On Thu, 6 Apr 2017, Massimo Bressan wrote:
hello
given my reproducible example
#---
date<-seq(ISOdate(2017,1, 1, 0), by="hour", length.out = 48)
v1<-1:48
df<-data.frame(date,v1)
#--
"date" and "df" are functions in base R... best to avoid hiding them by
re-using those names in the global environment
ISOdate forces GMT, which many data sets that you might work with do NOT
use. It is better to use ISOdatetime to avoid letting hidden code
determine the timezone that is applied to (or compared with) your data.
I need to calculate the average of variable v1 at specific hour "endpoints" of
the day: i.e. at hours 6.00 and 22.00 respectively
the desired result is
date v1
01/01/17 22:00 15.5
02/01/17 06:00 27.5
02/01/17 22:00 39.5
at hour 06:00 of each day the average is calculated by considering the 8
previous records (hours from 23:00 to 6:00)
at hour 22:00 of each day the average is calculated by considering the 16
previous records (hours from 7:00 to 22:00)
any hint please?
I've been trying with some functions within the "xts" package but withouth much
result...
I am not sure how I would do this with xts, but the below code is one
fairly literal approach (implemented two ways) to translate your
requirements that is also potentially extensible if the data or
requirements change.
### Base R....
Sys.setenv( TZ = "Etc/GMT+5" ) # selected arbitrarily here but not left to
# the system to decide
dta <- data.frame( datetime = seq( ISOdatetime( 2017,1, 1, 0, 0, 0 )
, by="hour"
, length.out = 48
)
, v1 = 1:48
)
dta$nrec <- 1
dta$date <- as.POSIXct( trunc.POSIXt( dta$datetime, units="days" ) )
dta$tod <- as.numeric( dta$datetime - dta$date, units = "hours" )
dta$timeslot <- factor( ifelse( 6 < dta$tod & dta$tod <= 22
, "Day"
, "Night"
)
, levels = c( "Night", "Day" )
)
dta$slotdatetime <- dta$date + as.difftime( ifelse( "Day" == dta$timeslot
, 22
, ifelse( 22 < dta$tod
, 24+6
, 6
)
)
, units="hours"
)
dta2 <- aggregate( dta[ , c( "v1", "nrec" ) ]
, dta[ , c( "timeslot", "slotdatetime" ), drop=FALSE ]
, FUN = sum
)
dta2 <- subset( dta2, nrec == ifelse( "Day"==timeslot, 16, 8 ) )
dta2$v1mean <- dta2$v1 / dta2$nrec
#### or if you don't mind the tidyverse....
library(dplyr) # wonderland of non-standard evaluation... beware, Alice!
Sys.setenv( TZ = "Etc/GMT+5" ) # selected arbitrarily here but not left to
# the system to decide
dta <- data.frame( datetime = seq( ISOdatetime( 2017,1, 1, 0, 0, 0 )
, by="hour"
, length.out = 48
)
, v1 = 1:48
)
dta2 <- ( dta
%>% mutate( date = as.POSIXct( trunc.POSIXt( datetime
, units="days"
)
)
, tod = as.numeric( datetime - date, units = "hours" )
, timeslot = factor( ifelse( 6 < tod & tod <= 22
, "Day"
, "Night"
)
, levels = c( "Night", "Day" )
)
, slotdatetime = date +
as.difftime( ifelse( "Day" == timeslot
, 22
, ifelse( 22 < tod
, 24+6
, 6
)
)
, units="hours"
)
)
%>% group_by( slotdatetime, timeslot )
%>% summarise( v1mean = mean( v1 )
, nrec = n()
)
%>% filter( nrec == ifelse( "Day"==timeslot, 16, 8 ) )
)
thanks for the help
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