R语言read.table函数

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#r语言

本文详细解析了R语言中read.table函数的各项参数及其用途，包括如何指定文件路径、处理缺失值、定义分隔符等内容。

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read.table(file, header = FALSE, sep = "", quote = "\"'",
           dec = ".", numerals = c("allow.loss", "warn.loss", "no.loss"),
           row.names, col.names, as.is = !stringsAsFactors,
           na.strings = "NA", colClasses = NA, nrows = -1,
           skip = 0, check.names = TRUE, fill = !blank.lines.skip,
           strip.white = FALSE, blank.lines.skip = TRUE,
           comment.char = "#",
           allowEscapes = FALSE, flush = FALSE,
           stringsAsFactors = default.stringsAsFactors(),
           fileEncoding = "", encoding = "unknown", text, skipNul = FALSE)

file 文件名，在windows系统下可为“dir\\example.txt”，在linux系统下为“dir/example.txt”


 
header 
header设置为TRUE，表示第一行的内容是每一列的名字
sep 分隔符，默认sep = ""（空格）
quote quote只对被当做character的列有效
dec the character used in the file for decimal points.
numerals string indicating how to convert numbers whose conversion to double precision would lose accuracy
row.names 行名的向量
col.names 列名的向量
as.is the default behavior of read.table is to convert character variables (which are not converted to logical, numeric or complex) to factors. The variable as.is controls the conversion of columns not otherwise specified by colClasses. Its value is either a vector of logicals (values are recycled if necessary), or a vector of numeric or character indices which specify which columns should not be converted to factors.
Note: to suppress all conversions including those of numeric columns, set colClasses = "character".
Note that as.is is specified per column (not per variable) and so includes the column of row names (if any) and any columns to be skipped.
na.strings a character vector of strings which are to be interpreted as NA values. Blank fields are also considered to be missing values in logical, integer, numeric and complex fields. Note that the test happens after white space is stripped from the input, so na.strings values may need their own white space stripped in advance.
colClasses 表示读出的列的类型（"character"、"numeric"、"Date"等）
nrows 正整数，表示读入的最大行数
skip integer: the number of lines of the data file to skip before beginning to read data.
check.names logical. If TRUE then the names of the variables in the data frame 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.
fill logical. If TRUE then in case the rows have unequal length, blank fields are implicitly added. See ‘Details’.
strip.white logical. Used only when sep has been specified, and allows the stripping of leading and trailing white space from unquoted character fields (numeric fields are always stripped). See scan for further details (including the exact meaning of ‘white space’), remembering that the columns may include the row names.
blank.lines.skip logical: if TRUE blank lines in the input are ignored.
comment.char character: a character vector of length one containing a single character or an empty string. Use "" to turn off the interpretation of comments altogether.
allowEscapes logical. Should C-style escapes such as \n be processed or read verbatim (the default)? Note that if not within quotes these could be interpreted as a delimiter (but not as a comment character). For more details see scan.
flush logical: if TRUE, scan will flush to the end of the line after reading the last of the fields requested. This allows putting comments after the last field.
stringsAsFactors logical: should character vectors be converted to factors? Note that this is overridden by as.is and colClasses, both of which allow finer control.
fileEncoding character string: if non-empty declares the encoding used on a file (not a connection) so the character data can be re-encoded. See the ‘Encoding’ section of the help for file, the ‘R Data Import/Export Manual’ and ‘Note’.
encoding encoding to be assumed for input strings. It is used to mark character strings as known to be in Latin-1 or UTF-8 (see Encoding): it is not used to re-encode the input, but allows R to handle encoded strings in their native encoding (if one of those two). See ‘Value’ and ‘Note’.
text character string: if file is not supplied and this is, then data are read from the value of text via a text connection. Notice that a literal string can be used to include (small) data sets within R code.
skipNul logical: should nuls be skipped?


`header`	`header设置为TRUE，表示第一行的内容是每一列的名字`
`sep`	分隔符，默认sep = ""（空格）
`quote`	quote只对被当做character的列有效
`dec`	the character used in the file for decimal points.
`numerals`	string indicating how to convert numbers whose conversion to double precision would lose accuracy
`row.names`	行名的向量
`col.names`	列名的向量
`as.is`	the default behavior of `read.table` is to convert character variables (which are not converted to logical, numeric or complex) to factors. The variable `as.is` controls the conversion of columns not otherwise specified by `colClasses`. Its value is either a vector of logicals (values are recycled if necessary), or a vector of numeric or character indices which specify which columns should not be converted to factors. Note: to suppress all conversions including those of numeric columns, set `colClasses = "character"`. Note that `as.is` is specified per column (not per variable) and so includes the column of row names (if any) and any columns to be skipped.
`na.strings`	a character vector of strings which are to be interpreted as `NA` values. Blank fields are also considered to be missing values in logical, integer, numeric and complex fields. Note that the test happens after white space is stripped from the input, so `na.strings` values may need their own white space stripped in advance.
`colClasses`	表示读出的列的类型（"character"、"numeric"、"Date"等）
`nrows`	正整数，表示读入的最大行数
`skip`	integer: the number of lines of the data file to skip before beginning to read data.
`check.names`	logical. If `TRUE` then the names of the variables in the data frame 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.
`fill`	logical. If `TRUE` then in case the rows have unequal length, blank fields are implicitly added. See ‘Details’.
`strip.white`	logical. Used only when `sep` has been specified, and allows the stripping of leading and trailing white space from unquoted `character` fields (`numeric` fields are always stripped). See `scan` for further details (including the exact meaning of ‘white space’), remembering that the columns may include the row names.
`blank.lines.skip`	logical: if `TRUE` blank lines in the input are ignored.
`comment.char`	character: a character vector of length one containing a single character or an empty string. Use `""` to turn off the interpretation of comments altogether.
`allowEscapes`	logical. Should C-style escapes such as \n be processed or read verbatim (the default)? Note that if not within quotes these could be interpreted as a delimiter (but not as a comment character). For more details see `scan`.
`flush`	logical: if `TRUE`, `scan` will flush to the end of the line after reading the last of the fields requested. This allows putting comments after the last field.
`stringsAsFactors`	logical: should character vectors be converted to factors? Note that this is overridden by `as.is` and `colClasses`, both of which allow finer control.
`fileEncoding`	character string: if non-empty declares the encoding used on a file (not a connection) so the character data can be re-encoded. See the ‘Encoding’ section of the help for `file`, the ‘R Data Import/Export Manual’ and ‘Note’.
`encoding`	encoding to be assumed for input strings. It is used to mark character strings as known to be in Latin-1 or UTF-8 (see `Encoding`): it is not used to re-encode the input, but allows R to handle encoded strings in their native encoding (if one of those two). See ‘Value’ and ‘Note’.
`text`	character string: if `file` is not supplied and this is, then data are read from the value of `text` via a text connection. Notice that a literal string can be used to include (small) data sets within R code.
`skipNul`	logical: should nuls be skipped?