Hello,
Something like this?
dat <-
structure(list(st = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), .Label = c("Sa", "Ta"), class = "factor"), year = c(1966L,
1966L, 1966L, 1966L, 1966L, 1966L, 1966L, 1966L, 1966L, 1967L,
1967L, 1967L, 1967L, 1967L, 1967L, 1967L, 1967L, 1967L, 1968L,
1968L, 1968L, 1968L, 1968L, 1968L, 1968L, 1968L, 1968L, 1969L,
1969L, 1969L, 1969L, 1969L, 1969L, 1969L, 1969L, 1969L, 1955L,
1955L, 1955L, 1955L, 1955L, 1955L, 1955L, 1955L, 1955L, 1956L,
1956L, 1956L, 1956L, 1956L, 1956L, 1956L, 1956L, 1956L, 1957L,
1957L, 1957L, 1957L, 1957L, 1957L, 1957L, 1957L, 1957L, 1957L,
1958L, 1958L, 1958L, 1958L, 1958L, 1958L, 1958L, 1958L), month = c(1L,
1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L,
3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L,
5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L, 10L,
10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L), day = c(1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
2L, 3L, 1L, 2L, 3L), population = c(2.4, 2.4, 2.4, 2.4, 2.4,
2.4, 2.3, 2.2, 2.3, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4,
2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.3, 2.2, 2.3, 2.4, 2.4, 2.4, 2.4,
2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.3, 2.2,
2.3, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4,
2.4, 2.4, 2.4, 2.3, 2.2, 2.3, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4, 2.4,
2.4, 2.4)), .Names = c("st", "year", "month", "day", "population"
), class = "data.frame", row.names = c(NA, -72L))
agg <- aggregate(population ~ st + year + month, data = dat, FUN = mean)
reshape(agg, direction = "wide",
idvar = c("st", "month"),
timevar = "year",
v.names = "population")
Hope this helps,
Rui Barradas
Em 17-12-2012 17:11, eliza botto escreveu:
> Dear R users,
> [in case the format of email is changed or you dont finf it easy to
> understand, i have attached a text file of my question]
> i have the data in the following format and i want to convert it in the
> format given at the end.
> Ta ans Sa are the names of certain cities. there are 69 cities in my
> data.
> column 1 is representing station name (i am writing the data of only
> two cities for simplicity but actually, as i wrote, i have 69 cities
> and the actuall table runs down very deep.)
> Column 2 represnts the year for which the data is given (Actuall data
> for each station is of different length but atleast of 24 years).
> Column 3 and 4 reprent the month and the day of the data. obviously
> each year has 12 months and each month as different number of days, but
> to make table easily understable only 3 months and 3 days of each month
> are considered. febrary for leap years should also be considered.
> col5 represents population of that city
>
> st. year month day population in million
> Ta 1966 1 1 2.4
> Ta 1966 1 2 2.4
> Ta 1966 1 3 2.4
> Ta 1966 2 1 2.4
> Ta 1966 2 2 2.4
> Ta 1966 2 3 2.4
> Ta 1966 3 1 2.3
> Ta 1966 3 2 2.2
> Ta 1966 3 3 2.3
> Ta 1967 1 1 2.4
> Ta 1967 1 2 2.4
> Ta 1967 1 3 2.4
> Ta 1967 2 1 2.4
> Ta 1967 2 2 2.4
> Ta 1967 2 3 2.4
> Ta 1967 3 1 2.4
> Ta 1967 3 2 2.4
> Ta 1967 3 3 2.4
> Ta 1968 1 1 2.4
> Ta 1968 1 2 2.4
> Ta 1968 1 3 2.4
> Ta 1968 2 1 2.4
> Ta 1968 2 2 2.4
> Ta 1968 2 3 2.4
> Ta 1968 3 1 2.3
> Ta 1968 3 2 2.2
> Ta 1968 3 3 2.3
> Ta 1969 1 1 2.4
> Ta 1969 1 2 2.4
> Ta 1969 1 3 2.4
> Ta 1969 2 1 2.4
> Ta 1969 2 2 2.4
> Ta 1969 2 3 2.4
> Ta 1969 3 1 2.4
> Ta 1969 3 2 2.4
> Ta 1969 3 3 2.4
> Sa 1955 1 1 2.4
> Sa 1955 1 2 2.4
> Sa 1955 1 3 2.4
> Sa 1955 2 1 2.4
> Sa 1955 2 2 2.4
> Sa 1955 2 3 2.4
> Sa 1955 3 1 2.3
> Sa 1955 3 2 2.2
> Sa 1955 3 3 2.3
> Sa 1956 4 1 2.4
> Sa 1956 4 2 2.4
> Sa 1956 4 3 2.4
> Sa 1956 5 1 2.4
> Sa 1956 5 2 2.4
> Sa 1956 5 3 2.4
> Sa 1956 6 1 2.4
> Sa 1956 6 2 2.4
> Sa 1956 6 3 2.4
> Sa 1957 7 1 2.4
> Sa 1957 7 2 2.4
> Sa 1957 7 3 2.4
> Sa 1957 8 1 2.4
> Sa 1957 8 2 2.4
> Sa 1957 8 3 2.4
> Sa 1957 9 1 2.3
> Sa 1957 9 2 2.2
> Sa 1957 9 3 2.3
> Sa 1957 10 1 2.4
> Sa 1958 10 2 2.4
> Sa 1958 10 3 2.4
> Sa 1958 11 1 2.4
> Sa 1958 11 2 2.4
> Sa 1958 11 3 2.4
> Sa 1958 12 1 2.4
> Sa 1958 12 2 2.4
> Sa 1958 12 3 2.4
> ...
> ...
> uptill 69th station
>
> i want to convert the data in following format
>> Ta ## matrix for station Ta
> 1966 1967 1968 1969
> AVERAGE OF MONTH 1 AVERAGE OF MONTH 1 AVERAGE OF MONTH 1 AVERAGE OF MONTH 1
> AVERAGE OF MONTH 2 AVERAGE OF MONTH 2 AVERAGE OF MONTH 2 AVERAGE OF MONTH 2
> AVERAGE OF MONTH 3 AVERAGE OF MONTH 3 AVERAGE OF MONTH 3 AVERAGE OF MONTH 3
> ........
> ........
> AVERAGE OF MONTH 12 AVERAGE OF MONTH 12 AVERAGE OF MONTH 12 AVERAGE OF MONTH
> 12
> similar operation are to be done for "Sa" and the remaining 67
> stations...
> which means i want to have 69 matrices, in which each column (number of
> columns should be equal to number of years of data) should contain 12
> mean monthly values of population of each year.
>
> thanks in advance
>
> eliza
>
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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and provide commented, minimal, self-contained, reproducible code.
