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R: Apply Functions
 

R: Apply Functions

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R: Apply Functions

R: Apply Functions

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    R: Apply Functions R: Apply Functions Presentation Transcript

    • Apply functions
      The Dataminingtools.net Team
    • Apply functions
      Apply functions are used to execute a function repetitively. "Apply" functions keeps us from having to write loops to perform some operation on every row or every column of a matrix or data frame, or on every element in a list.
    • Apply family
      sapply()
      lapply()
      apply()
      • mapply()
      • tapply()
      • rapply()
    • Usage
      Using Loops!
      > avg <- numeric (8)
      > avg
      [1] 0 0 0 0 0 0 0 0
      > for(i in 1:8)
      + avg[i]<-mean(state.x77[,i])
      > avg[i]
      [1] 70735.88
      > avg
      [1] 4246.4200 4435.8000 1.1700 70.8786 7.3780
      [6] 53.1080 104.4600 70735.8800
    • Usage
      Using ‘apply’
      > apply (state.x77, 2, median)
      Population Income Illiteracy Life Exp Murder
      2838.500 4519.000 0.950 70.675 6.850
      HS Grad Frost Area
      53.250 114.500 54277.000
      The 2 means "go by column" -- a 1 would have meant "go by row."
    • Usage
      We construct a function and pass it to apply. It computes the median and maximum of each column of state.x77.
    • Usage
       apply() works on each row, one at a time, to find the smallest number in each row. which() function, returns the indices within a vector for which the vector holds the value TRUE
    • lapplyand sapply
      The lapply() function works on any list. The "l" in "lapply" stands for "list."
      The "s" in "sapply" stands for "simplify."
    • tapply
      tapply() is a very powerful function that lets us break a vector into pieces and apply some function to each of the pieces. It is like sapply(), except that with sapply() the pieces are always elements of a list. With tapply() we get to specify how the breakdown is done.
      >tapply(barley$yield, barley$site, mean)
      Grand Rapids Duluth University Farm Morris Crookston Waseca
      24.93167 27.99667 32.66667 35.4 37.42 48.10833