Python is a widely used high-level interpreted programming language for general-purpose programming. Python 3.x will be used which presents some changes in terms of syntax and lots of improvements from Python 2.x, while the two major versions are not backward compatible.

Anaconda is a distribution of Python with other packages needed for Data Mining.

Visual Studio Code (VS Code) is a code editor with support for most programming languages. Alternative: you can use any text editor e.g. Notepad++

Libraries are commonly installed using the pip package manager if they are not already included in the Anaconda distribution:

• NumPy is the fundamental package for scientific computing with Python.

• Scipy is a Python-based ecosystem of open-source software for mathematics, science, and engineering

• Scikit-learn is a simple and efficient tool for data mining and data analysis

• Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

• Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.

Installing a library (e.g. numpy) in Python is as simple as running the following command in the terminal:

pip install numpy

• Install Anaconda e.g. https://www.anaconda.com/distribution/ (already installed)
• Create a new file and save it as e.g. lab1.py
• Open with e.g. Notepad++
• Write a simple Python program e.g.

  print("hello world")

• Open the terminal in the current folder (Shift+Right click>Open command window here) and run the program from the command line e.g.

  python lab1.py

*The Python version should be specified if there are multiple distributions installed (e.g. 2.7, 3.6, 3.7) such as (depending on the installed environment and distribution):

python3 lab1.py
python3.7 lab1.py
py -3 lab1.py

The same applies for installing packages using pip:

pip install numpy
pip3 install numpy
pip3.7 install numpy
py -3 -m pip install numpy

python3.7 script.py

pip3.7 install numpy

Python is an interpreted dynamically-typed language. Data type specification is not required when creating a variable (but can be specified in modern Python). Creating a variable is as simple as:

a = 10

a: int = 10

*Why would types be useful in Python?

Numbers in Python can be integers or floating point (real) and also Decimal and Fraction.

Operations:

• addition:

  4+5=9, 4.3+4.2=8.5

• subtraction:

  4-5=-1, 4.3-8.2=-3.9

• division:

  5/2=2.5

• division discards the fractional part:

  5//2=2

• remainder of the division:

  5%2=1

• power:

  3**4=81

# create a numeric variable
a = 10
b = 20
 
# print the value
print(a)
 
# addition
s = a + b
print(s)
 
# fractions
from fractions import Fraction
 
print(Fraction(16, -10))
 
# decimal
from decimal import *
 
print(Decimal(1) / Decimal(7))
print(1/7)

Strings are used to represent text or a sequence of characters. Python can operate with strings which can be expressed in several ways

# declaring strings
s1 = 'Python'
s2 = "Programing"
 
# declaring unicode strings:
us1 = u"Ciprian Truică"
us2 = u'Ciprian Truică'

Operations:

• Concatenation

  s3 = s1 + " " + s2

• Multiplication with a scalar

  s4 = "alibec" * 3

• Getting a character from a specific index

  s3[5]

• Getting the length of a string

  len(s3)

• Getting sub-strings
  • characters between 2 indexes

    s3[2:4]

  • first n elements

    s3[:n]

  • last n elements

    s3[len(s3)-n:]
    s3[-n:]

Functions:

• len returns the length of the string

  len(s3)

• replace is used for replacing a substring by another substring

  s3.replace("Python", "Fun")

• split is used for splitting a string into substrings based on a given token/delimiter

  s3.split(" ")

s3[2] = "a"

Python knows several compound data types, used to group together other values. The most versatile is the list, which can be written as a list of comma-separated values (items) between square brackets.

list1 = [1, 4, 9, 25]
list2 = [36, 49, 65, 81, 100]

Operations:

• Concatenation

  list3 = list1 + list2

• Multiplication with a scalar

  list4 = list1 * 3

• Getting an element from a specific index

  list3[5]

• Getting the length of a list

  len(list3)

• Getting sub-lists
  • characters between 2 indexes

    list3[2:4]

  • first n elements

    list3[:n]

  • last n elements

    list3[len(list3)-n:]
    list3[-n:]

list2[2] = 65

Matrices are lists of lists:

m = [ [1, 2], [3, 4] ]

In computer programming, a statement is a syntactic unit of a programming language that expresses some action to be carried out. Examples of statements in Python include if else, for in, while

If else statements are used to allow programmers to ask questions and then, based on the result, perform different actions.

if exp1:
   # do something
elif exp2:
   # do something else
else:
   # do something else

n=int(input("Enter a number"))

For loops are used to iterate though a list of values, useful when performing repeated actions with a defined number of iterations.

for elem in list1:
   # do something

While loops are used to iterate until a condition that is true becomes false.

while exp:
   # do something