Transforming data for nice output table

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Transforming data for nice output table

kydaviddoyle
Hello everyone,

I'm trying to generate tables of my data out of R for my report.

My data is setup in the format as follows and the example can be found at:
http://doylesdartden.com/R/ExampleData.csv

Location        Date        Year      GW_Elevation
127(I)        5/14/2006     2006       752.46
119(I)        5/14/2006     2006       774.67
127(I)        6/11/2007     2007       752.06
119(I)        6/11/2007     2007       775.57

I would like to generate a table that showed

Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation xxx.....

119(I)                    774.67                      775.57
          xxxx
127(I)                    752.46                      752.06
          xxxx
XXXX                          XX                           XX

 Any thoughts on how to transform the data so it would be in this format??

Thank you for your time

David Doyle

        [[alternative HTML version deleted]]

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Take Care

David Doyle
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Re: Transforming data for nice output table

Rui Barradas
Hello,

This is a very frequent question.
I could rewrite one or two answers taken from StackOverflow:

https://stackoverflow.com/questions/5890584/how-to-reshape-data-from-long-to-wide-format


But there you will have more options.


Hope this helps,

Rui Barradas

On 20/08/2018 20:17, David Doyle wrote:

> Hello everyone,
>
> I'm trying to generate tables of my data out of R for my report.
>
> My data is setup in the format as follows and the example can be found at:
> http://doylesdartden.com/R/ExampleData.csv
>
> Location        Date        Year      GW_Elevation
> 127(I)        5/14/2006     2006       752.46
> 119(I)        5/14/2006     2006       774.67
> 127(I)        6/11/2007     2007       752.06
> 119(I)        6/11/2007     2007       775.57
>
> I would like to generate a table that showed
>
> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation xxx.....
>
> 119(I)                    774.67                      775.57
>            xxxx
> 127(I)                    752.46                      752.06
>            xxxx
> XXXX                          XX                           XX
>
>   Any thoughts on how to transform the data so it would be in this format??
>
> Thank you for your time
>
> David Doyle
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] 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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Re: Transforming data for nice output table

Jim Lemon-4
In reply to this post by kydaviddoyle
Hi David,
As you want the _values_ of Year from the initial data frame appended
to the _names_ of GW_Elevation, you can't do it the easy way:

dddf<-read.table(text="Location        Date        Year      GW_Elevation
127(I)        5/14/2006     2006       752.46
119(I)        5/14/2006     2006       774.67
127(I)        6/11/2007     2007       752.06
119(I)        6/11/2007     2007       775.57",
header=TRUE)
library(prettyR)
# easy part
sdddf<-stretch_df(dddf[c(1,3,4)],"Location",c("Year","GW_Elevation"))
sdddf

This only works for a data frame with the structure and names of the initial one

# hard part
sdddf_dim<-dim(sdddf)
nyears<-(sdddf_dim[2] - 1)/2
fsdddf<-sdddf[,c(1,1:nyears+nyears+1)]
names(fsdddf)<-c("Location",paste("GW_Elevation",unique(dddf$Year),sep="_"))
fsdddf

I would strongly suggest being happy with the easy way, because if the
order of years isn't ascending, the hard way won't work.

Jim

On Tue, Aug 21, 2018 at 5:17 AM, David Doyle <[hidden email]> wrote:

> Hello everyone,
>
> I'm trying to generate tables of my data out of R for my report.
>
> My data is setup in the format as follows and the example can be found at:
> http://doylesdartden.com/R/ExampleData.csv
>
> Location        Date        Year      GW_Elevation
> 127(I)        5/14/2006     2006       752.46
> 119(I)        5/14/2006     2006       774.67
> 127(I)        6/11/2007     2007       752.06
> 119(I)        6/11/2007     2007       775.57
>
> I would like to generate a table that showed
>
> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation xxx.....
>
> 119(I)                    774.67                      775.57
>           xxxx
> 127(I)                    752.46                      752.06
>           xxxx
> XXXX                          XX                           XX
>
>  Any thoughts on how to transform the data so it would be in this format??
>
> Thank you for your time
>
> David Doyle
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] 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.

______________________________________________
[hidden email] 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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Re: Transforming data for nice output table

Jeff Newmiller
If departing from base R into contributed territory, tidyr::spread is
well-suited to this.

library(dplyr)
library(tidyr)
dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv"
                , header = TRUE
                , as.is = TRUE
                )
result <- (   dta # starting with your data...
           # keep only relevant columns
           %>% select( Location, Year, GW_Elevation )
           # make the key column look like your desired column names
           %>% mutate( Year = sprintf( "GW_Elevation %d", Year ) )
           # spread the "long" data out "wide"
           %>% spread( Year, GW_Elevation )
           )

On Tue, 21 Aug 2018, Jim Lemon wrote:

> Hi David,
> As you want the _values_ of Year from the initial data frame appended
> to the _names_ of GW_Elevation, you can't do it the easy way:
>
> dddf<-read.table(text="Location        Date        Year      GW_Elevation
> 127(I)        5/14/2006     2006       752.46
> 119(I)        5/14/2006     2006       774.67
> 127(I)        6/11/2007     2007       752.06
> 119(I)        6/11/2007     2007       775.57",
> header=TRUE)
> library(prettyR)
> # easy part
> sdddf<-stretch_df(dddf[c(1,3,4)],"Location",c("Year","GW_Elevation"))
> sdddf
>
> This only works for a data frame with the structure and names of the initial one
>
> # hard part
> sdddf_dim<-dim(sdddf)
> nyears<-(sdddf_dim[2] - 1)/2
> fsdddf<-sdddf[,c(1,1:nyears+nyears+1)]
> names(fsdddf)<-c("Location",paste("GW_Elevation",unique(dddf$Year),sep="_"))
> fsdddf
>
> I would strongly suggest being happy with the easy way, because if the
> order of years isn't ascending, the hard way won't work.
>
> Jim
>
> On Tue, Aug 21, 2018 at 5:17 AM, David Doyle <[hidden email]> wrote:
>> Hello everyone,
>>
>> I'm trying to generate tables of my data out of R for my report.
>>
>> My data is setup in the format as follows and the example can be found at:
>> http://doylesdartden.com/R/ExampleData.csv
>>
>> Location        Date        Year      GW_Elevation
>> 127(I)        5/14/2006     2006       752.46
>> 119(I)        5/14/2006     2006       774.67
>> 127(I)        6/11/2007     2007       752.06
>> 119(I)        6/11/2007     2007       775.57
>>
>> I would like to generate a table that showed
>>
>> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation xxx.....
>>
>> 119(I)                    774.67                      775.57
>>           xxxx
>> 127(I)                    752.46                      752.06
>>           xxxx
>> XXXX                          XX                           XX
>>
>>  Any thoughts on how to transform the data so it would be in this format??
>>
>> Thank you for your time
>>
>> David Doyle
>>
>>         [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> [hidden email] 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.
>
> ______________________________________________
> [hidden email] 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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                                       Live:   OO#.. Dead: OO#..  Playing
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Re: Transforming data for nice output table

Rui Barradas
In reply to this post by Rui Barradas
Hello,

One of those would be with package reshape2.



dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv")

subdta <- dta[, c("Location", "Year", "GW_Elevation")]

res <- reshape2::dcast(subdta, Location ~ Year, value.var = "GW_Elevation")
names(res)[-1] <- paste("GW_Elevation", names(res)[-1], sep = "_")
head(res)


Hope this helps,

Rui Barradas

On 20/08/2018 21:37, Rui Barradas wrote:

> Hello,
>
> This is a very frequent question.
> I could rewrite one or two answers taken from StackOverflow:
>
> https://stackoverflow.com/questions/5890584/how-to-reshape-data-from-long-to-wide-format 
>
>
>
> But there you will have more options.
>
>
> Hope this helps,
>
> Rui Barradas
>
> On 20/08/2018 20:17, David Doyle wrote:
>> Hello everyone,
>>
>> I'm trying to generate tables of my data out of R for my report.
>>
>> My data is setup in the format as follows and the example can be found
>> at:
>> http://doylesdartden.com/R/ExampleData.csv
>>
>> Location        Date        Year      GW_Elevation
>> 127(I)        5/14/2006     2006       752.46
>> 119(I)        5/14/2006     2006       774.67
>> 127(I)        6/11/2007     2007       752.06
>> 119(I)        6/11/2007     2007       775.57
>>
>> I would like to generate a table that showed
>>
>> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation
>> xxx.....
>>
>> 119(I)                    774.67                      775.57
>>            xxxx
>> 127(I)                    752.46                      752.06
>>            xxxx
>> XXXX                          XX                           XX
>>
>>   Any thoughts on how to transform the data so it would be in this
>> format??
>>
>> Thank you for your time
>>
>> David Doyle
>>
>>     [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> [hidden email] 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.
>>
>
> ---
> This email has been checked for viruses by AVG.
> https://www.avg.com
>
> ______________________________________________
> [hidden email] 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.

______________________________________________
[hidden email] 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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Re: Transforming data for nice output table

Rui Barradas
Sorry, there is no need to subset the data frame,

reshape2::dcast(dta, etc)

will do the same.

Rui Barradas

On 21/08/2018 05:10, Rui Barradas wrote:

> Hello,
>
> One of those would be with package reshape2.
>
>
>
> dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv")
>
> subdta <- dta[, c("Location", "Year", "GW_Elevation")]
>
> res <- reshape2::dcast(subdta, Location ~ Year, value.var = "GW_Elevation")
> names(res)[-1] <- paste("GW_Elevation", names(res)[-1], sep = "_")
> head(res)
>
>
> Hope this helps,
>
> Rui Barradas
>
> On 20/08/2018 21:37, Rui Barradas wrote:
>> Hello,
>>
>> This is a very frequent question.
>> I could rewrite one or two answers taken from StackOverflow:
>>
>> https://stackoverflow.com/questions/5890584/how-to-reshape-data-from-long-to-wide-format 
>>
>>
>>
>> But there you will have more options.
>>
>>
>> Hope this helps,
>>
>> Rui Barradas
>>
>> On 20/08/2018 20:17, David Doyle wrote:
>>> Hello everyone,
>>>
>>> I'm trying to generate tables of my data out of R for my report.
>>>
>>> My data is setup in the format as follows and the example can be
>>> found at:
>>> http://doylesdartden.com/R/ExampleData.csv
>>>
>>> Location        Date        Year      GW_Elevation
>>> 127(I)        5/14/2006     2006       752.46
>>> 119(I)        5/14/2006     2006       774.67
>>> 127(I)        6/11/2007     2007       752.06
>>> 119(I)        6/11/2007     2007       775.57
>>>
>>> I would like to generate a table that showed
>>>
>>> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation
>>> xxx.....
>>>
>>> 119(I)                    774.67                      775.57
>>>            xxxx
>>> 127(I)                    752.46                      752.06
>>>            xxxx
>>> XXXX                          XX                           XX
>>>
>>>   Any thoughts on how to transform the data so it would be in this
>>> format??
>>>
>>> Thank you for your time
>>>
>>> David Doyle
>>>
>>>     [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> [hidden email] 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.
>>>
>>
>> ---
>> This email has been checked for viruses by AVG.
>> https://www.avg.com
>>
>> ______________________________________________
>> [hidden email] 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.
>
> ______________________________________________
> [hidden email] 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.

______________________________________________
[hidden email] 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
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Re: Transforming data for nice output table

David Carlson
Another approach to adding GW_Elevation to the year value, but the table is more compact with just the year.

dta <- read.csv("http://doylesdartden.com/R/ExampleData.csv")
Years <- paste("GW_Elevation", dta$Year)
xtabs(GW_Elevation~Location+Years, dta)


David L. Carlson
Department of Anthropology
Texas A&M University

-----Original Message-----
From: R-help [mailto:[hidden email]] On Behalf Of Rui Barradas
Sent: Monday, August 20, 2018 11:39 PM
To: David Doyle <[hidden email]>; [hidden email]
Subject: Re: [R] Transforming data for nice output table

Sorry, there is no need to subset the data frame,

reshape2::dcast(dta, etc)

will do the same.

Rui Barradas

On 21/08/2018 05:10, Rui Barradas wrote:

> Hello,
>
> One of those would be with package reshape2.
>
>
>
> dta <- read.csv( "http://doylesdartden.com/R/ExampleData.csv")
>
> subdta <- dta[, c("Location", "Year", "GW_Elevation")]
>
> res <- reshape2::dcast(subdta, Location ~ Year, value.var = "GW_Elevation")
> names(res)[-1] <- paste("GW_Elevation", names(res)[-1], sep = "_")
> head(res)
>
>
> Hope this helps,
>
> Rui Barradas
>
> On 20/08/2018 21:37, Rui Barradas wrote:
>> Hello,
>>
>> This is a very frequent question.
>> I could rewrite one or two answers taken from StackOverflow:
>>
>> https://stackoverflow.com/questions/5890584/how-to-reshape-data-from-long-to-wide-format 
>>
>>
>>
>> But there you will have more options.
>>
>>
>> Hope this helps,
>>
>> Rui Barradas
>>
>> On 20/08/2018 20:17, David Doyle wrote:
>>> Hello everyone,
>>>
>>> I'm trying to generate tables of my data out of R for my report.
>>>
>>> My data is setup in the format as follows and the example can be
>>> found at:
>>> http://doylesdartden.com/R/ExampleData.csv
>>>
>>> Location        Date        Year      GW_Elevation
>>> 127(I)        5/14/2006     2006       752.46
>>> 119(I)        5/14/2006     2006       774.67
>>> 127(I)        6/11/2007     2007       752.06
>>> 119(I)        6/11/2007     2007       775.57
>>>
>>> I would like to generate a table that showed
>>>
>>> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation
>>> xxx.....
>>>
>>> 119(I)                    774.67                      775.57
>>>            xxxx
>>> 127(I)                    752.46                      752.06
>>>            xxxx
>>> XXXX                          XX                           XX
>>>
>>>   Any thoughts on how to transform the data so it would be in this
>>> format??
>>>
>>> Thank you for your time
>>>
>>> David Doyle
>>>
>>>     [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> [hidden email] 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.
>>>
>>
>> ---
>> This email has been checked for viruses by AVG.
>> https://www.avg.com
>>
>> ______________________________________________
>> [hidden email] 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.
>
> ______________________________________________
> [hidden email] 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.

______________________________________________
[hidden email] 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.
______________________________________________
[hidden email] 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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Re: Transforming data for nice output table

PaulJohnson32gmail
In reply to this post by kydaviddoyle
On Mon, Aug 20, 2018 at 2:17 PM David Doyle <[hidden email]> wrote:

>
> Hello everyone,
>
> I'm trying to generate tables of my data out of R for my report.
>
> My data is setup in the format as follows and the example can be found at:
> http://doylesdartden.com/R/ExampleData.csv
>
> Location        Date        Year      GW_Elevation
> 127(I)        5/14/2006     2006       752.46
> 119(I)        5/14/2006     2006       774.67
> 127(I)        6/11/2007     2007       752.06
> 119(I)        6/11/2007     2007       775.57
>
> I would like to generate a table that showed
>
> Location    GW_Elevation 2006    GW_Elevation 2007    GW_Elevation xxx.....
>
> 119(I)                    774.67                      775.57
>           xxxx
> 127(I)                    752.46                      752.06
>           xxxx
> XXXX                          XX                           XX
>
>  Any thoughts on how to transform the data so it would be in this format??
>
> Thank you for your time
>
> David Doyle

Dear David

I'd consider studying R's reshape function, it was intended exactly
for this purpose. No reason to adventure into any user-contributed
tidy places to get this done.

dta <- read.csv("http://doylesdartden.com/R/ExampleData.csv")
dta <- dta[c("Location", "Year", "GW_Elevation")]
dta.wide <- reshape(dta, direction = "wide", idvar = "Location",
v.names = "GW_Elevation", timevar = "Year")
head(dta.wide)

  Location GW_Elevation.2006 GW_Elevation.2007 GW_Elevation.2008
1   127(I)            752.46                NA            757.50
2   119(S)            774.67            778.76            776.40
3   132(I)            759.45            761.68            764.27
4   132(S)            761.77            761.04            765.44
5   111(I)            753.52            763.24            764.24
6   111(S)            766.18            772.84            767.41
  GW_Elevation.2009 GW_Elevation.2010 GW_Elevation.2011 GW_Elevation.2012
1            759.90            756.40            759.05            759.31
2            777.59            777.45            778.21            778.13
3            761.90            764.03            763.63            763.99
4            761.21            763.12            762.69            759.57
5            750.85            764.37            762.99            763.90
6            769.77            767.88            767.95            767.19
  GW_Elevation.2013 GW_Elevation.2014 GW_Elevation.2015 GW_Elevation.2016
1            756.07            756.66            757.72            757.66
2            778.88            778.28            775.16            778.28
3            761.22            762.81            762.36            764.46
4            763.19            763.87            761.94            763.90
5            764.42            761.65            764.02            762.93
6            770.20            767.25            767.74            766.87

The main difference between this and your stated target is that your
target column names have spaces in them, which are forbidden in
column names of data frames. Here R used a period for joining strings.
You can override
that if you want to with the reshape function, but usually I'd let the periods
happen.

If you do want to replace period with spaces, it can be done, but you
break the warranty
on other uses of a data frame. (Could get rid of underscore after GW
in same way)

colnames(dta.wide) <- sub("Elevation.", "Elevation ",
colnames(dta.wide), fixed = TRUE)

I'd not try to use that wide frame for many other purposes because of
the spaces, but it works well if you want to make a pleasant table out
of it. For example, xtable is my favorite:

library(xtable)

xt <- xtable(dta.wide)
print(xt)

The latex from that prints out beautifully in a document. The print
method for xtable has a file parameter if you want to save the file.

Good Luck

pj



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--
Paul E. Johnson   http://pj.freefaculty.org
Director, Center for Research Methods and Data Analysis http://crmda.ku.edu

To write to me directly, please address me at pauljohn at ku.edu.

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
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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.