R help - Oct 2010 - Loss of precision in read.csv.

Given a csv file from this location

Airports<-"http://www.ourairports.com/data/airports.csv"

download.file(Airports,basename(Airports))


airports <-read.csv("airports.csv",encoding="UTF-8")
> airports[1,]
    id ident     type              name latitude_deg longitude_deg
elevation_ft continent iso_country iso_region municipality scheduled_service

1 6523   00A heliport Total Rf Heliport      *40.0708      -74.9336 *
  11      <NA>          US      US-PA     Bensalem                no

  gps_code iata_code local_code home_link wikipedia_link keywords

1      00A                  00A


And the precision is lost which we can show by using readLines:


fred<-readLines("airports.csv")
> fred[2]
[1] "6523,\"00A\",\"heliport\",\"Total Rf
Heliport\",*
40.07080078125,-74.9336013793945*
,11,\"NA\",\"US\",\"US-PA\",\"Bensalem\",\"no\",\"00A\",,\"00A\",,,"


I tried various approaches, using colClasses, switching to read.tables,
specifying dec="."


I tested read.csv and it does preserve precision on my test case, but not on
this data.


Ideas?

	[[alternative HTML version deleted]]

Hi Steven,

As near as I can tell, no precision is lost.  R is just being
courteous and not excessively filling our consoles.  Try:

print(airports[1,"latitude_deg"], digits = 22)

which is the most digits R will print (although internally it can
store more I believe).

Alternately, you can convert it to character class:

as.character(airports[1, ])

So in short, this is just a cosmetic feature of presenting the data,
not its actual storage.

Cheers,

Josh

On Sat, Oct 9, 2010 at 1:33 PM, steven mosher <moshersteven at gmail.com>
wrote:
> Given a csv file from this location
>
> Airports<-"http://www.ourairports.com/data/airports.csv"
>
> download.file(Airports,basename(Airports))
>
>
> airports <-read.csv("airports.csv",encoding="UTF-8")
>
>> airports[1,]
>
> ? ?id ident ? ? type ? ? ? ? ? ? ?name latitude_deg longitude_deg
> elevation_ft continent iso_country iso_region municipality
scheduled_service
>
> 1 6523 ? 00A heliport Total Rf Heliport ? ? ?*40.0708 ? ? ?-74.9336 *
> ?11 ? ? ?<NA> ? ? ? ? ?US ? ? ?US-PA ? ? Bensalem ? ? ? ? ? ? ? ?no
>
> ?gps_code iata_code local_code home_link wikipedia_link keywords
>
> 1 ? ? ?00A ? ? ? ? ? ? ? ? ?00A
>
>
> And the precision is lost which we can show by using readLines:
>
>
> fred<-readLines("airports.csv")
>
>> fred[2]
> [1] "6523,\"00A\",\"heliport\",\"Total Rf
Heliport\",*
> 40.07080078125,-74.9336013793945*
>
,11,\"NA\",\"US\",\"US-PA\",\"Bensalem\",\"no\",\"00A\",,\"00A\",,,"
>
>
> I tried various approaches, using colClasses, switching to read.tables,
> specifying dec="."
>
>
> I tested read.csv and it does preserve precision on my test case, but not
on
> this data.
>
>
> Ideas?
>
> ? ? ? ?[[alternative HTML version deleted]]
>
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>


-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/