A fixed width file can be a very compact representation of numeric data. It's also very fast to parse, because every field is in the same place in every line. Unfortunately, it's painful to parse because you need to describe the length of every field. Readr aims to make it as easy as possible by providing a number of different ways to describe the field structure.
read_fwf(file, col_positions, col_types = NULL, locale = default_locale(), na = c("", "NA"), comment = "", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress()) fwf_empty(file, skip = 0, col_names = NULL, comment = "", n = 100L) fwf_widths(widths, col_names = NULL) fwf_positions(start, end = NULL, col_names = NULL) fwf_cols(...)
Either a path to a file, a connection, or literal data (either a single string or a raw vector).
Files ending in
Literal data is most useful for examples and tests. It must contain at least one new line to be recognised as data (instead of a path) or be a vector of greater than length 1.
Using a value of
Column positions, as created by
Alternatively, you can use a compact string representation where each
character represents one column:
c = character, i = integer, n = number, d = double,
l = logical, D = date, T = date time, t = time, ? = guess, or
The locale controls defaults that vary from place to place.
The default locale is US-centric (like R), but you can use
Character vector of strings to use for missing values. Set this
A string used to identify comments. Any text after the comment characters will be silently ignored.
Should leading and trailing whitespace be trimmed from each field before parsing it?
Number of lines to skip before reading data.
Maximum number of records to read.
Maximum number of records to use for guessing column types.
Display a progress bar? By default it will only display
in an interactive session and not while knitting a document. The display
is updated every 50,000 values and will only display if estimated reading
time is 5 seconds or more. The automatic progress bar can be disabled by
Either NULL, or a character vector column names.
Number of lines the tokenizer will read to determine file structure. By default it is set to 100.
Width of each field. Use NA as width of last field when reading a ragged fwf file.
Starting and ending (inclusive) positions of each field. Use NA as last end field when reading a ragged fwf file.
If the first element is a data frame,
then it must have all numeric columns and either one or two rows.
The column names are the variable names. The column values are the
variable widths if a length one vector, and if length two, variable start and end
positions. The elements of
read_table() to read fixed width files where each
column is separated by whitespace.
#> John Smith WA 418-Y11-4111 Mary Hartford CA 319-Z19-4341 Evan Nolan IL 219-532-c301# You can specify column positions in several ways: # 1. Guess based on position of empty columns read_fwf(fwf_sample, fwf_empty(fwf_sample, col_names = c("first", "last", "state", "ssn")))#>#> #> #> #> #> #>#> # A tibble: 3 x 4 #> first last state ssn #> <chr> <chr> <chr> <chr> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301# 2. A vector of field widths read_fwf(fwf_sample, fwf_widths(c(20, 10, 12), c("name", "state", "ssn")))#>#> #> #> #> #>#> # A tibble: 3 x 3 #> name state ssn #> <chr> <chr> <chr> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301# 3. Paired vectors of start and end positions read_fwf(fwf_sample, fwf_positions(c(1, 30), c(10, 42), c("name", "ssn")))#>#> #> #> #>#> # A tibble: 3 x 2 #> name ssn #> <chr> <chr> #> 1 John Smith 418-Y11-4111 #> 2 Mary Hartf 319-Z19-4341 #> 3 Evan Nolan 219-532-c301# 4. Named arguments with start and end positions read_fwf(fwf_sample, fwf_cols(name = c(1, 10), ssn = c(30, 42)))#>#> #> #> #>#> # A tibble: 3 x 2 #> name ssn #> <chr> <chr> #> 1 John Smith 418-Y11-4111 #> 2 Mary Hartf 319-Z19-4341 #> 3 Evan Nolan 219-532-c301# 5. Named arguments with column widths read_fwf(fwf_sample, fwf_cols(name = 20, state = 10, ssn = 12))#>#> #> #> #> #>#> # A tibble: 3 x 3 #> name state ssn #> <chr> <chr> <chr> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301