Beginner’s Notes in JULIA Language

• Packages

1. Pkg.add(“RDatasets ”)  installs package RDatasets
2. using  RDatasets –loads package RDatasets
3. Pkg.update() Updates all packages

some packages to install IJulia, RDatasets, PyCall,PyPlot,Gadfly,Rif

• Data Input -pwd() – Gets you the current working directory

1. cd(“C:/Path”) -Sets the working directory to the new path , here C:/Path
2. readdir() – Lists all the files present in the current working directory
3. using DataFrames

a=readtable(“1.csv”)

or df=readtable(“adult.data.txt”,header=false)

or

df= collect(readdlm(“adult.csv”))

or from package

Using RDatasets

iris=dataset(“datasets”,”iris”)

• Object Inspection

1. summary(a) Gives the structure of object named  including class, dimensions,
2. colnames(a) Gives the names of variables of the object
3. typeof(a) Gives the class of a object like data.frame, list,matrix, vector etc

size(a) Givesthe dimension of object (rows column)

Plots

using Gadfly

plot(df,x=”x1″ ,color=”x15″,Geom.histogram)

plot(iris,x=”SepalLength”,y=”SepalWidth”,color=”Species”)

using PyPlot

boxplot(df[:x15])

Note- we can use df[:x15] notation to refer to x15 variable in Data Frame df

For missing values we use Data Arrays and @data to convert object to Data Array

Then use removeNA ( or dropna in Julia 0.3) to remove missing values so as to run functions like mean etc

The describe function gives the numerical summary

describe(df[:x1])

Min      17.0
1st Qu.  28.0
Median   37.0
Mean     38.58164675532078
3rd Qu.  48.0
Max      90.0
NAs      0
NA%      0.0%

NOTES-

1) Doesnt work very well on Win 32

2) Two interfaces – command line or IJulia Notebook

3) If you type an object name , gives you the first twenty and last twenty rows- which is quite intuitive designed.

4) PyCall is an interface to Python and Rif is an interface to R- but I had issues trying to work with Rif

5) Basically even simple things( functions!) are renamed in Julia- the effort seems to keep it distinct with R

6) PyPlot for basic plots and Gadfly for ggplot2 plots

Note- some of it was shown here-Updated

http://nbviewer.ipython.org/gist/decisionstats/62c5387624a9ba9015a4

Author: Ajay Ohri

http://about.me/ajayohri View all posts by Ajay Ohri