readr::read_csv("file.csv", col_types = rep("c", times = 18)) gives Error: not compatible with STRSXP

Question

I'm trying to read in a fairly simple csv file, but readr is throwing an error when I try to specify the column types. Here's a small snippet of my data:

text <- "Item,Date,Time,SeizureTime,ET,OriginatingNumber,TerminatingNumber,IMEI,IMSI,CT,Feature,DIALED,FORWARDED,TRANSLATED,ORIG_ORIG,MAKE,MODEL,TargetNumber
3,10/31/2012,7:53:00,0:15,1:43,(123)555-1216,(123)555-5662,,,MO,[],,11235552511,,,,,(123)555-5662
4,10/31/2011,9:04:00,0:25,0:00,(123)555-0214,(123)555-5662,,,MO,[],,11235552511,,,,,(123)555-5662
9,10/31/2014,9:08:00,0:11,2:13,(123)555-8555,(132)555-5662,,,MO,[],,11235552511,,,,,(123)555-5662
12,10/31/2011,9:27:00,0:07,0:10,(123)555-0214,(123)555-5662,,,MO,[],,11235552511,,,,,(123)555-5662
13,10/31/2015,9:35:00,0:27,0:00,(123)555-0214,(123)555-5662,,,MO,[],,11235552511,,,,,(123)555-5662
16,10/31/2011,10:09:00,0:10,14:13,(123)555-1216,(123)555-5662,,,MO,[],,11235552511,,,,,(123)555-5662"

dat <- read.table(text = text, sep = ",", header = TRUE)

When trying to read in the actual CSV using read_csv("file.csv", col_types = rep("c", times = 18)) I get the error mentioned in the title. I've seen a couple SO questions regarding this error and they all seem to be related to C++ functions taking place in the background, but I don't know how to remedy it. If I strip off the col_types argument, the error goes away, but it doesn't parse the data correctly.

Answer 1

When you specified the columns you used rep("c", times=18), but that creates a vector with 18 elements. From the help for ?read_csv, the col_types argument takes a single string of column shortcuts like "ccccdc". So we paste the c's together to form one string:

read_csv(text, col_types=paste(rep("c", 18), collapse=""))
Source: local data frame [6 x 18]

   Item       Date     Time SeizureTime    ET
  (chr)      (chr)    (chr)       (chr) (chr)
1     3 10/31/2012  7:53:00        0:15  1:43
2     4 10/31/2011  9:04:00        0:25  0:00
3     9 10/31/2014  9:08:00        0:11  2:13
4    12 10/31/2011  9:27:00        0:07  0:10
5    13 10/31/2015  9:35:00        0:27  0:00
6    16 10/31/2011 10:09:00        0:10 14:13