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Julia meetup bangalore

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Julia meetup @ InMobi 19/4/2014

Julia meetup @ InMobi 19/4/2014

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Transcript

  • 1. Github Stats
  • 2. Commits
  • 3. Code Frequency
  • 4. Strings
  • 5. Character julia> ’x’ ’x’ julia> typeof(ans) Char
  • 6. Character julia> ’A’ < ’a’ True julia> ’A’ + 1 ’B’
  • 7. String julia> str = “Hello, world.” “Hello, world.” julia> str[1] ’H’ julia> str[4:9] "lo, wo“
  • 8. String julia> greet = "Hello" "Hello“ julia> whom = "world" "world“ julia> string(greet, ", ", whom, ".n") "Hello, world.n"
  • 9. Introduction to DataFrames
  • 10. julia> Pkg.add("DataFrames") julia> Pkg.add("RDatasets") julia> using DataFrames julia> using RDatasets
  • 11. julia> v = @data([NA, 3, 2, 5, 4]) julia> mean(v)
  • 12. The NA type: Represents a missing value Like NULL in some systems Poisons other values Like NaN for floating point numbers
  • 13. julia> 1 + NA NA julia> 1 > NA NA julia> isna(NA) true
  • 14. A DataFrame is a list of DataVector's DataFrame's allow mixed indexing: Columns by number Columns by name Rows + Columns by number + number Rows + Columns by number + name
  • 15. df = DataFrame() df[:A] = 1:8 df[:B] = ["M", "F", "F", "M", "F", "M", "M", "F"] df
  • 16. using Rdatasets iris = dataset("datasets", "iris") head(iris)