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Convert data frame to monthly time series

I have a data frame of monthly data for 100 years (1200 data points) with months in columns and years in rows. I want to convert it to a monthly time series, and I tried several ways, none of which create the correct “temporary” structure.

The problem is that R considers the data frame as 100 observations (years) out of 12 variables (months). Here is the reproducible code for my last attempt:

set.seed(12)
dummy.df <- as.data.frame(matrix(round(rnorm(1200),digits=2),nrow=100,ncol=12))
rownames(dummy.df) <- seq(from=1901, to=2000)
colnames(dummy.df) <- c("jan","feb","mar","apr","may","jun","jul","aug","sep","oct","nov","dec")
dummy.df.ts <- ts(as.vector(as.matrix(dummy.df)), start=c(1901,1), end=c(2000,12), frequency=12)

In the "dummy.df.ts" object, rows and columns are switched, and instead of consecutive observations in the columns, all are January February, etc. stack with each other one by one. How can I get the correct time structure?

An example of my data: these are monthly temperature values ​​from 1901 to 1905.

fr.monthly.temp.sample  

     JAN FEB MAR  APR  MAY  JUN  JUL  AUG  SEP  OCT NOV DEC  
1901 2.7 0.4 4.7 10.0 13.0 16.9 19.2 18.3 15.7 10.6 4.9 3.5  
1902 4.1 3.2 7.5 10.3 10.0 15.1 18.2 17.4 15.0 10.2 6.3 3.5  
1903 3.8 5.9 7.6  7.1 12.9 14.9 17.6 17.3 15.5 12.1 6.9 2.7  
1904 3.0 4.6 5.5 10.3 13.6 16.3 20.2 18.5 13.9 11.2 5.4 4.8  
1905 1.7 4.0 7.4  9.3 11.9 16.5 20.0 17.6 14.7  8.4 5.5 3.8

Plot of original time series

ts():

fr.monthly.temp.sample.ts <- ts(as.vector(as.matrix(fr.monthly.temp.sample)),                              start=c(1901,1), end=c(1905,12), frequency=12)

, :

fr.monthly.temp.sample.ts  

      Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec  
1901  2.7  4.1  3.8  3.0  1.7  0.4  3.2  5.9  4.6  4.0  4.7  7.5  
1902  7.6  5.5  7.4 10.0 10.3  7.1 10.3  9.3 13.0 10.0 12.9 13.6  
1903 11.9 16.9 15.1 14.9 16.3 16.5 19.2 18.2 17.6 20.2 20.0 18.3  
1904 17.4 17.3 18.5 17.6 15.7 15.0 15.5 13.9 14.7 10.6 10.2 12.1  
1905 11.2  8.4  4.9  6.3  6.9  5.4  5.5  3.5  3.5  2.7  4.8  3.8

Plot of time series from R code

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(function t()) :

set.seed(12)
dummy.df <- as.data.frame(matrix(round(rnorm(1200), digits = 2),
                                 nrow = 100, ncol = 12))
rownames(dummy.df) <- seq(1901, 2000)
colnames(dummy.df) <- month.abb
dummy.df.ts <- ts(as.vector(t(as.matrix(dummy.df))), 
                  start=c(1901,1), end=c(2000,12), frequency=12)

2

, , ts().

. - , month.abb, .

set.seed(12)
dummy.df <- as.data.frame(matrix(round(rnorm(1200),digits=2),nrow=100,ncol=12))
months <- format(seq.Date(as.Date("2013-01-01"), as.Date("2013-12-01"), 
                          by = "month"), format = "%b")
colnames(dummy.df) <- months
dummy.df$Year <- seq(1901, 2000) # set as variable, not as rownames

, 1200 , :

library("reshape2")
dummy.df <- melt(dummy.df, id.vars = "Year")

:

dummy.df$Date <- as.Date(paste(dummy.df$Year, dummy.df$variable, "01", sep = "-"),
                         format = ("%Y-%b-%d"))
dummy.df <- dummy.df[order(dummy.df$Date), ]

ts(), ts :

dummy.df.ts <- ts(dummy.df$value, start=c(1901,1), end=c(2000,12), frequency=12)
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