What can R do about a messy data format?

Question

Sometimes I see data posted in a Stack Overflow question formatted like in this question. This is not the first time, so I have decided to ask a question about it, and

Answer 1

md_table <- scan(text = "
+------------+------+------+----------+--------------------------+
|    Date    | Emp1 | Case | Priority | PriorityCountinLast7days |
+------------+------+------+----------+--------------------------+
| 2018-06-01 | A    | A1   |        0 |                        0 |
| 2018-06-03 | A    | A2   |        0 |                        1 |
| 2018-06-03 | A    | A3   |        0 |                        2 |
| 2018-06-03 | A    | A4   |        1 |                        1 |
| 2018-06-03 | A    | A5   |        2 |                        1 |
| 2018-06-04 | A    | A6   |        0 |                        3 |
| 2018-06-01 | B    | B1   |        0 |                        1 |
| 2018-06-02 | B    | B2   |        0 |                        2 |
| 2018-06-03 | B    | B3   |        0 |                        3 |
+------------+------+------+----------+--------------------------+",
what = "", sep = "", comment.char = "+", quiet = TRUE)

## it is clear that there are 5 columns
mat <- matrix(md_table[md_table != "|"], ncol = 5, byrow = TRUE)
#      [,1]         [,2]   [,3]   [,4]       [,5]                      
# [1,] "Date"       "Emp1" "Case" "Priority" "PriorityCountinLast7days"
# [2,] "2018-06-01" "A"    "A1"   "0"        "0"                       
# [3,] "2018-06-03" "A"    "A2"   "0"        "1"                       
# [4,] "2018-06-03" "A"    "A3"   "0"        "2"                       
# [5,] "2018-06-03" "A"    "A4"   "1"        "1"                       
# [6,] "2018-06-03" "A"    "A5"   "2"        "1"                       
# [7,] "2018-06-04" "A"    "A6"   "0"        "3"                       
# [8,] "2018-06-01" "B"    "B1"   "0"        "1"                       
# [9,] "2018-06-02" "B"    "B2"   "0"        "2"                       
#[10,] "2018-06-03" "B"    "B3"   "0"        "3"

## a data frame with all character columns
dat <- setNames(data.frame(mat[-1, ], stringsAsFactors = FALSE), mat[1, ])
#        Date Emp1 Case Priority PriorityCountinLast7days
#1 2018-06-01    A   A1        0                        0
#2 2018-06-03    A   A2        0                        1
#3 2018-06-03    A   A3        0                        2
#4 2018-06-03    A   A4        1                        1
#5 2018-06-03    A   A5        2                        1
#6 2018-06-04    A   A6        0                        3
#7 2018-06-01    B   B1        0                        1
#8 2018-06-02    B   B2        0                        2
#9 2018-06-03    B   B3        0                        3

## or maybe just use `type.convert` on some columns?
dat[] <- lapply(dat, type.convert)