# Blog Archives

## Usage of R functions "table" & "ifelse" when NA’s exist

January 12, 2011
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Most of the time I came across now and then in help posts questions regarding the mismatching total count of observations after employing the R functions "table" and "ifelse". This usually creates frustration among fresh/part-time practitioners which e...

## Knowing whether a time-series has been differenced appropriately in order to make it stationary

May 7, 2010
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Hello everybody,Today I would like to make you learn a simple method (and of-course using R) how to identify whether a time-series has been differenced appropriately while making it stationary.Suppose, you have made a series stationary by differencing it, now in order to know whether it is neither over nor under differenced subject the current series against next level...

## Knowing whether a time-series has been differenced appropriately in order to make it stationary

May 7, 2010
By

Hello everybody,Today I would like to make you learn a simple method (and of-course using R) how to identify whether a time-series has been differenced appropriately while making it stationary.Suppose, you have made a series stationary by differencing it, now in order to know whether it is neither over nor under differenced subject the current series against next level...

## Easy way of determining number of lines/records in a given large file using R

February 10, 2010
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Dear Readers,Today I would like to post the easy way of determining number of lines/records in any given large file using R.Directly to point.1) If data set is small let say less than 50MB or around in R one can read it with ease using: length(readLines("xyzfile.csv"))2) But if data set is too large say more...

## Easy way of determining number of lines/records in a given large file using R

February 10, 2010
By

Dear Readers,Today I would like to post the easy way of determining number of lines/records in any given large file using R.Directly to point.1) If data set is small let say less than 50MB or around in R one can read it with ease using: length(readLines("xyzfile.csv"))2) But if data set is too large say more...