For what it's worth the janitor::remove_empty() (which removes all-NA
rows by default, can be set to remove columns instead) can be useful for
this kind of cleanup.
On 2023-09-24 5:58 a.m., Michael Dewey wrote:
Dear David
To get the first 46 rows just do KurtzData[1:43,]
However really you want to find out why it happened. It looks as though
the .csv file you read has lots of blank lines at the end. I would open
it in an editor to check that.
Michael
On 23/09/2023 23:55, Parkhurst, David wrote:
With help from several people, I used file.choose() to get my file
name, and read.csv() to read in the file as KurtzData. Then when I
print KurtzData, the last several lines look like this:
39 5/31/22 16.0 341 1.75525 0.0201 0.0214 7.00
40 6/28/22 2:00 PM 0.0 215 0.67950 0.0156 0.0294 NA
41 7/25/22 11:00 AM 11.9 1943.5 NA NA 0.0500 7.80
42 8/31/22 0 220.5 NA NA 0.0700 30.50
43 9/28/22 0.067 10.9 NA NA 0.0700 10.20
44 10/26/22 0.086 237 NA NA 0.1550 45.00
45 1/12/23 1:00 PM 36.26 24196 NA NA 0.7500 283.50
46 2/14/23 1:00 PM 20.71 55 NA NA 0.0500 2.40
47 NA NA NA NA
48 NA NA NA NA
49 NA NA NA NA
Then the NA�s go down to one numbered 973. Where did those extras
likely come from, and how do I get rid of them? I assume I need to
get rid of all the lines after #46, to do calculations and graphics, no?
David
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