search for: meas_date

Hi all, I have been chipping away at a problem I encountered in calculating rates per year from a moderately large data file (46412 rows). When I ran the following command, I got obviously wrong output: interval<- c(NA,as.numeric(diff( strptime(mkdf$MEAS_DATE,"%d/%m/%Y")))/365.25) The values in MEAS_DATE looked like this: mkdf$MEAS_DATE[1:10] [1] 1/5/1962 1/5/1963 1/5/1964 1/3/1965 1/4/1966 1/4/1967 1/6/1968 [8] 25/3/1969 1/4/1971 1/2/1974 146 Levels: 10/10/1967 1/10/1947 1/10/1965 1/10/1967 1/10/1983 ... 9/1/1992 To abbreviate...

...sus with it? Any clues would be very helpful in moving forward. The overall goal of the code below is to minimize the residuals between the blue circles and green squares by adjusting the limits of the secondary y-axis. Thanks, Eric library(zoo) temp.dat<-read.table(textConnection("Well Meas_Date WTD ECgw GW_Project_Area Region Avg.EM.Survey.Value Avg.Soil.Paste.EC SD_EM_Survey 1 4/12/1999 1.75 2.27 LOWER-UPSTREAM US NA NA NA 1 5/11/1999 1.24 5.04 LOWER-UPSTREAM US NA NA NA 1 5/27/1999 1.27 4.45 LOWER-UPSTREAM US NA NA NA 1 6/3/1999 1.27 4.09 LOWER-UPSTREAM US 3.347069 3.126667 0.6347013 1...

...of how to stuff the code that follows the plot commands into a loop that adjusts ylim_2 so as to minimize "min_this"? I'm guessing there is a function to do this? Thanks, Eric library(zoo) #example data and plotting commands follow temp.dat<-read.table(textConnection("Well Meas_Date WTD ECgw GW_Project_Area Region Avg.EM.Survey.Value Avg.Soil.Paste.EC SD_EM_Survey 1 4/12/1999 1.75 2.27 LOWER-UPSTREAM US NA NA NA 1 5/11/1999 1.24 5.04 LOWER-UPSTREAM US NA NA NA 1 5/27/1999 1.27 4.45 LOWER-UPSTREAM US NA NA NA 1 6/3/1999 1.27 4.09 LOWER-UPSTREAM US 3.347069 3.126667 0.6347013 1...