R Converting list of dates with different formats

Question

So I have lists of dates that I cant quite get to be considered dates due to:

Error in charToDate(x) : character string is not in a standard unambiguous format

The data comes in as character vector and converts to unknown after the last line of code. I'd like to eventually order my data by these dates, but because these are treated as character vectors, things dont arrange correctly.

Sample Data: http://www.fast-files.com/getfile.aspx?file=191192 http://www.fast-files.com/getfile.aspx?file=191193

library("xlsx")
library("readxl")
library("dplyr")
library("data.table")
library("tidyverse")
library("lubridate")
library("zoo")
library("stringr")
A <- read_csv("A.csv")
B <- read_csv("B.csv")
C<- rbind(A,B)
C[C=="/  /"]<-NA
as.Date(C$`ROLL OUT SHIP DATE`)
format <- guess_formats(c(C$`ROLL OUT SHIP DATE`), c("mdY", "BdY", "Bdy", "bdY", "bdy", "mdy", "dby"))
C$`ROLL OUT SHIP DATE` <-as.Date(strptime(C$`ROLL OUT SHIP DATE`, format))

a.csv data:

"Due Date","ROLL OUT SHIP DATE","Vendor Ship Date"
"04/01/2019","/  /","02/25/2019"
"06/06/2019","/  /","04/30/2019"
"04/01/2019","/  /","02/25/2019"
"03/09/2019","/  /","/  /"
"03/09/2019","/  /","/  /"
"03/09/2019","/  /","/  /"
"05/01/2019","/  /","03/25/2019"
"05/10/2019","/  /","04/03/2019"
"05/01/2019","/  /","03/25/2019"
"05/10/2019","04/01/2019","04/03/2019"
"04/24/2019","05/01/2019","03/25/2019"
"03/09/2019","/  /","/  /"
"/  /","/  /","/  /"

b.csv:

"Due Date","ROLL OUT SHIP DATE","Vendor Ship Date"
"04/06/2019","04/07/2019","03/13/2019"
"04/21/2019","04/07/2019","04/03/2019"
"03/30/2019","02/18/2019","03/04/2019"
"03/30/2019","/  /","03/04/2019"
"02/10/2019","/  /","/  /"
"04/05/2019","/  /","02/25/2019"
"06/14/2019","/  /","05/01/2019"
"03/08/2019","/  /","01/21/2019"
"03/08/2019","/  /","01/21/2019"
"03/22/2019","/  /","02/04/2019"
"03/31/2019","04/08/2019","02/25/2019"
"08/03/2019","/  /","06/20/2019"
"08/03/2019","/  /","06/20/2019"
"03/04/2019","/  /","/  /"
"07/30/2019","/  /","06/16/2019"
"07/30/2019","/  /","06/23/2019"
"03/25/2019","/  /","/  /"
"03/29/2019","/  /","/  /"
"03/29/2019","/  /","/  /"
"03/29/2019","/  /","/  /"
"03/29/2019","/  /","/  /"
"03/31/2019","/  /","02/25/2019"
"05/14/2019","/  /","04/01/2019"
"06/17/2019","/  /","05/05/2019"
"03/07/2019","/  /","01/20/2019"
"06/07/2019","/  /","05/01/2019"
"03/16/2019","04/08/2019","01/28/2019"
"03/16/2019","/  /","02/05/2019"
"04/11/2019","/  /","03/05/2019"
"05/15/2019","/  /","04/08/2019"
"06/09/2019","/  /","05/03/2019"
"05/08/2019","/  /","04/01/2019"
"06/12/2019","/  /","04/29/2019"
"/  /","/  /","/  /"
"/  /","/  /","/  /"

I won't speak for everyone, but I'm personally reluctant to download from file-sharing sites. Can you provide a representative example of data here in a reproducible form? See - https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example — thelatemail, Mar 04 '19 at 22:30
I listed segments of the data to be pasted into CSV if that helps. The actual data totals ~2000 rows. — Cptacorn, Mar 05 '19 at 13:54

R Converting list of dates with different formats

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