Load .csv / .csv.gz file from a remote connection

This is a thin wrapper on data.table::fread, but memoised & cached for twenty four hours.

Usage

csv_from_url(...)

Arguments

...

Arguments passed on to data.table::fread

input: A single character string. The value is inspected and deferred to either file= (if no \n present), text= (if at least one \n is present) or cmd= (if no \n is present, at least one space is present, and it isn't a file name). Exactly one of input=, file=, text=, or cmd= should be used in the same call.
file: File name in working directory, path to file (passed through path.expand for convenience), or a URL starting http://, file://, etc. Compressed files with extension .gz and .bz2 are supported if the R.utils package is installed.
text: The input data itself as a character vector of one or more lines, for example as returned by readLines().
cmd: A shell command that pre-processes the file; e.g. fread(cmd=paste("grep",word,"filename")). See Details.
sep: The separator between columns. Defaults to the character in the set [,\t |;:] that separates the sample of rows into the most number of lines with the same number of fields. Use NULL or "" to specify no separator; i.e. each line a single character column like base::readLines does.
sep2: The separator within columns. A list column will be returned where each cell is a vector of values. This is much faster using less working memory than strsplit afterwards or similar techniques. For each column sep2 can be different and is the first character in the same set above [,\t |;], other than sep, that exists inside each field outside quoted regions in the sample. NB: sep2 is not yet implemented.
nrows: The maximum number of rows to read. Unlike read.table, you do not need to set this to an estimate of the number of rows in the file for better speed because that is already automatically determined by fread almost instantly using the large sample of lines. nrows=0 returns the column names and typed empty columns determined by the large sample; useful for a dry run of a large file or to quickly check format consistency of a set of files before starting to read any of them.
header: Does the first data line contain column names? Defaults according to whether every non-empty field on the first data line is type character. If so, or TRUE is supplied, any empty column names are given a default name.
na.strings: A character vector of strings which are to be interpreted as NA values. By default, ",," for columns of all types, including type character is read as NA for consistency. ,"", is unambiguous and read as an empty string. To read ,NA, as NA, set na.strings="NA". To read ,, as blank string "", set na.strings=NULL. When they occur in the file, the strings in na.strings should not appear quoted since that is how the string literal ,"NA", is distinguished from ,NA,, for example, when na.strings="NA".
stringsAsFactors: Convert all or some character columns to factors? Acceptable inputs are TRUE, FALSE, or a decimal value between 0.0 and 1.0. For stringsAsFactors = FALSE, all string columns are stored as character vs. all stored as factor when TRUE. When stringsAsFactors = p for 0 <= p <= 1, string columns col are stored as factor if uniqueN(col)/nrow < p.
verbose: Be chatty and report timings?
skip: If 0 (default) start on the first line and from there finds the first row with a consistent number of columns. This automatically avoids irregular header information before the column names row. skip>0 means ignore the first skip rows manually. skip="string" searches for "string" in the file (e.g. a substring of the column names row) and starts on that line (inspired by read.xls in package gdata).
select: A vector of column names or numbers to keep, drop the rest. select may specify types too in the same way as colClasses; i.e., a vector of colname=type pairs, or a list of type=col(s) pairs. In all forms of select, the order that the columns are specified determines the order of the columns in the result.
drop: Vector of column names or numbers to drop, keep the rest.
colClasses: As in utils::read.csv; i.e., an unnamed vector of types corresponding to the columns in the file, or a named vector specifying types for a subset of the columns by name. The default, NULL means types are inferred from the data in the file. Further, data.table supports a named list of vectors of column names or numbers where the list names are the class names; see examples. The list form makes it easier to set a batch of columns to be a particular class. When column numbers are used in the list form, they refer to the column number in the file not the column number after select or drop has been applied. If type coercion results in an error, introduces NAs, or would result in loss of accuracy, the coercion attempt is aborted for that column with warning and the column's type is left unchanged. If you really desire data loss (e.g. reading 3.14 as integer) you have to truncate such columns afterwards yourself explicitly so that this is clear to future readers of your code.
integer64: "integer64" (default) reads columns detected as containing integers larger than 2^31 as type bit64::integer64. Alternatively, "double"|"numeric" reads as utils::read.csv does; i.e., possibly with loss of precision and if so silently. Or, "character".
dec: The decimal separator as in utils::read.csv. When "auto" (the default), an attempt is made to decide whether "." or "," is more suitable for this input. See details.
col.names: A vector of optional names for the variables (columns). The default is to use the header column if present or detected, or if not "V" followed by the column number. This is applied after check.names and before key and index.
check.names: default is FALSE. If TRUE then the names of the variables in the data.table are checked to ensure that they are syntactically valid variable names. If necessary they are adjusted (by make.names) so that they are, and also to ensure that there are no duplicates.
encoding: default is "unknown". Other possible options are "UTF-8" and "Latin-1". Note: it is not used to re-encode the input, rather enables handling of encoded strings in their native encoding.
quote: By default ("\""), if a field starts with a double quote, fread handles embedded quotes robustly as explained under Details. If it fails, then another attempt is made to read the field as is, i.e., as if quotes are disabled. By setting quote="", the field is always read as if quotes are disabled. It is not expected to ever need to pass anything other than \"\" to quote; i.e., to turn it off.
strip.white: Logical, default TRUE, in which case leading and trailing whitespace is stripped from unquoted "character" fields. "numeric" fields are always stripped of leading and trailing whitespace.
fill: logical or integer (default is FALSE). If TRUE then in case the rows have unequal length, number of columns is estimated and blank fields are implicitly filled. If an integer is provided it is used as an upper bound for the number of columns. If fill=Inf then the whole file is read for detecting the number of columns.
blank.lines.skip: logical, default is FALSE. If TRUE blank lines in the input are ignored.
key: Character vector of one or more column names which is passed to setkey. Only valid when argument data.table=TRUE. Where applicable, this should refer to column names given in col.names.
index: Character vector or list of character vectors of one or more column names which is passed to setindexv. As with key, comma-separated notation like index="x,y,z" is accepted for convenience. Only valid when argument data.table=TRUE. Where applicable, this should refer to column names given in col.names.
showProgress: TRUE displays progress on the console if the ETA is greater than 3 seconds. It is produced in fread's C code where the very nice (but R level) txtProgressBar and tkProgressBar are not easily available.
data.table: TRUE returns a data.table. FALSE returns a data.frame. The default for this argument can be changed with options(datatable.fread.datatable=FALSE).
nThread: The number of threads to use. Experiment to see what works best for your data on your hardware.
logical01: If TRUE a column containing only 0s and 1s will be read as logical, otherwise as integer.
keepLeadingZeros: If TRUE a column containing numeric data with leading zeros will be read as character, otherwise leading zeros will be removed and converted to numeric.
yaml: If TRUE, fread will attempt to parse (using yaml.load) the top of the input as YAML, and further to glean parameters relevant to improving the performance of fread on the data itself. The entire YAML section is returned as parsed into a list in the yaml_metadata attribute. See Details.
autostart: Deprecated and ignored with warning. Please use skip instead.
tmpdir: Directory to use as the tmpdir argument for any tempfile calls, e.g. when the input is a URL or a shell command. The default is tempdir() which can be controlled by setting TMPDIR before starting the R session; see base::tempdir.
tz: Relevant to datetime values which have no Z or UTC-offset at the end, i.e. unmarked datetime, as written by utils::write.csv. The default tz="UTC" reads unmarked datetime as UTC POSIXct efficiently. tz="" reads unmarked datetime as type character (slowly) so that as.POSIXct can interpret (slowly) the character datetimes in local timezone; e.g. by using "POSIXct" in colClasses=. Note that fwrite() by default writes datetime in UTC including the final Z and therefore fwrite's output will be read by fread consistently and quickly without needing to use tz= or colClasses=. If the TZ environment variable is set to "UTC" (or "" on non-Windows where unset vs `""` is significant) then the R session's timezone is already UTC and tz="" will result in unmarked datetimes being read as UTC POSIXct. For more information, please see the news items from v1.13.0 and v1.14.0.

Value

a dataframe as created by data.table::fread()

Examples

# \donttest{
try({ # prevents cran errors
  csv_from_url("https://github.com/nflverse/nflverse-data/releases/download/test/combines.csv")
})
#>       season draft_year           draft_team draft_round draft_ovr   pfr_id
#>        <int>      <int>               <char>       <int>     <int>   <char>
#>    1:   2000       2000        New York Jets           1        13 AbraJo00
#>    2:   2000       2000     Seattle Seahawks           1        19 AlexSh00
#>    3:   2000       2000   Kansas City Chiefs           6       188 AlfoDa20
#>    4:   2000         NA                               NA        NA         
#>    5:   2000       2000    Carolina Panthers           1        23 AndeRa21
#>   ---                                                                      
#> 7676:   2022       2022    Green Bay Packers           1        28 WyatDe00
#> 7677:   2022         NA                               NA        NA WydeJa00
#> 7678:   2022       2022     Cleveland Browns           4       124 YorkCa00
#> 7679:   2022         NA                               NA        NA         
#> 7680:   2022       2022 New England Patriots           4       137 ZappBa00
#>                  cfb_id      player_name    pos           school     ht    wt
#>                  <char>           <char> <char>           <char> <char> <int>
#>    1:                       John Abraham    OLB   South Carolina    6-4   252
#>    2: shaun-alexander-1  Shaun Alexander     RB          Alabama    6-0   218
#>    3:                     Darnell Alford     OT      Boston Col.    6-4   334
#>    4:                       Kyle Allamon     TE       Texas Tech    6-2   253
#>    5:                   Rashard Anderson     CB    Jackson State    6-2   206
#>   ---                                                                        
#> 7676:   devonte-wyatt-1    Devonte Wyatt     DT          Georgia    6-3   304
#> 7677: jalen-wydermyer-1  Jalen Wydermyer     TE        Texas A&M    6-4   255
#> 7678:       cade-york-1        Cade York      K              LSU    6-1   206
#> 7679:                        Nick Zakelj     OT          Fordham    6-6   316
#> 7680:    bailey-zappe-1     Bailey Zappe     QB Western Kentucky    6-1   215
#>       forty bench vertical broad_jump  cone shuttle
#>       <num> <int>    <num>      <int> <num>   <num>
#>    1:  4.55    NA       NA         NA    NA      NA
#>    2:  4.58    NA       NA         NA    NA      NA
#>    3:  5.56    23     25.0         94  8.48    4.98
#>    4:  4.97    NA     29.0        104  7.29    4.49
#>    5:  4.55    NA     34.0        123  7.18    4.15
#>   ---                                              
#> 7676:  4.77    NA     29.0        111    NA      NA
#> 7677:    NA    NA       NA         NA    NA      NA
#> 7678:    NA    12       NA         NA    NA      NA
#> 7679:  5.13    27     28.5        110  7.75    4.71
#> 7680:  4.88    NA     30.0        109  7.19    4.40
# }