-00-00", format="%Y-%m-%d-%H-%M")
df2 <- data.frame(data_POSIX=seq(first_day_2, last_day_2, by="1 days"))
df2$value <- runif(nrow(df2), 0, 10)

df <- rbind(df1, df2)





         (oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
---Oo---------oO----------------

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Jim Lemon
# 
Hi Stefano,
What about this?

df$months<-format(df$data_POSIX,"%Y-%m")
snow_means<-by(df$value,df$months,mean)

Jim

On Mon, Sep 14, 2020 at 8:19 PM Stefano Sofia
<stefano.sofia at regione.marche.it> wrote:
Stefano Sofia
# 
Yes, perfect.
Thank you.

Stefano

         (oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
---Oo---------oO----------------
Rui Barradas
# 
Hello,

Here are two aggregate options, the first base R only, the second one 
with package zoo.


year_month <- format(df$data_POSIX, "%Y-%m")
aggregate(value ~ year_month, df, mean)    # or even value ~ format(etc)
#  year_month    value
#1    2019-01 6.430922
#2    2019-02 4.846731
#3    2019-03 4.968503
#4    2020-02 6.484031
#5    2020-03 4.910305
#6    2020-04 4.906575


aggregate(value ~ zoo::as.yearmon(data_POSIX), df, mean)
#  zoo::as.yearmon(data_POSIX)    value
#1                    jan 2019 6.430922
#2                    fev 2019 4.846731
#3                    mar 2019 4.968503
#4                    fev 2020 6.484031
#5                    mar 2020 4.910305
#6                    abr 2020 4.906575


Hope this helps,

Rui Barradas

?s 11:19 de 14/09/20, Stefano Sofia escreveu:
Stefano Sofia
# 
Thank you again.
I finally used aggregate because it build a data frame straight away.

Stefano

         (oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
---Oo---------oO----------------