Recreat the "Get Started" vignette

inst/extdata/deaths.csv

@@ -0,0 +1,13 @@
+Date file created:,02/12/2022,,,,
+File created by:,Sally,Brown,,,
+Name,Profession,Age,Has kids,Date of birth,Date of death
+David Bowie,musician,69,TRUE,1/8/1947,1/10/2016
+Carrie Fisher,actor,60,TRUE,10/21/1956,12/27/2016
+Chuck Berry,musician,90,TRUE,10/18/1926,3/18/2017
+Bill Paxton,actor,61,TRUE,5/17/1955,2/25/2017
+Prince,musician,57,TRUE,6/7/1958,4/21/2016
+Alan Rickman,actor,69,FALSE,2/21/1946,1/14/2016
+Florence Henderson,actor,82,TRUE,2/14/1934,11/24/2016
+Harper Lee,author,89,FALSE,4/28/1926,2/19/2016
+Zsa Zsa Gábor,actor,99,TRUE,2/6/1917,12/18/2016
+George Michael,musician,53,FALSE,6/25/1963,12/25/2016

inst/extdata/funny_quotes.csv

@@ -0,0 +1,4 @@
+Size, Cost
+'Small', $5.00
+'Medium, Large, Extra Large',$10.00
+

inst/extdata/interpret-nas.csv

@@ -0,0 +1,7 @@
+x,y
+1,45
+2,-
+3,66
+4,30
+5,-
+

inst/extdata/mini_gap_Europe.csv

@@ -0,0 +1,6 @@
+country,continent,year,lifeExp,pop,gdpPercap
+Albania,Europe,1952,55.23,1282697,1601.056136
+Austria,Europe,1952,66.8,6927772,6137.076492
+Belgium,Europe,1952,68,8730405,8343.105127
+Bosnia and Herzegovina,Europe,1952,53.82,2791000,973.5331948
+Bulgaria,Europe,1952,59.6,7274900,2444.286648

inst/extdata/mini_gap_Oceania.csv

@@ -0,0 +1,6 @@
+country,continent,year,lifeExp,pop,gdpPercap
+Australia,Oceania,1952,69.12,8691212,10039.59564
+New Zealand,Oceania,1952,69.39,1994794,10556.57566
+Australia,Oceania,1957,70.33,9712569,10949.64959
+New Zealand,Oceania,1957,70.26,2229407,12247.39532
+Australia,Oceania,1962,70.93,10794968,12217.22686

inst/extdata/norway.csv

@@ -0,0 +1,25 @@
+date,value
+1 januar 2022,"1,23"
+15 januar 2022,"3,21"
+30 januar 2022,"4,55"
+1 februar 2022,"10,67"
+15 februar 2022,"333,23"
+28 februar 2022,"343,33"
+1 mars 2022,"11,32"
+15 mars 2022,"3,98"
+30 mars 2022,"44,12"
+1 april 2022,"1,22"
+15 april 2022,"9,04"
+30 April 2022,"45,05"
+1 mai 2022,"788,02"
+15 mai 2022,"65,21"
+30 mai 2022,"67,55"
+1 juni 2022,"127.897,23"
+15 juni 2022,"322.222,21"
+30 juni 2022,"240,55"
+1 juli 2022,"170,23"
+15 juli 2022,"3,09"
+30 juli 2022,"42,06"
+1 august 2022,"89,43"
+15 august 2022,"7,21"
+30 august 2022,"1,55"

inst/extdata/problem_numbers.csv

@@ -0,0 +1,8 @@
+value
+1
+2
+3
+4
+5.00
+6
+7

vignettes/column-types.Rmd

@@ -14,6 +14,143 @@ knitr::opts_chunk$set(
 )
 ```
 
+The key problem that readr solves is __parsing__ a flat file into a tibble.
+Parsing is the process of taking a text file and turning it into a rectangular tibble where each column is the appropriate part.
+Parsing takes place in three basic stages:
+
+1.  The flat file is parsed into a rectangular matrix of
+    strings.
+
+1.  The type of each column is determined.
+
+1.  Each column of strings is parsed into a vector of a 
+    more specific type.
+
+## Vector parsers
+
+It's easiest to learn the vector parsers using `parse_` functions.
+These all take a character vector and some options.
+They return a new vector the same length as the old, along with an attribute describing any problems.
+
+First, let's load the readr library
+
+```{r}
+library(readr)
+```
+
+### Atomic vectors
+
+`parse_logical()`, `parse_integer()`, `parse_double()`, and `parse_character()` are straightforward parsers that produce the corresponding atomic vector.
+
+```{r}
+parse_integer(c("1", "2", "3"))
+parse_double(c("1.56", "2.34", "3.56"))
+parse_logical(c("true", "false"))
+```
+
+By default, readr expects `.` as the decimal mark and `,` as the grouping mark.
+You can override this default using `locale()`, as described in `vignette("locales")`.
+
+### Flexible numeric parser
+
+`parse_integer()` and `parse_double()` are strict: the input string must be a single number with no leading or trailing characters.
+`parse_number()` is more flexible: it ignores non-numeric prefixes and suffixes, and knows how to deal with grouping marks.
+This makes it suitable for reading currencies and percentages:
+
+```{r}
+parse_number(c("0%", "10%", "150%"))
+parse_number(c("$1,234.5", "$12.45"))
+```
+
+### Date/times
+
+readr supports three types of date/time data:
+
+* dates: number of days since 1970-01-01.
+* times: number of seconds since midnight.
+* datetimes: number of seconds since midnight 1970-01-01.
+
+```{r}
+parse_datetime("2010-10-01 21:45")
+parse_date("2010-10-01")
+parse_time("1:00pm")
+```
+
+Each function takes a `format` argument which describes the format of the string.
+If not specified, it uses a default value:
+
+* `parse_datetime()` recognises
+  [ISO8601](https://en.wikipedia.org/wiki/ISO_8601) 
+  datetimes.
+
+* `parse_date()` uses the `date_format` specified by
+  the `locale()`. The default value is `%AD` which uses
+  an automatic date parser that recognises dates of the 
+  format `Y-m-d` or `Y/m/d`.
+
+* `parse_time()` uses the `time_format` specified by
+  the `locale()`. The default value is `%At` which uses
+  an automatic time parser that recognises times of the
+  form `H:M` optionally followed by seconds and am/pm.
+
+In most cases, you will need to supply a `format`, as documented in `parse_datetime()`:
+
+```{r}
+parse_datetime("1 January, 2010", "%d %B, %Y")
+parse_datetime("02/02/15", "%m/%d/%y")
+```
+
+### Factors
+
+When reading a column that has a known set of values, you can read directly into a factor.
+`parse_factor()` will generate a warning if a value is not in the supplied levels.
+
+```{r}
+parse_factor(c("a", "b", "a"), levels = c("a", "b", "c"))
+parse_factor(c("a", "b", "d"), levels = c("a", "b", "c"))
+```
+
+
+## Column specification
+
+readr uses some heuristics to guess the type of each column which can be accessed using `guess_parser()`:
+
+```{r}
+guess_parser(c("a", "b", "c"))
+guess_parser(c("1", "2", "3"))
+guess_parser(c("1,000", "2,000", "3,000"))
+guess_parser(c("2001/10/10"))
+```
+
+The guessing policies are described in the documentation for the individual functions.
+Guesses are fairly strict.
+For example, we don't guess that currencies are numbers, even though we can parse them:
+
+```{r}
+guess_parser("$1,234")
+parse_number("$1,234")
+``` 
+
+There are two parsers that will never be guessed: `col_skip()` and `col_factor()`.
+You will always need to supply these explicitly.
+
+You can see the specification that readr would generate for a column file by using `spec_csv()`, `spec_tsv()` and so on:
+
+```{r}
+x <- spec_csv(readr_example("challenge.csv"))
+```
+
+For bigger files, you can often make the specification simpler by changing the default column type using `cols_condense()`
+
+```{r}
+mtcars_spec <- spec_csv(readr_example("mtcars.csv"))
+mtcars_spec
+
+cols_condense(mtcars_spec)
+```
+
+## Column type guessing
+
 readr will guess column types from the data if the user does not specify the types.
 The `guess_max` parameter controls how many rows of the input file are used to form these guesses.
 Ideally, the column types would be completely obvious from the first non-header row and we could use `guess_max = 1`.
@@ -162,3 +299,4 @@ Clean up the temporary tricky csv file.
 ```{r}
 file.remove(tfile)
 ```
+