You can just use the same code that I provided before but now use your
dataset. Like this
df <- read.csv(file="data2.csv",header=TRUE)
dates <- as.Date(paste(df$year,"-01-01",sep=""))
myXts <- xts(df,order.by=dates)
head(myXts)
#The last command "head(myXts)" shows you the first few rows of the
xts
object
year cnsm incm wlth
1980-01-01 1980 173.6527 53.3635 60.3013
1981-01-01 1981 175.4613 53.6929 60.4980
1982-01-01 1982 174.5724 53.4890 60.2358
1983-01-01 1983 171.5070 53.2223 60.1047
1984-01-01 1984 173.3462 53.2851 60.6946
1985-01-01 1985 171.7075 53.1596 60.7598
On Sat, Sep 16, 2017 at 9:55 AM, Berend Hasselman <bhh at xs4all.nl>
wrote:
>
> > On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com>
wrote:
> >
> > hello to all. I am working on macroeconomic data series of India,
which
> in
> > a yearly basis. I am unable to convert my data frame into time series.
> > kindly help me.
> > also using zoo and xts packages. but they take only monthly
observations.
> >
> > 'data.frame': 30 obs. of 4 variables:
> > $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ...
> > $ cnsm: num 174 175 175 172 173 ...
> > $ incm: num 53.4 53.7 53.5 53.2 53.3 ...
> > $ wlth: num 60.3 60.5 60.2 60.1 60.7 ...
> > --
>
> Second try to do what you would like (I hope and think)
> Using Eric's sample data
>
> <code>
> zdf <- data.frame(year=2001:2010, cnsm=sample(170:180,10,replace=TRUE),
> incm=rnorm(10,53,1), wlth=rnorm(10,60,1))
> zdf
>
> # R ts
> zts <- ts(zdf[,-1], start=zdf[1,"year"])
> zts
>
> # turn data into a zoo timeseries and an xts timeseries
>
> library(zoo)
> z.zoo <- as.zoo(zts)
> z.zoo
>
> library(xts)
> z.xts <- as.xts(zts)
> z.xts
> </code>
>
> Berend Hasselman
>
> > Yadawananda Neog
> > Research Scholar
> > Department of Economics
> > Banaras Hindu University
> > Mob. 9838545073
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
[[alternative HTML version deleted]]
oky.. thank you very much to all of you On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at gmail.com> wrote:> You can just use the same code that I provided before but now use your > dataset. Like this > > df <- read.csv(file="data2.csv",header=TRUE) > dates <- as.Date(paste(df$year,"-01-01",sep="")) > myXts <- xts(df,order.by=dates) > head(myXts) > > #The last command "head(myXts)" shows you the first few rows of the xts > object > year cnsm incm wlth > 1980-01-01 1980 173.6527 53.3635 60.3013 > 1981-01-01 1981 175.4613 53.6929 60.4980 > 1982-01-01 1982 174.5724 53.4890 60.2358 > 1983-01-01 1983 171.5070 53.2223 60.1047 > 1984-01-01 1984 173.3462 53.2851 60.6946 > 1985-01-01 1985 171.7075 53.1596 60.7598 > > > On Sat, Sep 16, 2017 at 9:55 AM, Berend Hasselman <bhh at xs4all.nl> wrote: > >> >> > On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: >> > >> > hello to all. I am working on macroeconomic data series of India, which >> in >> > a yearly basis. I am unable to convert my data frame into time series. >> > kindly help me. >> > also using zoo and xts packages. but they take only monthly >> observations. >> > >> > 'data.frame': 30 obs. of 4 variables: >> > $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... >> > $ cnsm: num 174 175 175 172 173 ... >> > $ incm: num 53.4 53.7 53.5 53.2 53.3 ... >> > $ wlth: num 60.3 60.5 60.2 60.1 60.7 ... >> > -- >> >> Second try to do what you would like (I hope and think) >> Using Eric's sample data >> >> <code> >> zdf <- data.frame(year=2001:2010, cnsm=sample(170:180,10,replace=TRUE), >> incm=rnorm(10,53,1), wlth=rnorm(10,60,1)) >> zdf >> >> # R ts >> zts <- ts(zdf[,-1], start=zdf[1,"year"]) >> zts >> >> # turn data into a zoo timeseries and an xts timeseries >> >> library(zoo) >> z.zoo <- as.zoo(zts) >> z.zoo >> >> library(xts) >> z.xts <- as.xts(zts) >> z.xts >> </code> >> >> Berend Hasselman >> >> > Yadawananda Neog >> > Research Scholar >> > Department of Economics >> > Banaras Hindu University >> > Mob. 9838545073 >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide http://www.R-project.org/posti >> ng-guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> >> ______________________________________________ >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posti >> ng-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > >-- Yadawananda Neog Research Scholar Department of Economics Banaras Hindu University Mob. 9838545073 [[alternative HTML version deleted]]
Assuming the input data.frame, DF, is of the form shown reproducibly
in the Note below, to convert the series to zoo or ts:
library(zoo)
# convert to zoo
z <- read.zoo(DF)
# convert to ts
as.ts(z) #
Note:
DF <- structure(list(year = c(1980, 1981, 1982, 1983, 1984), cnsm = c(174,
175, 175, 172, 173), incm = c(53.4, 53.7, 53.5, 53.2, 53.3),
with = c(60.3, 60.5, 60.2, 60.1, 60.7)), .Names = c("year",
"cnsm", "incm", "with"), row.names = c(NA, -5L),
class = "data.frame")
On Sat, Sep 16, 2017 at 8:10 AM, yadav neog <yadavneog at gmail.com>
wrote:> oky.. thank you very much to all of you
>
>
> On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at
gmail.com> wrote:
>
>> You can just use the same code that I provided before but now use your
>> dataset. Like this
>>
>> df <- read.csv(file="data2.csv",header=TRUE)
>> dates <- as.Date(paste(df$year,"-01-01",sep=""))
>> myXts <- xts(df,order.by=dates)
>> head(myXts)
>>
>> #The last command "head(myXts)" shows you the first few rows
of the xts
>> object
>> year cnsm incm wlth
>> 1980-01-01 1980 173.6527 53.3635 60.3013
>> 1981-01-01 1981 175.4613 53.6929 60.4980
>> 1982-01-01 1982 174.5724 53.4890 60.2358
>> 1983-01-01 1983 171.5070 53.2223 60.1047
>> 1984-01-01 1984 173.3462 53.2851 60.6946
>> 1985-01-01 1985 171.7075 53.1596 60.7598
>>
>>
>> On Sat, Sep 16, 2017 at 9:55 AM, Berend Hasselman <bhh at
xs4all.nl> wrote:
>>
>>>
>>> > On 15 Sep 2017, at 11:38, yadav neog <yadavneog at
gmail.com> wrote:
>>> >
>>> > hello to all. I am working on macroeconomic data series of
India, which
>>> in
>>> > a yearly basis. I am unable to convert my data frame into time
series.
>>> > kindly help me.
>>> > also using zoo and xts packages. but they take only monthly
>>> observations.
>>> >
>>> > 'data.frame': 30 obs. of 4 variables:
>>> > $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989
...
>>> > $ cnsm: num 174 175 175 172 173 ...
>>> > $ incm: num 53.4 53.7 53.5 53.2 53.3 ...
>>> > $ wlth: num 60.3 60.5 60.2 60.1 60.7 ...
>>> > --
>>>
>>> Second try to do what you would like (I hope and think)
>>> Using Eric's sample data
>>>
>>> <code>
>>> zdf <- data.frame(year=2001:2010,
cnsm=sample(170:180,10,replace=TRUE),
>>> incm=rnorm(10,53,1), wlth=rnorm(10,60,1))
>>> zdf
>>>
>>> # R ts
>>> zts <- ts(zdf[,-1], start=zdf[1,"year"])
>>> zts
>>>
>>> # turn data into a zoo timeseries and an xts timeseries
>>>
>>> library(zoo)
>>> z.zoo <- as.zoo(zts)
>>> z.zoo
>>>
>>> library(xts)
>>> z.xts <- as.xts(zts)
>>> z.xts
>>> </code>
>>>
>>> Berend Hasselman
>>>
>>> > Yadawananda Neog
>>> > Research Scholar
>>> > Department of Economics
>>> > Banaras Hindu University
>>> > Mob. 9838545073
>>> >
>>> > [[alternative HTML version deleted]]
>>> >
>>> > ______________________________________________
>>> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>> > https://stat.ethz.ch/mailman/listinfo/r-help
>>> > PLEASE do read the posting guide
http://www.R-project.org/posti
>>> ng-guide.html
>>> > and provide commented, minimal, self-contained, reproducible
code.
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posti
>>> ng-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>
>
>
> --
> Yadawananda Neog
> Research Scholar
> Department of Economics
> Banaras Hindu University
> Mob. 9838545073
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> 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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