Operation

Julia

MATLAB

Python

Comment

% comment

% comment

# comment

Multi-line comment

#= ... =#

%{ ... %}

""" ... """

Assignment

x = 10

x = 10

x = 10

Dynamic typing

x = 1; x = "hi"

x = 1; x = "hi"

x = 1; x = "hi"

Type verification

typeof(x)

class(x)

type(x)

An integer

x = 10

x = int64(10)

x = 10

A floating-point number

x = 1.5

x = 1.5

x = 1.5

A complex number

1 + 2im

1 + 2i

1 + 2j

Infinity

Inf

Inf

float("inf")

NaN

NaN

NaN

float("nan")

Line

s = "Hello"

s = "Hello"

s = "Hello"

String interpolation

"x = $x"

sprintf("x = %d", x)

f"x = {x}"

String concatenation

"a" * "b"

["a" "b"]

"a" + "b"

Repeating a line

"Hеllo"^3

repmat("Hеllo",1,3)

"Hello"*3

Creating an array/vector

[1,2,3]

[1,2,3]

[1,2,3]

The matrix

[1 2; 3 4]

[1 2; 3 4]

np.array([[1,2],[3,4]])

Indexing starts with

1

1

0

Access to the element

A[1,2]

A(1,2)

A[0,1]

The last element

A[end]

A(end)

A[-1]

Cross-section of an array

A[1:3]

A(1:3)

A[0:3]

Logical indexing

A[A .> 0]

A(A > 0)

A[A > 0]

Size of the array

size(A)

size(A)

A.shape

Length of the array

length(A)

length(A)

len(A)

Creating a null array

zeros(3,3)

zeros(3,3)

np.zeros((3,3))

Creating a unit matrix

I(3) / Matrix(I,3,3)

eye(3)

np.eye(3)

Range

1:10

1:10

range(1,11)

Range step

1:2:10

1:2:10

range(1,11,2)

Element-wise multiplication

A .* B

A .* B

A * B

Matrix multiplication

A * B

A * B

A @ B

Piecemeal degree

A .^ 2

A .^ 2

A ** 2

Matrix division

A \ b

A \ b

np.linalg.solve(A,b)

Transposition

A'

A'

A.T

Concatenating arrays horizontally

[A B]

[A B]

np.hstack((A,B))

Concatenating arrays vertically

[A; B]

[A; B]

np.vstack((A,B))

The if condition

if x > 0 ... end

if x > 0 ... end

if x > 0:

The ternary operator

x > 0 ? a : b

ifelse(x>0,a,b)

a if x>0 else b

The for loop

for i in 1:10 ... end

for i in 1:10 ... end

for i in range(10):

The while loop

while x > 0 ... end

while x > 0 ... end

while x > 0:

Cycle interruption

break

break

break

Skipping an iteration

continue

continue

continue

Function (briefly)

f(x)=x^2

f = @(x) x^2

f = lambda x: x**2

Function (normal)

function f(x) ... end

function y=f(x) ... end

def f(x):

Return of the value

return x

return x

return x

Anonymous function

x -> x^2

@(x) x^2

lambda x: x**2

List Generator

[x^2 for x in 1:5]

arrayfun(@(x)x^2,1:5)

[x**2 for x in range(1,6)]

Dictionary

Dict("a"=>1)

containers.Map()

{"a":1}

Plenty

Set([1,2])

unique([...])

set([1,2])

Checking the accessories

x ∈ A

ismember(x,A)

x in A

Exception handling

try ... catch e ... end

try ... catch ... end

try ... except Exception as e:

Error generation

error("msg")

error("msg")

raise Exception("msg")

Structure/Class

struct Point ... end

classdef Point ... end

class Point:

The abstract type

abstract type Shape end

classdef (Abstract)

from abc import ABC

Importing a module

using LinearAlgebra

import pkg.*

import numpy as np

Connecting a file

include("a.jl")

run("a.m")

import module

Documentation of the function

""" doc """

% help text

""" doc """

Macros

@time, @show

missing

missing

Measuring time

@time expr

tic; ...; toc

timeit()

Output to the console

println(x)

disp(x)

print(x)

Formatted output

@printf

fprintf

print(f"...")

Working with the DataFrame

DataFrame(...)

table(...)

pd.DataFrame(...)

Charts

plot()

plot()

matplotlib.pyplot.plot()

A random number

rand()

rand()

random.random() / np.random.rand()

Sorting

sort(A)

sort(A)

sorted(A)

Map function

map(f,A)

arrayfun(f,A)

map(f,A)

Filtering

filter(f,A)

A(mask)

filter(f,A)

Equality check

==

==

==

Identity verification

===

isequal

is

Missing value

missing

missing

None / np.nan

Nothing / null

nothing

[]

None