search for: coltype

...t * from CREATE TABLE schema_info (version int) 54 SQL:BatchCompleted CREATE TABLE schema_info (version int) 54 SQL:BatchCompleted select * from CREATE TABLE schema_info (version int) 54 SQL:BatchCompleted SELECT COLUMN_NAME as ColName, COLUMN_DEFAULT as DefaultValue, DATA_TYPE as ColType, COL_LENGTH(''schema_info'', COLUMN_NAME) as Length, COLUMNPROPERTY(OBJECT_ID(''schema_info''), COLUMN_NAME, ''IsIdentity'') as IsIdentity, NUMERIC_SCALE as Scale FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = ''schema_info'' 54...

...u) "2004-01-05" (M) "2004-01-06" (Tu) "2004-01-07" (W) "2004-01-08" (Th) The codes are (also attached): rm(list=ls()) library(XLConnect) library(xlsx) fl<-paste("allData_out3.xlsx") a1<-readWorksheetFromFile(fl, sheet="first", colTypes="numeric") b1<-readWorksheetFromFile(fl, sheet="second", colTypes="numeric") a_col<-readWorksheetFromFile(fl, sheet="first") date11<-as.Date(a_col$date, format="%Y-%m-%d") The output: > date11 [1] "2003-12-31" "2004-01...

...n"=>"CIA flight...", "flightdate(1i)"=>"2005", "flightdate(2i)"=>"11", "flightdate(3i)"=>"24"}} [4;35;1mReport Columns (0.070000) SELECT COLUMN_NAME as ColName, COLUMN_DEFAULT as DefaultValue, DATA_TYPE as ColType, COL_LENGTH(''reports'', COLUMN_NAME) as Length, COLUMNPROPERTY(OBJECT_ID(''reports''), COLUMN_NAME, ''IsIdentity'') as IsIdentity, NUMERIC_SCALE as Scale FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = ''reports'' [4;36;1mSQL...

...quot;2004-01-07" (W) > "2004-01-08" (Th) > > > > The codes are (also attached): > > > rm(list=ls()) > library(XLConnect) > library(xlsx) > > fl<-paste("allData_out3.xlsx") > a1<-readWorksheetFromFile(fl, sheet="first", colTypes="numeric") > b1<-readWorksheetFromFile(fl, sheet="second", colTypes="numeric") > a_col<-readWorksheetFromFile(fl, sheet="first") > date11<-as.Date(a_col$date, format="%Y-%m-%d") > > > The output: >> date11 > [1]...

...> > > > > > > > The codes are (also attached): > > > > > > rm(list=ls()) > > library(XLConnect) > > library(xlsx) > > > > fl<-paste("allData_out3.xlsx") > > a1<-readWorksheetFromFile(fl, sheet="first", colTypes="numeric") > > b1<-readWorksheetFromFile(fl, sheet="second", colTypes="numeric") > > a_col<-readWorksheetFromFile(fl, sheet="first") > > date11<-as.Date(a_col$date, format="%Y-%m-%d") > > > > > > The out...

...ched): > >>> > >>> > >>> rm(list=ls()) > >>> library(XLConnect) > >>> library(xlsx) > >>> > >>> fl<-paste("allData_out3.xlsx") > >>> a1<-readWorksheetFromFile(fl, sheet="first", colTypes="numeric") > >>> b1<-readWorksheetFromFile(fl, sheet="second", colTypes="numeric") > >>> a_col<-readWorksheetFromFile(fl, sheet="first") > >>> date11<-as.Date(a_col$date, format="%Y-%m-%d") > >>...

...>>> The codes are (also attached): >>> >>> >>> rm(list=ls()) >>> library(XLConnect) >>> library(xlsx) >>> >>> fl<-paste("allData_out3.xlsx") >>> a1<-readWorksheetFromFile(fl, sheet="first", colTypes="numeric") >>> b1<-readWorksheetFromFile(fl, sheet="second", colTypes="numeric") >>> a_col<-readWorksheetFromFile(fl, sheet="first") >>> date11<-as.Date(a_col$date, format="%Y-%m-%d") >>> >>>...

...numeric). Here is my code (the Excel file is attached): rm(list=ls(all=TRUE)) library(XLConnect) tab <- loadWorkbook("C:/Users/Downloads/File.xlsx", create = TRUE) set <- readWorksheet(tab, sheet = "settings") setNum <- readWorksheet(tab, sheet = "settings", colTypes="numeric") index <- which((!is.na(setNum)), arr.ind=TRUE) if(length(index)!=0){ set[index] <- unlist(lapply(set[index], function(x) as.numeric(as.character(x)))) } ## to check set[10,1] ## Problem: must be numeric !!!! writeWorksheetToFile("C:/Users/Downloads/Test.xlsx&quot...

...te OLE error code:80004005 in Microsoft OLE DB Provider for SQL Server Cannot create new connection because in manual or distributed transaction mode. HRESULT error code:0x80020009 Exception occurred.: SELECT COLUMN_NAME as ColName, COLUMN_DEFAULT as DefaultValue, DATA_TYPE as ColType, COL_LENGTH(''S_RESIT I''ve tried using transactions in rails but to no avail, if I have 10 windows open and refresh all at once, several windows will produce that error. MS suggests (http://support.microsoft.com/default.aspx?scid=kb%3Ben-us%3B272358): Use a server-side or clie...

Hi, I have a dataset consisting of 350,000 rows and 266 columns. Out of 266 columns 250 are dummy variable columns. I am trying to read this data set into R dataframe object but unable to do it due to memory size limitations (object size created is too large to handle in R). Is there a way to handle such a large dataset in R. My PC has 1GB of RAM, and 55 GB harddisk space running

...;> >>> >> >>> rm(list=ls()) >> >>> library(XLConnect) >> >>> library(xlsx) >> >>> >> >>> fl<-paste("allData_out3.xlsx") >> >>> a1<-readWorksheetFromFile(fl, sheet="first", colTypes="numeric") >> >>> b1<-readWorksheetFromFile(fl, sheet="second", colTypes="numeric") >> >>> a_col<-readWorksheetFromFile(fl, sheet="first") >> >>> date11<-as.Date(a_col$date, format="%Y-%m-%d") &...

..." }\n"; - pr " p = strchrnul (tok, ':');\n"; + pr " p = strchrnul (tok, '\\r');\n"; pr " if (*p) next = p+1; else next = NULL;\n"; pr " *p = '\\0';\n"; (match coltype with @@ -633,7 +633,7 @@ cleanup_free_mountable (mountable_t *mountable) pr " r = command (&out, &err,\n"; pr " \"lvm\", \"%ss\",\n" typ; pr " \"-o\", lvm_%s_cols, \"--unbuffered\", \&...

...sion of ".txt". > > rm(list=ls(all=TRUE)) > library(XLConnect) > tab <- loadWorkbook("C:/Users/Downloads/File.xlsx", create = TRUE) > set <- readWorksheet(tab, sheet = "settings") > setNum <- readWorksheet(tab, sheet = "settings", colTypes="numeric") Presumably you could also send the results of dput(setNum) .. either as a .txt attachment or embedded in an email. > index <- which((!is.na(setNum)), arr.ind=TRUE) > if(length(index)!=0){ > set[index] <- unlist(lapply(set[index], function(x) as.numeric(as....

Dear Listers: I have a couple of data frames to report and each corresponds to different condtions, e.g. conditions=c(10, 15, 20, 25). In this examples, four data frames need to be exported in a "pretty" report. I knew Perl has some module for exporting data to Excel and after googling, I found R does not. So I am wondering if there is a package in R for generating good reports. I

Hi, I have a medium-sized (19MB) CSV file that I'd like to read into R. The read.csv() function seems to be a bit inefficient to deal with it, and I remember that using scan() with "what" options is better. However I'm unable to understand how to use it. The first few lines of the data look like:

...ension of ".txt". > > rm(list=ls(all=TRUE)) > library(XLConnect) > tab <- loadWorkbook("C:/Users/Downloads/File.xlsx", create = TRUE) > set <- readWorksheet(tab, sheet = "settings") > setNum <- readWorksheet(tab, sheet = "settings", colTypes="numeric") Presumably you could also send the results of dput(setNum) .. either as a .txt attachment or embedded in an email. > index <- which((!is.na(setNum)), arr.ind=TRUE) > if(length(index)!=0){ > set[index] <- unlist(lapply(set[index], function(x) as.numeric(as.c...

...pr " }\n"; - pr " p = strchrnul (tok, ',');\n"; + pr " p = strchrnul (tok, ':');\n"; pr " if (*p) next = p+1; else next = NULL;\n"; pr " *p = '\\0';\n"; (match coltype with @@ -631,7 +631,7 @@ cleanup_free_mountable (mountable_t *mountable) pr " r = command (&out, &err,\n"; pr " \"lvm\", \"%ss\",\n" typ; pr " \"-o\", lvm_%s_cols, \"--unbuffered\", \&...

Hi, I'm working in R 2.11.1 x64 on Windows x86_64-pc-mingw32. I'm trying to insert a very large CSV file into a SQLite database. I'm pretty new to working with databases in R, so I apologize if I'm overlooking something obvious here. I'm trying to work with the American Community Survey data, which is two 1.3GB csv files. I have enough RAM to read one of them into memory,

Hi, Attached are two datasheet to be read. My raw data "130502temp.xlsx" contains numbers with ' symbols, and they can't be read as numbers. Even if I copy and paste as numbers to form a new file "130502temp_number1.xlsx", they could not be read smoothly. 1. How can I read the datasheet as numbers? 2. How can I treat the notation "-" as (1)

I am unable to get ActiveRecord session support to work under 2.x against a SQL Server database. I''m starting to wonder if anyone is running 2.x against SQL Server? Is anyone running under the following configuration: Rails 2.x SQL Server 2000 DB (using AR adapter in ODBC mode) AR store for ActionController session store. I''d like to chat with you if you are. Thanks, Wes --