Re: [R] Conditional read-in of data

2009-11-04 Thread mnstn

Hello Jim and Gabor,
Thanks for your inputs. The lines:

a<-as.matrix(read.table(pipe("awk -f cut.awk Data.file")))
cut.awk>{for(i = 1; i <= NF; i=i+10) print $i,""}

solved my problem. I know that 40k lines is not a large data set. I have
about 150 files each of which has 40k rows and in each file I wanted to
visualize (basically to ensure nothing odd is going on) how the data behaves
in each quarter of the data w/o making 150 figures/pdf files. In future as
my data size increases I will consider using relational databases.

Thanks again,
mnstn


Gabor Grothendieck wrote:
> 
> 1. You can pipe your data through gawk (or other scripting language)
> process as in:
> http://tolstoy.newcastle.edu.au/R/e5/help/08/09/2129.html
> 
> 2. read.csv.sql in the sqldf package on CRAN will set up a database
> for you, read the file into the database automatically defining the
> layout of the table, extract a portion into R based on an sql
> statement that you provide and then destroy the database all in one
> statement.  It uses the sqlite database which is included in the
> RSQLite R package that it depends on so there is nothing to separately
> install.
> See ?read.csv.sql in the package and also see example 13 on the home page:
> http://sqldf.googlecode.com
> 
> 
> On Wed, Nov 4, 2009 at 12:07 AM, mnstn  wrote:
>>
>> Hello All,
>> I have a 40k rows long data set that is taking a lot of time to be
>> read-in.
>> Is there a way to skip reading even/odd numbered rows or read-in only
>> rows
>> that are multiples of, say, 10? This way I get the general trend of the
>> data
>> w/o actually reading the entire thing. The option 'skip' in read.table
>> simply skips the first n rows and reads the rest. I do understand that
>> once
>> the full data set (40k rows) is read-in, I can manipulate the data. But
>> the
>> bottle-neck here is the first read/scan of data.
>>
>> I searched in the forum using key words (conditional skip/skip reading
>> rows/skip data/conditional data read) etc. but couldn't find relevant
>> conversations. I apologize if this has already been discussed since it
>> does
>> seem hard to imagine that nobody has come across this problem yet.
>>
>> Any suggestions/comments are welcome.
>> Thanks,
>> mnstn
>> --
>> View this message in context:
>> http://old.nabble.com/Conditional-read-in-of-data-tp26191091p26191091.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> __
>> R-help@r-project.org mailing list
>> 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@r-project.org mailing list
> 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: [R] Conditional read-in of data

2009-11-04 Thread Gabor Grothendieck
1. You can pipe your data through gawk (or other scripting language)
process as in:
http://tolstoy.newcastle.edu.au/R/e5/help/08/09/2129.html

2. read.csv.sql in the sqldf package on CRAN will set up a database
for you, read the file into the database automatically defining the
layout of the table, extract a portion into R based on an sql
statement that you provide and then destroy the database all in one
statement.  It uses the sqlite database which is included in the
RSQLite R package that it depends on so there is nothing to separately
install.
See ?read.csv.sql in the package and also see example 13 on the home page:
http://sqldf.googlecode.com


On Wed, Nov 4, 2009 at 12:07 AM, mnstn  wrote:
>
> Hello All,
> I have a 40k rows long data set that is taking a lot of time to be read-in.
> Is there a way to skip reading even/odd numbered rows or read-in only rows
> that are multiples of, say, 10? This way I get the general trend of the data
> w/o actually reading the entire thing. The option 'skip' in read.table
> simply skips the first n rows and reads the rest. I do understand that once
> the full data set (40k rows) is read-in, I can manipulate the data. But the
> bottle-neck here is the first read/scan of data.
>
> I searched in the forum using key words (conditional skip/skip reading
> rows/skip data/conditional data read) etc. but couldn't find relevant
> conversations. I apologize if this has already been discussed since it does
> seem hard to imagine that nobody has come across this problem yet.
>
> Any suggestions/comments are welcome.
> Thanks,
> mnstn
> --
> View this message in context: 
> http://old.nabble.com/Conditional-read-in-of-data-tp26191091p26191091.html
> Sent from the R help mailing list archive at Nabble.com.
>
> __
> R-help@r-project.org mailing list
> 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@r-project.org mailing list
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and provide commented, minimal, self-contained, reproducible code.


Re: [R] Conditional read-in of data

2009-11-04 Thread jim holtman
That does not seem like a "large" data set.  How are you reading it?
How many columns does it have?  What is "a lot of time" by your
definition?  You have provided minimal data for obtaining help.  I
common read in files with 300K rows in under 30 seconds.  Maybe you
need to consider a relational database for storing your data.

On Wed, Nov 4, 2009 at 12:07 AM, mnstn  wrote:
>
> Hello All,
> I have a 40k rows long data set that is taking a lot of time to be read-in.
> Is there a way to skip reading even/odd numbered rows or read-in only rows
> that are multiples of, say, 10? This way I get the general trend of the data
> w/o actually reading the entire thing. The option 'skip' in read.table
> simply skips the first n rows and reads the rest. I do understand that once
> the full data set (40k rows) is read-in, I can manipulate the data. But the
> bottle-neck here is the first read/scan of data.
>
> I searched in the forum using key words (conditional skip/skip reading
> rows/skip data/conditional data read) etc. but couldn't find relevant
> conversations. I apologize if this has already been discussed since it does
> seem hard to imagine that nobody has come across this problem yet.
>
> Any suggestions/comments are welcome.
> Thanks,
> mnstn
> --
> View this message in context: 
> http://old.nabble.com/Conditional-read-in-of-data-tp26191091p26191091.html
> Sent from the R help mailing list archive at Nabble.com.
>
> __
> R-help@r-project.org mailing list
> 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.
>



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?

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[R] Conditional read-in of data

2009-11-03 Thread mnstn

Hello All,
I have a 40k rows long data set that is taking a lot of time to be read-in.
Is there a way to skip reading even/odd numbered rows or read-in only rows
that are multiples of, say, 10? This way I get the general trend of the data
w/o actually reading the entire thing. The option 'skip' in read.table
simply skips the first n rows and reads the rest. I do understand that once
the full data set (40k rows) is read-in, I can manipulate the data. But the
bottle-neck here is the first read/scan of data.

I searched in the forum using key words (conditional skip/skip reading
rows/skip data/conditional data read) etc. but couldn't find relevant
conversations. I apologize if this has already been discussed since it does
seem hard to imagine that nobody has come across this problem yet.

Any suggestions/comments are welcome.
Thanks,
mnstn
-- 
View this message in context: 
http://old.nabble.com/Conditional-read-in-of-data-tp26191091p26191091.html
Sent from the R help mailing list archive at Nabble.com.

__
R-help@r-project.org mailing list
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.