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Accessing objects using variable strings in R

Edit: Thanks to those who answered so far; I am very new to R and just took on a big project for my graduate school, so I'm a bit overloaded with initial processing. The data I use is as follows (from publicly available precipitation data in WMO):


120 6272100 KHARTOUM 15.60 32.55 382 1899 1989 0.0
1899 0.03 0.03 0.03 0.03 0.03 1.03 13.03 12.03 9999 6.03 0.03 0.03
1900 0.03 0.03 0.03 0.03 0.03 23.03 80.03 47.03 23.03 8.03 0.03 0.03
1901 0.03 0.03 0.03 0.03 0.03 17.03 23.03 17.03 0.03 8.03 0.03 0.03
(...)
120 6272101 JEBEL AULIA 15.20 32.50 380 1920 1988 0.0
1920 0.03 0.03 0.03 0.00 0.03 6.90 20.00 108.80 47.30 1.00 0.01 0.03
1921 0.03 0.03 0.03 0.00 0.03 0.00 88.00 57.00 35.00 18.50 0.01 0.03
1922 0.03 0.03 0.03 0.00 0.03 0.00 87.50 102.30 10.40 15.20 0.01 0.03
(...)

There are ~ 100 observation stations that I'm interested in, each of which has a varying start and end date for rainfall measurements. They're formatted as above in a single data file, with stations separated by "120 (station number) (station name)".

I need first to separate this file by station, then to extract March, April, May and June for each year, then take a total of these months for each year. So far I'm messing around with loops (as below), but I understand this isn't the right way to go about it and would rather learn some better technique. Thanks again for the help!

(Original question:) I've got a large data set containing rainfall by season for ~100 years over 100+ locations. I'm trying to separate this data into more managable arrays, and in particular I want to retrieve the sum of the rainfall for March, April, May and June for each station for each year. The following is a simplified version of my code so far:

a <- array(1,dim=c(10,12))
for (i in 1:5) {

  all data:
  assign(paste("station_",i,sep=""), a)

  #march - june data:
  assign(paste("station_",i,"_mamj",sep=""), a[,4:7])
}

, station_(i)__mamj_, , . station_(i)_mamj_tot. , , station_ (i) _mamj, i . !

+3
3

, ddply ( ):

tot_mamj <- ddply(rain[rain$month %in% 3:6,-2], 'year', colwise(sum))

M/A/M/J :

   year station_1 station_2 station_3 station_4 station_5 ...
1  1972  8.618960  5.697739 10.083192  9.264512 11.152378 ...
2  1973 18.571748 18.903280 11.832462 18.262272 10.509621 ...
3  1974 22.415201 22.670821 32.850745 31.634717 20.523778 ...
4  1975 16.773286 17.683704 18.259066 14.996550 19.007762 ...
...

. dataframe, col.names - 'station_n'; (, , , . ). ( plyr split-apply-comb):

require(plyr) # for d*ply, summarise
#require(reshape) # for melt

# Parameterize everything here, it crucial for testing/debugging
all_years <- c(1970:2011)
nYears <- length(all_years)  
nStations <- 101
# We want station names as vector of chr (as opposed to simple indices)
station_names <- paste ('station_', 1:nStations, sep='')

rain <- data.frame(cbind(
  year=rep(c(1970:2011),12),
  month=1:12
))
# Fill in NAs for all data
rain[,station_names] <- as.numeric(NA)
# Make 'month' a factor, to prevent any numerical funny stuff e.g accidentally 'aggregating' it
rain$month <- factor(rain$month)

# For convenience, store the row indices for all years, M/A/M/J
I.mamj <- which(rain$month %in% 3:6)

# Insert made-up seasonal data for M/A/M/J for testing... leave everything else NA intentionally
rain[I.mamj,station_names] <- c(3,5,9,6) * runif(4*nYears*nStations)

# Get our aggregate of MAMJ totals, by year
# The '-2' column index means: "exclude month, to prevent it also getting 'aggregated'"
excludeMonthCol = -2
tot_mamj <- ddply(rain[rain$month %in% 3:6, excludeMonthCol], 'year', colwise(sum))

# voila!!
#    year station_1 station_2 station_3 station_4 station_5
# 1  1972  8.618960  5.697739 10.083192  9.264512 11.152378
# 2  1973 18.571748 18.903280 11.832462 18.262272 10.509621
# 3  1974 22.415201 22.670821 32.850745 31.634717 20.523778
# 4  1975 16.773286 17.683704 18.259066 14.996550 19.007762

, , , "" ( "-2": ). , , , , , ( ):

 ddply(rain[rain$month %in% 3:6, ], 'year', colwise(sum))
Error in Summary.factor(c(3L, 3L, 3L, 3L, 3L, 3L), na.rm = FALSE) : 
  sum not meaningful for factors
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get():

i <- 10
var <- paste("test", i, sep="_")
assign(10, var)
get(var)

, , , , ( IMO assign/get , eval (parse))

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assign station1, station2, station_3_mamj ..? , stations[[1]], stations[[2]], stations_mamj[[3]] .. , .

, , , , .

ETA: , , :

eval(parse(text=paste("station", i, "mamj", sep="_")))

eval , .

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