On Mon, 1 Nov 2021, Kevin Thorpe wrote:
I do not have a specific answer to your particular problem. All I can say
is when a CSV import doesn’t work, it can mean there is something in the
CSV file that is unexpected. When read_csv() fails, I will try read.csv()
to compare the results.
Kevin,
Interesting that there's no error:
cor_disc <- read.csv("../data/cor-disc.csv", header = TRUE)
...
12496 14171600 2010 3 15 16 45 PDT 1060
12497 14171600 2010 3 15 17 0 PDT 1060
12498 14171600 2010 3 15 17 15 PDT 1050
12499 14171600 2010 3 15 17 45 PDT 1050
[ reached 'max' / getOption("max.print") -- omitted 402856 rows ]
head(cor_disc)
site_nbr year mon day hr min tz disc
1 14171600 2009 10 23 0 0 PDT 8750
2 14171600 2009 10 23 0 15 PDT 8750
3 14171600 2009 10 23 0 30 PDT 8750
4 14171600 2009 10 23 0 45 PDT 8750
5 14171600 2009 10 23 1 0 PDT 8750
6 14171600 2009 10 23 1 15 PDT 8750
str(cor_disc)
'data.frame': 415355 obs. of 8 variables:
$ site_nbr: chr "14171600" "14171600" "14171600" "14171600" ...
$ year : int 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 ...
$ mon : int 10 10 10 10 10 10 10 10 10 10 ...
$ day : int 23 23 23 23 23 23 23 23 23 23 ...
$ hr : int 0 0 0 0 1 1 1 1 2 2 ...
$ min : int 0 15 30 45 0 15 30 45 0 15 ...
$ tz : chr "PDT" "PDT" "PDT" "PDT" ...
$ disc : int 8750 8750 8750 8750 8750 8750 8750 8730 8730 8730 ...
So, where might I look to see why tidyverse's read_csv() doesn't produce the
same results?
Regards,
Rich
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