mean of each month in data

aggwide <- reshape(agg, direction = "wide", idvar = c("st", "month"),

aggsplit <- split(aggwide[,colnames(aggwide)!="st"], aggwide$st)
aggsplit

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of Rui Barradas
Sent: Monday, December 17, 2012 12:06 PM
To: eliza botto
Cc: r-help at r-project.org
Subject: Re: [R] mean of each month in data

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

guide.html

	[[alternative HTML version deleted]]