[R] How to read a file with two data sets in text format

Janesh Devkota
2013-01-21T08:19:48Z

I was able to read the data using the following code:

jd1 <-
read.table('Practicedata.dat',header=T,sep="\t",nrow=6240)
jd2 <-
read.table('Practicedata.dat',header=T,sep="\t",skip=6241)
colnames(jd1) <- c("Date","Mod")
colnames(jd2) <- c("Date", "Obs")
p <- ggplot(jd1,aes(x=Date,y=Mod))+geom_line()
p <- p + geom_line(data=jd2,aes(x=Date,y=Obs),color="red")
p


Now, I want to make a scatter plot between jd1$Mod and jd2$Obs. But I
cannot create one since both of them have different number of rows. Since I
have less number of rows for Mod I am planning to use the date of Mod and
then find the corresponding values of Obs for those time periods. How can I
find the corresponding values of Obs for the give date in jd1 ?

Or is there any way to create a scatter plot and put the regression
equation and correlation coefficient.

Thank you so much.

Best Regards,
Janesh


On Mon, Jan 21, 2013 at 1:19 AM, Jd Devkota
<janesh.devkota@gmail.com>wrote:

> Hello All,
>
> I have a data file in a text format and there are two data sets. The data
> set are continuous.
> For each data set there is a header which has the number of data rows and
> the name of data series.
> For example first data set has "6240 Terry Cove-Model". Then the
data for
> that series follows upto 6240 rows. Then another data would start and it
> will have the header such as "5200 Terry-Observed"
>
> The sample data would look like:
>
> 6240 Terry Cove-Model
> 300 .300110459327698
> 300.041656494141 .289277672767639
> 300.083343505859 .276237487792969
> 300.125 .258902788162231
> 300.166656494141 .236579895019531
> 300.208343505859 .221315026283264
> 300.25 .214318037033081
> 300.291656494141 .190926909446716
> 300.333343505859 .158144593238831
> 300.375 .113302707672119
> 300.416656494141 .103684902191162
> 300.458343505859 9.72903966903687E-02
> 300.5 8.76948833465576E-02
> 300.541656494141 8.42459201812744E-02
> 300.583343505859 .078397274017334
> 300.625 8.44632387161255E-02
> 300.666656494141 9.32939052581787E-02
> 300.708343505859 .113663911819458
> 300.75 .123064398765564
> 300.791656494141 .157548069953918
> 300.833343505859 .148393034934998
> 300.875 .135645747184753
> 300.916656494141 .137590646743774
> 300.958343505859 .133154153823853
> 301 .131152510643005
> 301.041656494141 .114152908325195
> 301.083343505859 8.04083347320557E-02
> 301.125 5.53587675094604E-02
> 301.166656494141 3.17397117614746E-02
> 301.208343505859 4.07266616821289E-03
> 301.25 -2.15455293655396E-02
> 301.291656494141 -4.07489538192749E-02
> 301.333343505859 -5.85414171218872E-02
> 301.375 -7.53517150878906E-02
> 301.416656494141 -8.49723815917969E-02
> 301.458343505859 -7.91778564453125E-02
> 301.5 -7.02846050262451E-02
> 301.541656494141 -7.24701881408691E-02
> 301.583343505859 -7.76907205581665E-02
> 301.625 -6.82642459869385E-02
>  62401 Terry Cove-Data
> 300 .216407993
> 300.0042 .204216005
> 300.0083 .210311999
> 300.0125 .195071996
> 300.0167 .192023999
> 300.0208 .179831992
> 300.025 .188976001
> 300.0292 .185928004
> 300.0333 .195071996
> 300.0375 .219456009
> 300.0417 .210311999
> 300.0458 .204216005
> 300.05 .195071996
> 300.0542 .188976001
> 300.0583 .195071996
> 300.0625 .195071996
> 300.0667 .185928004
> 300.0708 .173735998
> 300.075 .170688001
> 300.0792 .167640004
> 300.0833 .167640004
> 300.0875 .167640004
> 300.0917 .167640004
> 300.0958 .161543991
> 300.1 .1524
> 300.1042 .158495994
> 300.1083 .149352003
> 300.1125 .158495994
> 300.1167 .1524
> 300.1208 .1524
> 300.125 .149352003
> 300.1292 .143256
> 300.1333 .146303997
> 300.1375 .149352003
> 300.1417 .146303997
> 300.1458 .137159996
> 300.15 .131064002
> 300.1542 .124967999
> 300.1583 .128015996
> 300.1625 .124967999
> 300.1667 .131064002
> 300.1708 .124967999
> 300.175 .124967999
> 300.1792 .134111999
> 300.1833 .118871996
> 300.1875 .128015996
> 300.1917 .131064002
> 300.1958 .128015996
> 300.2 .131064002
> 300.2042 .128015996
> 300.2083 .121920002
> 300.2125 .115823999
> 300.2167 .112776001
> 300.2208 .103632001
> 300.225 .097535998
> 300.2292 .103632001
> 300.2333 .094488001
> 300.2375 .082296003
> 300.2417 .0762
> 300.2458 .079247997
> 300.25 .067056
> 300.2542 .064007998
> 300.2583 .045720002
> 300.2625 .033528
> 300.2667 .036575999
> 300.2708 .036575999
> 300.275 .036575999
> 300.2792 .027432001
> 300.2833 .027432001
> 300.2875 .021336
> 300.2917 .012192
> 300.2958 .009144
> 300.3 .009144
> 300.3042 .003048
> 300.3083 0
> 300.3125 -.003048
> 300.3167 -.006096
> 300.3208 0
> 300.325 .006096
> 300.3292 -.003048
> 300.3333 .006096
>
> The full data set can be downloaded from
> https://www.dropbox.com/s/chhw3vz6ru1godk/Practicedata.Dat
>
> I want to make a comparison graph between modeled and observed. Once I am
> able to read two data sets as two sets of data or combined in one I would
> be able to create the time series graph.
>
> Another thing I need to do is create another sub data set where both the
> series have common data. One data might have more intervals than another.
> After I find two data sets of same interval then I want to plot a
> correlation graph.
>
> I hope I made it clear what I want to do.
>
> Thank you so much.
>
> Best Regards,
> Janesh
>

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