11.1-11.2


1.What function would you use to read a file where fields were separated with “|”? 

# read_delim(file, delim = "|")


2.Apart from file, skip, and comment, what other arguments do read_csv() and read_tsv() have in common? 

#the following arguments:
intersect(names(formals(read_csv)), names(formals(read_tsv)))
##  [1] "file"            "col_names"       "col_types"       "col_select"     
##  [5] "id"              "locale"          "na"              "quoted_na"      
##  [9] "quote"           "comment"         "trim_ws"         "skip"           
## [13] "n_max"           "guess_max"       "name_repair"     "num_threads"    
## [17] "progress"        "show_col_types"  "skip_empty_rows" "lazy"


5.Identify what is wrong with each of the following inline CSV files. What happens when you run the code? 

read_csv("a,b\n1,2,3\n4,5,6")     #Only two columns are specified in the header “a” and “b”, but the rows have three columns
## Warning: One or more parsing issues, see `problems()` for details
## Rows: 2 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (1): a
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## # A tibble: 2 × 2
##       a     b
##   <dbl> <dbl>
## 1     1    23
## 2     4    56
read_csv("a,b,c\n1,2\n1,2,3,4")   #the header has 3 columns, row 2 has 2 values and row 4 has 4 values
## Warning: One or more parsing issues, see `problems()` for details
## Rows: 2 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (2): a, b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## # A tibble: 2 × 3
##       a     b     c
##   <dbl> <dbl> <dbl>
## 1     1     2    NA
## 2     1     2    34
read_csv("a,b\n\"1")    #The opening quote "1 is dropped because it is not closed, and a is treated as an integer.
## Rows: 0 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): a, b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## # A tibble: 0 × 2
## # … with 2 variables: a <chr>, b <chr>
read_csv("a,b\n1,2\na,b") #Both “a” and “b” are treated as character vectors since they contain non-numeric strings. This may have been intentional, or the author may have intended the values of the columns to be “1,2” and “a,b”.
## Rows: 2 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): a, b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## # A tibble: 2 × 2
##   a     b    
##   <chr> <chr>
## 1 1     2    
## 2 a     b
read_csv("a;b\n1;3")   #The values are separated by “;” rather than “,”. 
## Rows: 1 Columns: 1
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): a;b
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## # A tibble: 1 × 1
##   `a;b`
##   <chr>
## 1 1;3


11.3


2.What happens if you try and set decimal_mark and grouping_mark to the same character? What happens to the default value of grouping_mark when you set decimal_mark to “,”? What happens to the default value of decimal_mark when you set the grouping_mark to “.”? 

#If the decimal and grouping marks are set to the same character, locale throws an error:
locale(decimal_mark = ".", grouping_mark = ".")
## Error: `decimal_mark` and `grouping_mark` must be different
#If the decimal_mark is set to the comma ",", then the grouping mark is set to the period ".":
locale(decimal_mark = ",")
## <locale>
## Numbers:  123.456,78
## Formats:  %AD / %AT
## Timezone: UTC
## Encoding: UTF-8
## <date_names>
## Days:   Sunday (Sun), Monday (Mon), Tuesday (Tue), Wednesday (Wed), Thursday
##         (Thu), Friday (Fri), Saturday (Sat)
## Months: January (Jan), February (Feb), March (Mar), April (Apr), May (May),
##         June (Jun), July (Jul), August (Aug), September (Sep), October
##         (Oct), November (Nov), December (Dec)
## AM/PM:  AM/PM
#If the grouping mark is set to a period, then the decimal mark is set to a comma
locale(grouping_mark = ".")
## <locale>
## Numbers:  123.456,78
## Formats:  %AD / %AT
## Timezone: UTC
## Encoding: UTF-8
## <date_names>
## Days:   Sunday (Sun), Monday (Mon), Tuesday (Tue), Wednesday (Wed), Thursday
##         (Thu), Friday (Fri), Saturday (Sat)
## Months: January (Jan), February (Feb), March (Mar), April (Apr), May (May),
##         June (Jun), July (Jul), August (Aug), September (Sep), October
##         (Oct), November (Nov), December (Dec)
## AM/PM:  AM/PM


7.Generate the correct format string to parse each of the following dates and times: 

d1 <- "January 1, 2010"
d2 <- "2015-Mar-07"
d3 <- "06-Jun-2017"
d4 <- c("August 19 (2015)", "July 1 (2015)")
d5 <- "12/30/14" 
t1 <- "1705"
t2 <- "11:15:10.12 PM"

parse_date(d1, "%B %d, %Y")
## [1] "2010-01-01"
parse_date(d2, "%Y-%b-%d")
## [1] "2015-03-07"
parse_date(d3, "%d-%b-%Y")
## [1] "2017-06-06"
parse_date(d4, "%B %d (%Y)")
## [1] "2015-08-19" "2015-07-01"
parse_date(d5, "%m/%d/%y")
## [1] "2014-12-30"
parse_time(t1, "%H%M")
## 17:05:00
parse_time(t2, "%H:%M:%OS %p")
## 23:15:10.12