On 20/01/2011 9:33 PM, D Kelly O'Day wrote:
Bill& Duncan
Thanks for your quick reply. I would still be looking for days.
Now I have to figure out how the bad data got into cts since I generate this
file each month.
When I read that .csv file in OpenOffice, the lines with the NAs arise
becau
Bill & Duncan
Thanks for your quick reply. I would still be looking for days.
Now I have to figure out how the bad data got into cts since I generate this
file each month.
--
View this message in context:
http://r.789695.n4.nabble.com/Unexpected-Gap-in-simple-line-plot-tp3228853p3228920.htm
You do have missing values. Setting xlim does not subset the data.
How about
link <- "http://processtrends.com/files/RClimate_CTS_latest.csv";
cts <- read.csv(link, header = TRUE)
scts <- subset(cts, !is.na(GISS) & !is.na(cts)) ## remove defectives
plot(GISS ~ yr_frac, scts, type =
On 20/01/2011 8:12 PM, D Kelly O'Day wrote:
I am getting an unexpected gap in a simple plot of monthly data series.
I have created a csv file of monthly climate observations that I store
on-line. When I download the csv file and plot one of the series, I get a
gap even though there is data for
4 matches
Mail list logo