Read rectangular files

These functions parse rectangular files (like csv or fixed-width format) into tibbles. They specify the overall structure of the file, and how each line is divided up into fields.

read_delim() read_csv() read_csv2() read_tsv()

Read a delimited file (including csv & tsv) into a tibble

read_fwf() fwf_empty() fwf_widths() fwf_positions() fwf_cols()

Read a fixed width file into a tibble

read_log()

Read common/combined log file into a tibble

read_table() read_table2()

Read whitespace-separated columns into a tibble

Column specification

The column specification describes how each column is parsed from a character vector in to a more specific data type. readr does make an educated guess about the type of each column, but you’ll need override those guesses when it gets them wrong.

problems() stop_for_problems()

Retrieve parsing problems

cols() cols_only()

Create column specification

cols_condense() spec()

Examine the column specifications for a data frame

spec_delim() spec_csv() spec_csv2() spec_tsv() spec_table() spec_table2()

Generate a column specification

Column parsers

Column parsers define how a single column is parsed, or a parse a single vector. Each parser comes in two forms: parse_xxx() which is used to parse vectors that already exist in R and col_xxx() which is used to parse vectors as they are loaded by a read_xxx() function.

parse_logical() parse_integer() parse_double() parse_character() col_logical() col_integer() col_double() col_character()

Parse logicals, integers, and reals

parse_datetime() parse_date() parse_time() col_datetime() col_date() col_time()

Parse date/times

parse_factor() col_factor()

Parse factors

parse_guess() col_guess() guess_parser()

Parse using the "best" type

parse_number() col_number()

Parse numbers, flexibly

col_skip()

Skip a column

Locale controls

The “locale” controls all options that vary from country-to-country or language-to-language. This includes things like the character used as the decimal mark, the names of days of the week, and the encoding. See vignette("locales") for more details.

locale() default_locale()

Create locales

date_names() date_names_lang() date_names_langs()

Create or retrieve date names

Write rectangular files

Despite its name, readr also provides a number of functions to write data frames to disk, or to convert them to in-memory strings.

format_delim() format_csv() format_csv2() format_tsv()

Convert a data frame to a delimited string

write_delim() write_csv() write_csv2() write_excel_csv() write_excel_csv2() write_tsv()

Write a data frame to a delimited file

Low-level IO and debugging tools

These functions can be used with non-rectangular files, binary data, and to help debug rectangular files that fail to parse.

read_file() read_file_raw() write_file()

Read/write a complete file

read_lines() read_lines_raw() write_lines()

Read/write lines to/from a file

count_fields()

Count the number of fields in each line of a file

guess_encoding()

Guess encoding of file

type_convert()

Re-convert character columns in existing data frame

readr_example()

Get path to readr example

clipboard()

Returns values from the clipboard

Chunked API

The chunked API allows you to read in files that are larger than memory, processing a chunk at a time. The API experimental: please try it out but be aware that it may change in the future.

callback

Callback classes

read_delim_chunked() read_csv_chunked() read_csv2_chunked() read_tsv_chunked()

Read a delimited file by chunks

read_lines_chunked() read_lines_raw_chunked()

Read lines from a file or string by chunk.