similar to: merge problem... extra lines appear in the presence of NAs

Good afternoon, I have a 63 small .csv files which I process daily, and until two weeks ago they processed just fine and only took a matter of moments and had non noticeable memory problem. Two weeks ago they have reached 318 lines and my script "broke". There are some missing-values in some of the files. I have tried hard many times over the last two weeks to create a

I would like to have some function for getting an overview of the variables in a worksheet. Class, dimesions, length, number of missing values,... Guess it wouldn't be that hard to set up such a function, but I guess there are others who have made it already. Or is it already a standard feature in the base package? Any suggestions? Robert

Dear friends - merry Christmas and thanks a lot for much help during the year! In the example below I fail to understand how the calculated value pH is represented in a simple plot - also included. The calculations are useful in practice and likely to be right in principle but I cannot see how this occurs: why a calculated value of 7.4 known as numeric is not simply plotted as such. It

Dear friends - copy paste missed SID <- c() before the first loop - sorry BW Troels Den 25-12-2017 kl. 19:12 skrev Troels Ring: > > Dear friends - merry Christmas and thanks a lot for much help during > the year! > > In the example below I fail to understand how the calculated value pH > is represented in a simple plot - also included. The calculations are > useful

Thanks a lot - formatting the ordinate as ylim=c(4,10) before plotting pH also removed the problem, and options(digits=10) confirmed that pH was not all exactly 7.4 - as I knew. Still I wonder just why R chooses to plot(ATOT,pH) as shown with repeated "7.4" instead of some more detailed representation. Thanks a gain and happy New Year! Troels Den 26-12-2017 kl. 01:03 skrev Bert

I hope you will forgive me this simple question on titration. I'm trying to find very small values from the algorithm below, which I believe is correctly formatted, and the constants are also correct. When SID goes over ATOT, fitted vales are much too low compared to the literature. I guess I must be using optimize in a wrong way but cannot find out how to improve it. I'm on windows, R

Good morning, I have currently 63 .csv files most of which have lines which look like 01/06/05,23445 Though some files have two numbers beside each date. There are missing values, and currently the longest file has 318 rows. (merge() is losing the head and doing runaway memory allocation - but thats another question - I'm still trying to pin that issue down and make a small repeatable

Hi all, I would like to remove rows from a matrix, based on the frequency of missing values. If there are more than 10 % missing values, the row should be deleted. I use the following to calculate the frequencies, thereby getting a new matrix with the frequencies: freqNA=rowMeans(is.na(exprdata)) But is there a shorter way to remove the rows based on "(1-freqNA)>0.1"

Dear R-helpers, We marked 6000 leaves from 5 SPECIES - 10 individuals/species - in two different TREATMENTs: a control and a dry-plot from which 50% of incoming precipitation was excluded. We followed those leaves for 42 months and noted the presence and absence at each visit. I then carried out a Cox Harzard model to see differences in leaf mortality between parcels and among species over time:

Signed-off-by: Scott Seago <sseago at redhat.com> --- AUTHORS | 17 ++++++ README | 10 +++ conf/ovirt-agent | 12 ++++ conf/ovirt-db-omatic | 12 ++++ conf/ovirt-host-browser | 12 ++++