-1

Currently, running the summary command on my data only prints the first 100 values. The remaining 876671 values in the (Other) category, as show below, are NA values. How can I get these values?

>summary(d)

  7/4/2015  8/27/2015   7/4/2012  8/29/2015   7/5/2015   8/7/2015   6/6/2015  8/26/2016   7/6/2015 
       754        738        736        725        723        721        719        719        717 
  7/3/2015  8/15/2015  9/12/2015  7/10/2015  8/21/2015  8/28/2015  9/11/2015   7/4/2014 10/31/2015 
       714        709        709        708        708        704        702        701        699 
 8/26/2015  8/20/2015  10/8/2015   7/1/2016  9/12/2016  7/28/2015  8/22/2015   8/3/2015   7/2/2015 
       697        695        690        689        686        682        682        681        680 
 7/23/2015   7/4/2013   8/2/2015 10/16/2015 10/17/2015  9/27/2016   8/1/2014  8/19/2015  9/16/2016 
       680        680        679        676        676        676        673        673        673 
 9/30/2015   5/7/2016  6/25/2015  6/28/2016   5/2/2016  9/19/2015   9/9/2015   4/8/2016  5/13/2016 
       673        671        671        671        670        670        670        669        668 
  7/8/2015   8/1/2015  11/1/2014   4/7/2016   8/2/2016   8/2/2014  8/22/2016  10/6/2015  7/20/2016 
       668        668        667        665        665        664        663        661        661 
 4/18/2016  8/17/2015  8/27/2016   5/6/2016   8/8/2015  9/20/2014  10/4/2015   5/8/2015  7/24/2015 
       659        658        658        657        657        657        656        656        656 
 8/10/2013  8/13/2016  8/20/2016  9/20/2015   7/6/2016  8/12/2015  6/25/2016  8/23/2015  10/3/2015 
       656        656        656        655        654        654        653        653        652 
 9/25/2016  6/27/2016   6/3/2016   6/8/2015   7/1/2015  9/26/2016   7/3/2014  8/14/2015  8/15/2014 
       652        650        650        650        650        650        649        649        649 
  9/2/2016  9/30/2016  10/2/2015  4/17/2015  7/25/2016  7/31/2015   7/7/2015   8/4/2013   8/4/2015 
       649        649        648        647        647        647        647        647        646 
10/30/2015  11/4/2016  9/29/2015  7/17/2015   9/6/2014  9/18/2015  9/25/2015 10/29/2016  6/19/2015 
       645        645        645        644        644        643        643        642        642 
   (Other) 
    876671 
haxtar
  • 1,962
  • 3
  • 20
  • 44
  • This would go a lot faster if we saw a representative sample of `d`. (Refs: https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and https://stackoverflow.com/help/mcve) – r2evans Dec 07 '17 at 00:13
  • I think it can be inferred from the summary. It's just a column of dates. – haxtar Dec 07 '17 at 00:16
  • 1
    No, it is not just a column of dates. If `d` were a data.frame, the output would not look like this. If `d` were a *vector* of `POSIXt`, the output would look different. Furthermore, you say that all 876671 values in the `(Other)` category are all `NA` values, so why would you need to get these values? Perhaps you could just use `rep(NA, 876671)` to get the values. – r2evans Dec 07 '17 at 00:22
  • 1
    Try: `summary(rep(Sys.Date(), 10))` and `summary(data.frame(a=rep(Sys.Date(), 10)))` to see what those two look like. And perhaps even `summary(c(NA,as.character(rep(Sys.Date()+1:10, 10))))`. Please just provide us something representative, perhaps just `dput(sample(d,size=20))` assuming it includes some of the non-date entries. – r2evans Dec 07 '17 at 00:28
  • d contains information grabbed from a csv file, where "date" is a column and dates are listed in month/day/year format. d is obtained through `dataset <- read.csv('path')` and `d = dataset$date` The remaining 80000+ values are NA values (I determined as a result of analyzing the result of `summary(d)`), but they shouldn't be. They should contain integer values. The solution was to use the maxsum parameter. Thank you for you responses, @r2evans – haxtar Dec 07 '17 at 00:33

1 Answers1

0

The solution was setting the parameter maxsum to some max number:

summary = summary(d, maxsum = 2000)
haxtar
  • 1,962
  • 3
  • 20
  • 44