R Part- 4

Here we go with next set of commands. In this page we will see datatype conversion. As we are going to handle with different types of data and we should also know how to convert from one type to another. Here we go!
R has many datastructures. It includes

• Vector
• List
• Matrix
• Data Frame
• Factors

• Tables
  Now let us see how to do conversion

  Converting Vector to Data Frame

  SampleVector = c(7,4,2,9)
  View(SampleVector)
  DataFrame = as.data.frame(Sample_Vector)
  View(DataFrame)

  Output for above commands in screenshot

  Now we will see how to convert from numeric to factor, numeric to categorical, categorical to numeric,

  Numeric to Factor conversion

  mc = mtcars
  str(mc)
  mc$cyl = as.factor(mc$cyl)
  mc$vs = as.factor(mc$vs)
  str(mc)

  Output for above commands in screenshot

  

  Numeric to Categorical conversion

  mc$mpgcat[mc$mpg >= 10 & mc$mpg <=16] = “Low”
  mc$mpgcat[mc$mpg >= 16 & mc$mpg <=20] = “Medium”
  mc$mpgcat[mc$mpg >20] = “High”

  Output for above commands in screenshot

  

  Categorical to Numeric Conversion

  TempObj = c(rep(“Medium”, 30), rep(“poor”, 30), rep(“Rich”, 40))
  TempObj1 = factor(TempObj, labels = (1:length(levels(factor(TempObj)))))
  TempObj2 = as.numeric(TempObj1)

  Output for above commands in screenshot

  

With this we will end up R, From next, we will start with Python. I will also check out for missed commands in R and update in middle, meanwhile lets start to learn python!!!!