https:\/\/julialang.org\/downloads\/<\/a> link or else you can search Google for the following, \u201cDownload Julia\u201d.<\/p>\n\n\n\nStep-2:<\/strong> Download as per your machine bit configuration, i.e. 32-bit or 64-bit.<\/p>\n\n\n\nStep-3:<\/strong> After download run the .exe file <\/p>\n\n\n\nStep-4:<\/strong> Click the install button and furtherly go with the picture shown below.<\/p>\n\n\n\nStep-5:<\/strong> Click the checkbox to run Julia and click Finish<\/strong> as shown in the figure below.<\/p>\n\n\n\nStep-6<\/strong>: Now you can see a command line prompt which is also known as REPL<\/p>\n\n\n\n(Read-Eval-Print-Loop)<\/p>\n\n\n\n
Before going into another topic, let\u2019s see Julia\u2019s packages for data analysis and data science-related projects.<\/p>\n\n\n\n
We know about jupyter notebook and its popularity in data science and ML, which gives fast results and easy to handle the IDE. Similarly, we do have a notebook for Julia i.e<\/p>\n\n\n\n
Juno IDE but if you are familiar with notebook then go on with jupyter notebook. Let\u2019s see how we can set up the package for Julia notebook(IJulia).<\/p>\n\n\n\n
Open the Julia prompt and then type the following command:<\/p>\n\n\n\n
Julia> Pkg.add(\u201cIJulia\u201d)<\/p>\n\n\n\n
After you run the command, the necessary packages will be added or updated.<\/p>\n\n\n\n
After IJulia package is downloaded or updated you can type the following code to run it:<\/p>\n\n\n\n
Julia> using IJulia<\/p>\n\n\n\n
Julia> notebook()<\/p>\n\n\n\n
You will get by default notebook \u201cdashboard\u201d which opens in your home directory or in the installation folder where you have done the installation;
If you want to open the dashboard in a different directory then notebook(dir = \u201c\/some\/path\u201d).<\/p>\n\n\n\n
Data Structures Concept in Julia Programming Language<\/strong>
<\/strong><\/h2>\n\n\n\nLike every other programming language, Julia also has data structure concepts. Let\u2019s learn about some of these concepts that are used for data analysis.<\/p>\n\n\n\n
\n- Vector(Array) \u2013 <\/strong>A vector is a one-dimensional array which is similar to a normal array. In array, we use numbers followed by a comma as separator similarly in Julia also the vector(array) follows same.<\/li>\n<\/ol>\n\n\n\n
Let\u2019s have a look on a piece of code.<\/p>\n\n\n\n
In Julia, the index starts at \u20181\u2019. In the above code snippet, it begins with \u20180\u2019 since its python. <\/p>\n\n\n\n
\n- Matrix Operations<\/strong><\/li>\n<\/ol>\n\n\n\n
A matrix is another data structure that is widely used in linear algebra. We know that matrix is of a multidimensional array. Let\u2019s see dome operation of a matrix in Julia,<\/p>\n\n\n\n
A = [1 2 3; 4 5 6; 7 8 9] # semi-column is used to change rows<\/strong><\/p>\n\n\n\n When we print, it looks like: 1 2 3<\/strong><\/p>\n\n\n\n 4 5 6<\/strong><\/p>\n\n\n\n 7 8 9<\/strong><\/p>\n\n\n\n In order access element, say A [1,2] = 2<\/strong><\/p>\n\n\n\nNow for transpose of a matrix, A\u2019<\/strong> then the following result will look like:<\/p>\n\n\n\n A\u2019 = 1 4 7<\/strong><\/p>\n\n\n\n 2 5 8<\/strong><\/p>\n\n\n\n 3 6 9<\/strong><\/p>\n\n\n\n\n- Dictionary<\/strong><\/li>\n<\/ol>\n\n\n\n
Another data structure is the dictionary, which is an unordered key-value pair, and the keys are always unique.<\/p>\n\n\n\n
Let\u2019s have a look on the dictionary implementation,<\/p>\n\n\n\n
D = Dict (\u201cstring1\u201d => \u201cHello\u201d, \u201clength\u201d => 5) #create dictionary<\/strong><\/p>\n\n\n\n It will get result : string => Hello<\/p>\n\n\n\n
Length => 5<\/p>\n\n\n\n
Suppose in-order to access the dictionary we will access the key of dictionary then the value will give us as result<\/p>\n\n\n\n
D[\u201clength]<\/strong><\/p>\n\n\n\n o\/p: 5<\/strong><\/p>\n\n\n\nto get count of dictionary use object. Count i.e D.count<\/strong><\/p>\n\n\n\nOperations of Dictionary:<\/strong><\/p>\n\n\n\n\n- Creation\u00a0 \u00a0 \u00a0 \u00a0 = <\/strong>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Dict(\u201ca\u201d => 1, \u201cb\u201d => 2)<\/strong><\/li>\n\n\n\n
- Addition\u00a0 \u00a0 \u00a0 \u00a0 =\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 d[\u201cc\u201d] = 3<\/strong><\/li>\n\n\n\n
- Removal\u00a0 \u00a0 \u00a0 \u00a0 =\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 delete !(d, \u201cb\u201d)<\/strong><\/li>\n\n\n\n
- Lookup\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 =\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 get(d,\u201da\u201d, 1)<\/strong><\/li>\n\n\n\n
- Update \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 =\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 d[\u201ca\u201d] = 10<\/strong><\/li>\n<\/ol>\n\n\n\n
Strings<\/strong><\/p>\n\n\n\nNext data structure is strings , strings are generally written within the quotes as {\u201c \u201d} i.e inverted commas. Similar to the python in Julia also once string is created it cannot be changes as they are immutable.<\/p>\n\n\n\n
Lets have a look,<\/p>\n\n\n\n
Text = \u201cHello world\u201d<\/strong><\/p>\n\n\n\n print(Text[1]) # will gives first character of string as H<\/strong><\/p>\n\n\n\n Print(Text.length) # will gives the length of string 11<\/strong><\/p>\n\n\n\nThere are three key phases of data structures that are used in data analysis <\/p>\n\n\n\n
\n- Data Exploration<\/strong><\/li>\n<\/ol>\n\n\n\n
<\/strong>It\u2019s all about finding the data more than what we have<\/p>\n\n\n\n\n- Data Munging<\/strong><\/li>\n<\/ol>\n\n\n\n
<\/strong>Cleaning the data and use that data for making better statistical models<\/p>\n\n\n\n\n- Predictive Modelling\u00a0<\/strong><\/li>\n<\/ol>\n\n\n\n
Final thing is run the algorithm and have fun<\/p>\n\n\n\n
Loops, Conditions In Julia<\/strong><\/p>\n\n\n\nLike other programming languages Julia also uses the loops and conditional statements<\/p>\n\n\n\n
For loop<\/p>\n\n\n\n
While Loop<\/p>\n\n\n\n
If condition <\/p>\n\n\n\n
These are most commonly used loops and condition statement in Julia as well as other programming languages<\/p>\n\n\n\n
If and else<\/strong><\/p>\n\n\n\nIn Julia we need not to worry about spaces, identation, semicolon, brackets etc instead just add end at the end of statement or condition. Lets have the syntax for if and else<\/p>\n\n\n\n
Syntax: if condition<\/p>\n\n\n\n
Statement<\/p>\n\n\n\n
else<\/p>\n\n\n\n
Statement<\/p>\n\n\n\n
end<\/p>\n\n\n\n
if elseif and else<\/strong><\/p>\n\n\n\nIt also follows same as if else block follows. Let\u2019s have look on syntax<\/p>\n\n\n\n
Syntax: if condition<\/p>\n\n\n\n
Statement<\/p>\n\n\n\n
elseif<\/p>\n\n\n\n
Statement<\/p>\n\n\n\n
else<\/p>\n\n\n\n
Statement<\/p>\n\n\n\n
End<\/p>\n\n\n\n
Lets take an example to the above we discuused<\/p>\n\n\n\n
If x > 0<\/p>\n\n\n\n
\u201cPositive\u201d<\/p>\n\n\n\n
else if x < 0<\/p>\n\n\n\n
\u201cNegative\u201d<\/p>\n\n\n\n
else<\/p>\n\n\n\n
\u201cWhole Number\u201d<\/p>\n\n\n\n
Lets talk about loops in Julia.<\/p>\n\n\n\n
For Loop<\/strong><\/h2>\n\n\n\nThe only difference to the loop for with other languages for loop is, in Julia for loop will have start and end counter.<\/p>\n\n\n\n
Julia> for i in 0: 10: 100<\/p>\n\n\n\n
Print(i)<\/p>\n\n\n\n
end<\/p>\n\n\n\n
will gives result as: 0 10 20 30 40 50 60 70 80 90 100<\/p>\n\n\n\n
Julia> for a in [\u201cred\u201d, \u201cgreen\u201d, \u201cyellow\u201d]<\/p>\n\n\n\n
Print(a, \u201c \u201c)<\/p>\n\n\n\n
end<\/p>\n\n\n\n
Will give result as : red green yellow<\/p>\n\n\n\n
Julia> for a in Dict(\u201cname\u201d => \u201corange\u201d, \u201csize\u201d => 6)<\/p>\n\n\n\n
Print(a)<\/p>\n\n\n\n
end<\/p>\n\n\n\n
Name => orange Size -=> 6<\/p>\n\n\n\n
Similarly we can also iterate through 2D array, lets have look on that<\/p>\n\n\n\n
A = reshape(1:50, (3, 3))<\/p>\n\n\n\n
for I in A<\/p>\n\n\n\n
Print(I, \u201c \u201c)<\/p>\n\n\n\n
end<\/p>\n\n\n\n
The result will be as 1 2 3 4 5 6 7 8 9 \u2026\u2026\u2026\u2026..50<\/p>\n\n\n\n
We can also use inside of functions <\/p>\n\n\n\n
function()<\/p>\n\n\n\n
for condition<\/p>\n\n\n\n
Statement<\/p>\n\n\n\n
end<\/p>\n\n\n\n
return <\/p>\n\n\n\n
end<\/p>\n\n\n\n
We know that scope of an variable inside a method or function will exists until its life span is not yet done once method or function ends and comes out then the variable scope is zero or dead<\/p>\n\n\n\n
Function()<\/p>\n\n\n\n
K = 2<\/p>\n\n\n\n
for I in 1:10 :50<\/p>\n\n\n\n
K = k*i<\/p>\n\n\n\n
end<\/p>\n\n\n\n
return<\/p>\n\n\n\n
end<\/p>\n\n\n\n
if we want to persist the variable to be exist in the function or method then use keyword \u201cglobal\u201d before variable name.<\/strong><\/p>\n\n\n\ncontinue and break<\/strong> are the condition statements used in between the loops <\/p>\n\n\n\nfor I 10:5:20 <\/p>\n\n\n\n
print(i) <\/p>\n\n\n\n
continue <\/p>\n\n\n\n
end <\/p>\n\n\n\n
comprehensions<\/strong><\/p>\n\n\n\nsimilar to python Julia also supports comprehensions <\/p>\n\n\n\n
Julia> s = set([a for a in 1: 8])<\/p>\n\n\n\n
Set([6,4,5,7,1,3,2,8])<\/p>\n\n\n\n
Julia> [(a,b) for a in 1:5, c in 1:2]<\/p>\n\n\n\n
(1,1) (1,2)<\/p>\n\n\n\n
(2,1) (2,2)<\/p>\n\n\n\n
(3,1) (3,2)<\/p>\n\n\n\n
(4,1) (4,2)<\/p>\n\n\n\n
(5,1) (5,2)<\/p>\n\n\n\n
Generator Expressions<\/strong><\/p>\n\n\n\n Like comprehensions generating expressions can also be used to produce result using iterable variable.<\/p>\n\n\n\n
Let\u2019s have a look on the example <\/p>\n\n\n\n
Julia> sum( x^2 for x in 1:10)<\/strong><\/p>\n\n\n\n 385<\/strong><\/p>\n\n\n\nNested Loops<\/strong><\/p>\n\n\n\n Nested loops in Julia is quite different as of writing loop inside another loop is known to be as nested loops. But, in Julia we need not make duplicate loops instead we can use<\/p>\n\n\n\n
@show(var1, var2) variables with comma separated<\/p>\n\n\n\n
Have a loop on the piece of code for better understanding<\/p>\n\n\n\n
for a in 1 : 10, y in 1: 10<\/p>\n\n\n\n
@show (x,y)<\/p>\n\n\n\n
Result will be:<\/p>\n\n\n\n
(x,y) = (1,1)<\/p>\n\n\n\n
(x,y) = (1,2)<\/p>\n\n\n\n
(x,y) = (1,3)<\/p>\n\n\n\n
(x,y) = (1,4)<\/p>\n\n\n\n
(x,y) = (1,5)<\/p>\n\n\n\n
(x,y) = (1,6)<\/p>\n\n\n\n
(x,y) = (1,7)<\/p>\n\n\n\n
(x,y) = (1,8)<\/p>\n\n\n\n
\u2026\u2026\u2026\u2026\u2026<\/p>\n\n\n\n
(x,y) = (10,10)<\/p>\n\n\n\n
@show is an macro that prints the names and values<\/strong><\/p>\n\n\n\n @time will gives the complexity of loops<\/strong><\/p>\n\n\n\nJulia> x = rand(1000);<\/p>\n\n\n\n
Julia> function sum()<\/p>\n\n\n\n
A = 0.0<\/p>\n\n\n\n
For I in x<\/p>\n\n\n\n
A + = i<\/p>\n\n\n\n
End<\/p>\n\n\n\n
Return A<\/p>\n\n\n\n
End<\/p>\n\n\n\n
Julia> @time sum()<\/p>\n\n\n\n
0.017705 seconds (15. 28k allocations: 694. 484 kiB)<\/p>\n\n\n\n
496.84883432553846 <\/p>\n\n\n\n
While Loop<\/strong><\/p>\n\n\n\nSame as for loop while as performs only when condition is true. The following syntax is<\/p>\n\n\n\n
While condition<\/p>\n\n\n\n
Statements<\/p>\n\n\n\n
End<\/p>\n\n\n\n
Let\u2019s have an example<\/p>\n\n\n\n
Julia> x = 0<\/p>\n\n\n\n
0<\/p>\n\n\n\n
Julia> while x < 3<\/p>\n\n\n\n
Print(x)<\/p>\n\n\n\n
global x+ = 1<\/p>\n\n\n\n
end<\/p>\n\n\n\n
result: 0 1 2<\/p>\n\n\n\n
And finally Exceptions with loops, like other programming language Julia also have try, catch blocks.<\/p>\n\n\n\n
Julia> s = \u201capple\u201d<\/p>\n\n\n\n
try<\/p>\n\n\n\n
S[1] = \u201ca\u201d<\/p>\n\n\n\n
catch e<\/p>\n\n\n\n
Print(\u201ccaught an error: $e\u201d)<\/p>\n\n\n\n
End<\/p>\n\n\n\n