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Statistical Computing with R学到的知

Statistical Computing with R学到的知

作者: kkkkkkang | 来源:发表于2022-01-25 15:29 被阅读0次

    不知道怎么敲,但常用到的帮助

    ?Syntax
    
    :: :::  access variables in a namespace
    $ @ component / slot extraction
    [ [[    indexing
    ^   exponentiation (right to left)
    - + unary minus and plus
    :   sequence operator
    %any% |>    special operators (including %% and %/%)
    * / multiply, divide
    + - (binary) add, subtract
    < > <= >= == != ordering and comparison
    !   negation
    & &&    and
    | ||    or
    ~   as in formulae
    -> ->>  rightwards assignment
    <- <<-  assignment (right to left)
    =   assignment (right to left)
    ?   help (unary and binary)
    
    # 其它的不一一列举了
    ?Arithmetic
    ?Comparison #relational operators
    ?Extract #operators on vectors and arrays
    ?Control #control flow
    ?Logic #logical operators
    

    特殊符号的帮助文档如何获取?

    # 加上双引号
    > ?%/%
    Error: unexpected SPECIAL in "?%/%"
    > ?"%/%"
    # 或者直接问Arithmetic,有很多
    > ?Arithmetic
    
    Arithmetic {base}   R Documentation
    Arithmetic Operators
    Description
    These unary and binary operators perform arithmetic on numeric or complex vectors (or objects which can be coerced to them).
    
    Usage
    + x
    - x
    x + y
    x - y
    x * y
    x / y
    x ^ y
    x %% y
    x %/% y
    

    查看R可用的颜色,DAAG包

    install.package("DAAG")
    library(DAAG)
    show.colors(type = c("singles"))
    show.colors(type = c("shades"))
    show.colors(type = c("gray"))
    
    singles
    shades
    gray

    然后就可以选里面颜色用了,记不住可以把这个图当桌面。

    ToothGrowth$dose <- as.factor(ToothGrowth$dose)
    head(ToothGrowth)
    library(ggplot2)
    library(DAAG)
    ggplot(ToothGrowth, aes(x=dose, y=len)) + 
        geom_boxplot()
    ggplot(ToothGrowth, aes(x=dose, y=len,color=dose)) + 
        geom_boxplot()+
        scale_color_manual(values=c("magenta", "magenta3", "magenta4"))
    
    image.png

    导入文件时,不作为因子,as.is = TRUE

    fileloc <- "https://archive.ics.uci.edu/ml/machine-learning-databases/
    auto-mpg/auto-mpg.data"
    df <- read.table(file = fileloc, na.strings = "?", as.is = TRUE)
    # na.strings指定哪个符号被认为是NA
    

    按照概率取样

    > x <- sample(1:3, size = 100, replace = TRUE,
    prob = c(.2, .3, .5))
    > table(x)
    x
    1 2 3
    17 35 48
    

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