My intention is to include certain columns if they meet certain criteria.
For example, if b is one of the columns of a1, then keep otherwise don't.
HTH..
santosh
On Fri, Jan 10, 2014 at 1:01 PM, MacQueen, Don macque...@llnl.gov wrote:
Apologies, but all that ifelse() stuff is too hard to
Don's response seems apropos to me. Do you understanding indexing,
i.e. the [ operator? If not, you should read An Introduction to R or
other tutorial (there are many good ones on the web). If that is not
the issue, you need to explain more clearly why his answer does not
suffice.
Cheers,
Bert
I don't think apropos or indexing would help. I am open to your
suggestions/tips.
I usually get multiple versions of a dataset (even with the same column
names). In the source data, I occasionally notice inconsistencies...
formatting issues, column naming issues etc..
As shown In the a1
At the risk of being annoying ...
Your original question was,
Is there a way to dynamically include columns in a dataframe?
The answer is yes. One way, and I think the simplest, is to calculate the
names of the columns you want to keep, and then use an expression like I
suggested, that is, one
I agree with Don... focus on identifying the names of the columns and then use
column name indexing to extract the columns you want. You will probably want to
rename them to a standard set of names once you have gone to all this
trouble... just assign the new vector of names to the names
?as.POSIXct for time-formatting. This function makes a structured list of
time data, where you specify an input time and format i.e.
as.POSIXct('2014-01-09 01:30:00', format='%Y-%m-%d %H:%M:%S')
On 1/10/14, 15:24 , Santosh santosh2...@gmail.com wrote:
I don't think apropos or indexing would
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