Python introduction towards data science

A Brief Introduction
to
Python
By.
Deepak Teja. P

Agenda
 What is a programming language ? & why we use it ?
 Different Programming languages.
 What is Python…?
 History of Python
 Scope of Python
 Applications of Python?
 Installing Python IDE
 What can I do with python
 A Sample Code.

What is a programming language ?
& why we use it ?

Different Programming languages.
 High Level Language
- High level languages are written in a form that is
close to our human language, enabling to programmer
to just focus on the problem being solved.
- No particular knowledge of the hardware is needed
as high level languages create programs that are
portable and not tied to a particular computer or micro
chip. These programmer friendly languages are called
‘high level’ as they are far removed from the machine
code instructions understood by the computer.
- It considers only Business logics but memory
issues are taken care by garbage collector

 Low level language
- Low-level languages are written to meet the needs
of particular computer architecture and hardware
requirements. Machine code is low level because it runs
directly on the processor. Low-level languages are
appropriate for writing operating systems or firmware for
micro-controllers.
-It considers only Memory issues
Note: Business logic is the programming that manages communication
between an end user interface and a database. The main components
of business logic are business rules and workflows.

Examples
 High Level Language
◦ Java, Python, Pascal, COBOL, FORTRAN,
BASIC
 Middle Level Language
◦ C,
 Low Level Language
◦ Assembly language (Assembler, Forth)

What is Python…?
 Python is a general purpose
programming language that is
often applied in scripting roles.
 So, Python is programming
language as well as scripting
language.
 Python is also called as Interpreted
language

Differences between program and
scripting language
 Basically, all scripting languages are
programming languages. The theoretical
difference between the scripting language
and programming language is that in case
of programming language we need to save
the program then compile and then run it,
but in script language like java script we
have to save the code and then direct run it
we need not to compile the script language
program.

History of Python
Guido van Rossum

 Developed in 1991
 Originally Started in 1989
 Developed by Guido Van Rosbum in
Netherlands
 Name python came from a comic show
“Monty’s python flying circus comic show”
telecasted in BBC-Netherlands from 1967
to 1974

Versions of Python
 Version 1.0 to 1.x
 25 October 1996- 5 September 2000.
 16 October 2000- 02 March 2019
 3 December 2008- 25 March 2019.

Applications of Python
 Web Applications
 Desktop GUI (graphical user interface)
Applications
 Software Development
 Scientific and Numeric
 Business Applications
 Embedded System development
 IoT Development
 Windows Azur
 Devops
 Network Applications
 Game Development, Etc.,

 Advantages Python
◦ Less code
◦ Simple Syntax
◦ Faster Execution
 Features of Python
◦ Easy to Read
◦ Easy to Maintain
◦ Easy to learn

Installation of Python
 Python is pre-installed on most Unix
systems, including Linux and MAC
OS X
 But for in Windows Operating Systems
, user can download from the
https://www.python.org/downloads/
 From the above link download latest
version of python IDE and install,
recent version is 3.7.3 but most of
them uses version 2.7.7 only

Who uses python
 Google makes extensive use of Python
in its web search system, and
employs Python’s creator.
 Intel, Cisco, Hewlett-Packard, Seagate,
Qualcomm, and IBM use Python for
hardware testing.
 ESRI (Environmental Systems Research Institute)
uses Python as an end-user
customization tool for its popular GIS
mapping products.
 The YouTube video sharing service is
largely written in Python.

What we can do with Python
 Graphical User Interface Programming
Internet Scripting
 Gaming, Images, XML , Robot and
more
 System programming
 Component Integration Database
Programming

Python Code Execution
PVM is which help to execute the python program.
PVM: Python Virtual Machine

 More to Discuss:
-Python is a case sensitive language
-Difference between Command prompt &
IDLE
IDLE(Interactive development
environment)
-Example of Python Program

What are operators in python?
 Operators are special symbols in
Python that carry out arithmetic or
logical computation. The value that the
operator operates on is called the
operand.

Operators in Python
 Arithmetic Operators
◦ +, -, *, /, %, //
 Comparison/Relational Operators
◦ <, >, <=, >=, ==, !=
 Logical Operators
◦ AND, OR, NOT
 Bit Wise Operators
◦ &, | , ~, x, ^
 Assignment Operators
◦ ==, *=, +=, -=, /=

 Difference between %, // & /
5 / 2 will return 2.5 and 5 // 2 will return 2 . The
former is floating point division, and the latter is floor
division, sometimes also called integer division.
% : Gives the reminder of the two numbers.
Example:
x= 4
y= 2
print(x%y)
print(x//y)
print(x/y)
 Output:
◦ 0
◦ 2
◦ 2.0

Comparison/Relational
Operators
 Comparison or Relational operators are used to
compare two things or to find the relation between
two entities.
 == Equals to
 != Not equals
 Example:
x=4
y=3
print(x==y)
print(x!=y)
Output:
False
True

Logical gates
 AND gate  OR gate
 Not gate  ExOR gate

Logical Operators
 And:
True if both the operands are true x and
y
 Or:
True if either of the operands is true x or
y
 Not:
True if operand is false (complements
the operand)

Example:
x=1
y=0
print(x and y)
print(x or y)
print(not x)
Output:
0
1
False

Bit Wise Operators
 & : And
 |: OR
 ~ : Complement/NOT
 ^ : XOR
 >> : Right Shift
 << : Left Shift
 Note: Bit wise operator first converts given
number into a binary number and performs
the operations

Example of Bit Wise operator
a = 10
b = 4
Print bitwise AND operation
print(a & b)
Print bitwise OR operation
print(a | b)
Print bitwise NOT operation
print(~a)
Print bitwise XOR operation
print(a ^ b)
Print bitwise right shift operation
print(a >> 2)
print bitwise left shift operation
print(a << 2)
Output
0
14
-11
14
2
40

Difference between Logical & Bit
wise operators
Example :
x=1
y=0
a=True
b=False
print(x and y)
print(x or y)
print(not x)
print(not y)
print(not a)
print(not b)
print(x&y)
print(x|y)
print(a & b)
print(a | b)
print(~x)
Output:
0
1
0
1
False
True
0
1
False
True

Assignment Operators
 == or =
 +=
 -=
 *=
 /=

Number conversions
S.No Type Python Number Representation
in output
1 Binary Bin 2 0b
2 Octal Oct 8 0o
3 Hexadecimal hex 16 0x

Decimal Conversions
 To convert Octal, Hexadecimal, Binary
to decimal we can use below
statement.
 Binary to Decimal
◦ print(int(“Binary number”,2))
 Octal to Decimal
◦ print(int(“Octal”,8))
 Hexadecimal to Decimal
◦ print(int(“Hexadecimal”,16))

Variables
 variable is a
◦ name.
◦ refers to a value.
◦ holds the data
◦ name of the memory location.
Note: To find the memory location of a variable we can
use below statement
>>>X=10
>>>print(id(x))

Properties of variable
 Every variable has a,
◦ Type
◦ Value
◦ Scope
◦ Location
◦ Life time
 Creating variable
◦ In python, to create a variable we need to
specify, The name of the variable
◦ Assign a value to name of the variable.

 Variables names,
Should not give as keywords
names, otherwise we will get error.
 We can assign multiple variables to
multiple values in single line.
 Example:
>>> a, b, c = 1, 2, 3
>>> print(a, b, c)
Output:
1 2 3

Data types
 A data type represents the type of the
data stored into a variable or memory
Note: We use type() in-built or predefined function in python.

Different types of data types
 There are two type of data types.
◦ Built-in data types:
 The data types which are already available in
python are called built-in data types.
◦ User defined data types:
 Data types which are created by programmer

Built-in data types
1. Numeric types
◦ int
◦ float
◦ complex
2. bool (boolean
type)
◦ True
◦ False
3. None
4. Str (string)
5. bytes
6. bytearray
7. list
8. set
9. tuple
10. dict
11. range

More to Discuss
 Exponential values in integers.
◦ 2E2 or 2e2
◦ Comparing complex numbers
◦ Case sensitivity in complex
values/numbers
◦ Adding Boolean values
◦ Printing none values
◦ How to create a string

Bytes
 bytes data type
◦ bytes data type represents group of numbers
just like an array
◦ bytes data type can store the values which
are from 0 to 256.
◦ bytes data type cannot store negative
numbers.
To create a byte data type
◦ First, we need to create list.
◦ The created list we need to pass to bytes()
function as a parameter
 Note: bytes data type is immutable means we cannot
modify or change the bytes object.

How to create a bytes
 To create a bytes first we need to create a list with [ ] a
variable name
 Then assign the created list to another variable by
stating it as byte as below
 Example:
>>>a= [1,2,3,4,5,]
>>>b= bytes(a)
>>>print(b)
>>>print(type(a))
 Output:
[1,2,3,4,5,]
<class 'bytes'>

bytearray data type
 bytearray is same as bytes data type,
but bytearray is mutable means we
can modify the content of bytearray
data type.
 The created list we need to pass as
bytearray() parameter

How to create a bytearray()
 First, we need to create list.
 The created list we need to pass as
bytearray() parameter
 It is as same as creating a bytes()
>>>x = [10, 20, 30, 40, 15]
>>>y = bytearray(x)
>>>print(type(y))
>>>print(y)
Output:
<class bytearray>
[10, 20, 30, 40, 15]

Modifying bytearray()
 We can modify the bytearray as it is a
mutable list as below
>>>x=[10,20,30,40,50]
>>>y=bytearray(x)
>>>print(y)
>>>y[3]=99
>>>print(y)
Output:
[10,20,30,40,50]
<class bytearray>

List
 We can create list data structure by
using square brackets [ ]
 list can store different data types
 list is mutable.
 Examples of list:
◦ [1,2,3,4,5]
◦ [1,2,’3x’,’x’,’y’,-2]
◦ [1,2,'3x','x','y',-2,{1,2,3,4}]

Python has a set of built-in
methods.
 append(): Adds an element at the end of the list
 clear(): Removes all the elements from the list
 copy(): Returns a copy of the list
 count(): Returns the number of elements with the
specified value
 extend(): Add the elements of a list (or any iterable),
to the end of the current list
 index(): Returns the index of the first element with
the specified value
 insert(): Adds an element at the specified position
 pop(): Removes the element at the specified
position
 remove(): Removes the item with the specified value
 reverse(): Reverses the order of the list
 sort(): Sorts the list

append()
>>>a=['apple','boy','cat']
>>>a. append('dog')
>>>print(a)
O/p: apple, boy cat,dog
clear()
>>>a.clear()
>>>print(a)
O/p: [ ]

Copy()
>>>b=a. copy()
>>>print(b)
O/p:
apple, boy, cat
Count():
>>>a=[1,2,3,3,3,3,3,3,5,6]
>>>b=a.count(3)
>>>print(b)
O/p:
6

Extend()
>>>b=['dog','egg']
>>>a.extend(b)
>>>print(a)
O/p:
['apple','boy','cat‘, 'dog','egg']
Index()
>>>b=a.index('boy')
>>>print(b)
O/p:
1

sort()
>>>cars = ['Ford', 'BMW', 'Volvo']
>>>cars.sort()
>>>print(cars)
O/p:
[‘BMW’, ‘Ford’,’Volvo’]
reverse()
>>>fruits = ['apple', 'banana', 'cherry']
>>>fruits.reverse()
>>>print(fruits)
O/p:
[‘cherry’, ‘banana’, ’apple’]

remove()
>>>fruits.remove("banana")
>>>print(fruits)
O/p:
[‘apple’,’cherry’]
Pop():
>>>fruits.pop(1)
>>>print(fruits)
O/p:
[‘apple’, ‘cherry’]

Insert():
fruits = ['apple', 'banana', 'cherry']
fruits.insert(1, "orange")
print(fruits)
O/p:
[‘apple’, ’orange’,’banana’,’cherry’]

tuple
 We can create tuple data structure by
using parenthesis ()
 tuple can store different data types.
 tuple is immutable.
 Examples of tuple:
 (1,2,3,4)

Examples of tuple
Creating a tuple
>>>a=(1,2,3,4,5)
>>>print(a)
>>>print(type(a))
O/p:
(1,2,3,4)
<class ‘tuple’>

Access Tuple Items
>>>a=("apple","boy","cat")
>>>print(a)
>>>print(a[1])
O/p:
Boy
Checking the presence of tuple
>>>a=("apple","boy","cat")
>>>if "apple" in a:
>>>print("yes apple is there in the given tuple")
O/p:
Yes apple is there in the given tuple

To print length of tuple
>>>a=(“apple”,”boy”,”dog”)
>>>print(len(a))
O/p:
3
Tuple as a constructor:
>>>a=tuple(("apple","boy","cat"))
>>>print(a)
>>>print(type(a))
O/p:
(“apple”,”boy”,”cat”)
<class “tuple”>

 Methods in tuples:
Count()
Index()
More to Discuss
1. Can we add elements into a tuple
2. Can we remove elements from the
tuple
3. Can we delete entire tuple

range()
 We can create a range of values by
using range() function
 The range datatype represents a
sequence of numbers.
 range data type is immutable, means
we cannot modify once it created.
 range data type values can be print by
using for loop.

Example of range()
>>>a=range(5)
>>>print(a)
>>>for x in a:
>>>print(x)
Output:
range(0, 5)
0
1
2
3
4

Note: We can create a list of values with range data
type
Program Creating list of values
>>>a=list(range(1, 10))
>>>print(a)
Output:
[1, 2, 3, 4, 5, 6, 7, 8, 9]

 By using index, we can access
elements present in the range data
type
>>>a=range(1, 10)
>>>print(a[0])
>>>print(a[1])
Output:
1
2

 A set is a collection which is unordered
and un-indexed. In Python sets are
written with curly brackets { }.
 You cannot access items in a set by
referring to an index, since sets are
unordered the items has no index.
 But you can loop through the set items
using a for loop, or ask if a specified
value is present in a set, by using the
“in” keyword.
 Once a set is created, you cannot
change its items, but you can add new
Set

Add Items
 To add one item to a set use the add() method.
 To add more than one item to a set use the update() method.
 Example:
>>>a={"apple","boy","cat"}
>>>print(type(a))
>>>a.add("dog")
>>>print(a)
>>>a.update(["nanna","flask"])
>>>print(a)
O/p:
<class,set”>
{‘apple’,’boy’,’cat’,’dog’}
{‘apple’,’boy’,’cat’,’dog’, ‘nanna’, ‘flask’}

 Printing a set:
>>>a={“apple”,”boy”,”cat”}
>>>print(a)
O/p:
Cat
Apple
Boy
To print the output in a sequence:
>>>for x in a
>>>print(a)
O/p:
apple
boy
cat

 To find the presence of an element:
>>>print(“boy” in a)
O/p:
True

 We can find the length of “set” by
using “len()”
 We can perform remove() & discard(),
both are same
>>>a.remove(“apple”)
>>>a.discard(“cat”)
>>>print(a)
O/p:
boy

 pop()
We can perform pop() also but as the
set() is unordered so it will delete the
last element of the set
>>>a={"apple","boy","cat","dog"}
>>>a.pop()
>>>print(a)
O/p:
Boy
Cat
dog

 We can also perform clear(), del() on the set
as below
>>>a.clear()
>>>print(a)
O/p:
{ }
Del():
>>>del a
>>>print(a)
O/p:
error

Methods in set{ }
 add(): Adds an element to the set
 clear(): Removes all the elements from the set
 copy(): Returns a copy of the set
 difference(): Returns a set containing the difference between two or more sets
 difference_update(): Removes the items in this set that are also included in
another, specified set
 discard(): Remove the specified item
 intersection(): Returns a set, that is the intersection of two other sets
 intersection_update():Removes the items in this set that are not present in other,
specified set(s)
 isdisjoint(): Returns whether two sets have a intersection or not
 issubset(): Returns whether another set contains this set or not
 issuperset(): Returns whether this set contains another set or not
 pop(): Removes an element from the set
 remove(): Removes the specified element
 symmetric_difference(): Returns a set with the symmetric differences of two sets
 symmetric_difference_update(): inserts the symmetric differences from this set
and another
 union(): Return a set containing the union of sets
 update(): Update the set with the union of this set and othersTest

Copy
>>>b=a.copy()
>>>print(b)
O/p:
{“apple”,”boy”,”cat”}
Difference
>>>b={“man”,”nest”,”apple”}
>>>z=a.difference(b)
O/p:
“man”,”nest”

Difference_update()
>>>b={“man”,”nest”,”apple”}
>>>a.difference_update(b)
O/p:
“man”,”nest”
Intersection()
>>>a={"apple", "boy","cat"}
>>>b={"man","nest","apple" }
>>>z=a.intersection(b)
>>>print(z)
O/p:
apple

Intersection_update():
>>>a.intersection_update(b)
>>>print(a)
O/p:
{“apple”}
isdisjoint()
>>>z=a.isdisjoint(b)
>>>print(z)
O/p:
False

issubset()
>>> a={‘a’,’b’,’c’,’d’,’e’,’f’}
>>> b={‘a’,’b’,’c’}
>>> d=b.issubset(a)
print(d)
O/p:
True
Issuperset():
>>>x = {"f", "e", "d", "c", "b", "a"}
>>> y = {"a", "b", "c"}
>>> z = x.issuperset(y)
>>> print(z)
O/p:
True

symmetric_difference():
>>>x = {"apple", "banana", "cherry"}
>>>y = {"google", "microsoft", "apple"}
>>>z = x.symmetric_difference(y)
>>>print(z)
O/p:
{"google", "microsoft",
“banana”,”cherry”}

Can also use the pop(), method to remove an item,
but this method will remove the last item.
Remember that sets are unordered, so you will not
know what item that gets removed.
 The return value of the pop() method is the
removed item.
Remove the last item by using the pop() method:
>>>a = {"apple", "banana", "cherry"}
>>>x = a.pop()
>>>print(x)
>>>print(a)
O/p:
{“apple”,”boy”}

symmetric_difference_update():
>>>x.symmetric_difference_update(y)
>>>print(x)
O/p:
{'google', 'cherry', 'microsoft', 'banana'}

union():
>>>z = x.union(y)
>>>print(z)
O/p:
{'banana', 'apple', 'google', 'microsoft', 'cherry'}
update():
x = {"apple", "banana", "cherry"}
y = {"google", "microsoft", "apple"}
x.update(y)
print(x)
O/p:
{'microsoft', 'cherry', 'apple', 'google', 'banana'}

Dictionary
 A dictionary is a collection which is
unordered, changeable and indexed. In
Python dictionaries are written with curly
brackets,{ } and they have keys and
values.
 Example:
>>>x={1:10}
>>>print(x)
>>>print(type(x))
O/p:
{1,10}
<class ‘dict’>

Can access the items of a dictionary by referring to its key
name, inside square brackets:
A={“animal”:”cat”, ”fruit”: “apple”, ”flower”:”Rose”}
print(type(a))
print(a[“flower”])
O/p:
<class “dict”>
Rose
Change Values:
A={“animal”:”cat”, ”fruit”: “apple”, ”flower”:”Rose”}
print(type(a))
print(a[“flower”])
A[“fruit”]=“Banana”
O/p:
<class “dict”>
{“animal”:”cat”, ”fruit”: “Banana”, ”flower”:”Rose”}

Print all key names in the dictionary, one by one:
>>>a={“animal”:”cat”, ”fruit”: “apple”, ”flower”:”Rose”}
>>>print(type(a))
>>>For x in a:
>>>print(x)
O/p:
<class “dict”>
animal
Fruit
flower
Printing all values in the dictionary, one by one:
>>>a={“animal”:”cat”, ”fruit”: “apple”, ”flower”:”Rose”}
>>>print(type(a))
>>>For x in a:
>>>print(a[x])
O/p:
Cat
Apple
Rose

We can also use the values() function to return values of a dictionary:
>>>a={"fruit": "apple", "animal": "cat","flower": "Rose"}
>>>print(a)
>>>for x in a.values():
>>> print(x)
O/p:
Apple
Cat
Rose
To print the complete “dict” we can also use below method:
>>>print(a)
>>>for x,y in a:
>>> print(x,y)
O/p:
{"fruit": "apple", "animal": "cat", "flower": "Rose"}
{"fruit": "apple", "animal": "cat", "flower": "Rose"}

We can also find the length of the dictionary:
>>>a={"fruit": "apple", "animal": "cat","flower":
"Rose"}
>>>print(a)
Print(len(a))
O/p:
3
To find the availability of elements in given dict:
>>>a={"fruit": "apple", "animal": "cat","flower":
"Rose"}
>>>if "animal" in a:
>>> print("Yes it is there")
O/p:
Yes it is there

Adding elements into given dict:
>>>print(a)
>>>a["color"]="Red"
>>>print(a)
O/p:
{“Color”: “Red, ”"fruit": "apple", "animal": "cat", "flower": "Rose“}
Deleting/Removing elements from dict:
>>>print(a)
>>>a["color"]="Red"
>>>print(a)
>>>a.pop("animal")
>>>print(a)
O/p:
{“Color”: “Red, ”"fruit": "apple", "animal": "cat", "flower": "Rose“}
{“Color”: “Red, ”"fruit": "apple", "flower": "Rose“}

Deleting an element from “dict” using del():
>>>print(a)
>>>del a[“flower”]
>>>print(a)
O/p:
{"fruit": "apple", "animal": "cat"}
To delete entire dict using del():
>>>print(a)
del a
print(a)
O/p:
Type Error

To copy a dict:
a={"fruit": "apple", "animal": "cat","flower": "Rose"}
print(a)
d=a.copy()
print(d)
O/p:
To clear a dict:
print(a)
a.clear()
print(a)
O/p:
{ }

Python has a set of built-in
methods that you can use on
dictionaries. clear(): Removes all the elements from the dictionary
 copy(): Returns a copy of the dictionary
 fromkeys(): Returns a dictionary with the specified keys and
values
 get(): Returns the value of the specified key
 items(): Returns a list containing the a tuple for each key
value pair
 keys(): Returns a list containing the dictionary's keys
 pop() Removes the element with the specified key
 popitem(): Removes the last inserted key-value pair
 setdefault(): Returns the value of the specified key. If the key
does not exist: insert the key, with the
specified value
 update(): Updates the dictionary with the specified key-
value pairs
 values(): Returns a list of all the values in the dictionary

fromkeys():
>>>x=('man','can','van')
>>>y=0
>>>a=dict.fromkeys(x,y)
>>>print(a)
O/p:
{man:0,can:0,van:0}
get():
x={“animal”: “Zebra”, ”Flower”:”Rose”,”Color”:
“Red”}
y=x.get(“color”)
Print(y)
O/p:
Red

items():
>>>x={'flower':"Rose",'color':"Red",'animal':"rat"
}
>>>y=x.items()
>>>print(y)
O/p:
[('color', 'Red'), ('flower', 'Rose'), ('animal', 'rat')]
keys():
car = { "brand": "Ford", "model": "Mustang",
"year": 1964}
x = car.keys()
print(x)
O/p:
dict_keys(['brand', 'model', 'year'])

pop():
>>>x={'flower':"Rose",'color':"Red",'animal':"rat"}
>>>print(x)
>>>x.pop("animal")
>>>print(x)
O/p:
{'flower':"Rose",'color':"Red"}
popitem():
Remove the last item from the dictionary:
>>>x={'flower':"Rose",'color':"Red",'animal':"rat"}
>>>print(x)
>>>x.popitem( )
>>>print(x)
O/p:
{'flower': 'Rose', 'animal': 'rat'}

>>>car = { "brand": "Ford","model":
"Mustang","year": 1964}
>>>x = car.setdefault("color", "White")
>>>print(x)
O/p:
White
Update():
>>>a={"animal":"cow","flower":"lilly","food":"idly
"}
>>>a.update({"name":"archi"})
>>>print(a)
O/p:
{"animal":"cow","flower":"lilly","food":"idly“,
"name":"archi"}

Membership Operators
 Membership operators are useful to check whether
the given object is available in collection
(sequence) or not. (It may be string, list, set, tuple
and dict)
 There are two membership operators,
◦ In
◦ not in
Example:
x=[1,2,3,4,5]
print(10 in x)
print(1 in x)
print(1 not in x)
print(100 not in x)

Keywords in python
 The words which are reserved to do
specific functionality is called
reserved keywords words.
 Totally we have 33 keywords in python
 These are also case sensitive
 All are small letters except
 True
 False
 None
 Note: We cannot use a keyword as variable name,
function name or any other identifier.

List of Keywords
 False
 class
 finally
 is
 return
 None
 continue
 for
 lambda
 try
 True
 def
 from
 nonlocal
 while
 and
 del
 global
 not
 with
 as
 elif
 for
 yield
 assert
 else
 import
 pass
 break
 except
 in
 raise

Keyword: None
 None is a special constant in Python that represents the
absence of a value or a null value.
 It is an object of its own data type, the None Type. We cannot
create multiple None objects but can assign it to variables.
These variables will be equal to one another.
 Example:
>>> x = None
>>> y = None
>>> x == y
Output:
True

Functions in Python:
 What is a function?
 What is the use of a function
 Types of Function

What is a function & use of a
function
 A function is a set of statements that
take inputs, do some specific
computation and produces output. The
idea is to put some commonly or
repeatedly done task together and
make a function, so that instead of
writing the same code again and again
for different inputs, we can call the
function.

Types of Function
 Python provides built-in functions like
print(), etc. but we can also create our
own functions. These functions are
called user-defined functions.
 That means python has two types of
functions
1.User defined
2. Built-in function

Syntax of Function:
 def function_name(parameters):
"""docstring"""
 statement(s)

 Example of a function:
>>>def greet(name):
"""This function greets to the person
passed in as parameter""“
>>>print("Hello, " + name + ". Good
morning!")
greet(“Deepak”)
O/p:
Hello Deepak Good morning

Parameters
 Parameters are specified after the function name, inside
the parentheses. We can add as many parameters as
you want, just separate them with a comma.
Ex:
>>>def classing(num):
>>>print(num+ " " "one")
>>>classing("one")
>>>classing("two")
>>>classing("three")
O/p:
One one
two one
three one

Default Parameter Value:
 If we call the function without parameter, it uses the
default value:
>>>def apple(country="India"):
>>>print("I am from" " " +country)
>>>apple("Japan")
>>>apple("Nepal")
>>>apple()
>>>apple("Bhutan")
O/p:
I am from Japan
I am from Nepal
I am from India
I am from Bhutan

Passing a List as a Parameter:
 We can send any data types of parameter to a function
(string, number, list, dictionary etc.), and it will be
treated as the same data type inside the function.
>>>def my_number(number):
>>>for x in number:
>>>print(x)
>>>integers=[1,2,3,4,5]
>>>my_number(integers)
O/p:
1
2
3
4
5

Return Value:
 To let a function return a value, use the return statement
 Example:
def multiplication(number):
return 10*number
print(multiplication(1))
O/p:
10
20
30
40

Recursion:
 Python also accepts function recursion, which
means a defined function can call itself.
 Recursion is a common mathematical and
programming concept. It means that a
function calls itself. This has the benefit of
meaning that you can loop through data to
reach a result.
 The developer should be very careful with
recursion as it can be quite easy to slip into
writing a function which never terminates, or
one that uses excess amounts of memory or
processor power. However, when written
correctly recursion can be a very efficient and
mathematically-elegant approach to
programming.

Agenda:
 Conditions.
 Loops
 Oops
 Examples

Conditions in Python
 If condition
 If else condition
 If elif else condition
 Nested condition

If condition:
 We use “If condition” to check either a
condition is true or False. To move to
the next statement if the give condition
is satisfied .
 Syntax:
if expression:
Statement
else:
Statement

 Example:1
def fun():
X=10
Y=20
If x<y:
Print(“y is greater”)
O/p:
Y is greater
Example:2
Def fun():
X=30
Y=20
If x<y:
Print(y is greater)
O/p:
??????

If else:
Example:1
def fun():
X=10
Y=20
If x<y:
Else:
Print(“x is greater”)
Fun()
O/p:
y is greater
Example:2
def fun():
X=20
Y=20
if x<y:
Print(“ x is greater”)
Else x>y:
O/p:
????

If else elif:
def fun():
X=20
Y=20
if x<y:
Print(“ y is greater”)
elif x>y:
Print(“x is greater”)
Else:
Print(“both are equal”)
Fun()
O/p:
Both are equal

If else if:
 def fun(name):
 name=input("please enter your name: ")
 if name=="Deepak":
 print("Hai deepak How are you doing")
 elif name=="John":
 print("Hai John How are you doing")
 elif name=="Bob":
 print("Hai Bob How are you doing")
 elif name=="Cat":
 print("Hai Cat How are you doing")
 else:
 print("Hai" +name+ "How are you
doing")
 fun("name")

Nested if:
 There may be a situation when we
want to check for another condition
after a condition resolves to true. In
such a situation, we can use the
nested ifconstruct.
 In a nested if construct,we can have
an if...elif...else construct inside
another if...elif...else construct.

Syntax:
 if expression1:
statement(s)
if expression2:
statement(s)
elif expression3:
statement(s)
elif expression4:
statement(s)
else:
statement(s)
else:
statement(s)

Example:
age= int(input("please enter your age: "))
if age >= 18:
weight=int(input("what is your weight: "))
if weight==150:
print("over weight")
elif weight== 120:
print("little less than over weight")
elif weight==100:
print("noraml weight")
elif weight==50:
print("less weight")
else:
print(“sorry please enter age more than or equal to 18")
O/p:
????

For loop in python:
 A for loop is used for repeating over a
sequence in any of the a list, a tuple, a
dictionary, a set, or a string.
 This is less like the for keyword in
other programming languages, and
works more like an iterator method as
found in other object-orientated
programming languages.
 With the for loop we can execute a
set of statements, once for each item
in a list, tuple, set etc.

Example:1
X=range(6)
For a in x:
Print(a)
O/p:
0
1
2
3
4
5
Example:2
x=["apple","boy","cat","do
g"]
for a in x:
print(a)
O/p:
Apple
Boy
Cat
dog

Example: 1
a="banana"
for x in a:
print(x)
O/p:
???
The break Statement
 With the break statement we can stop the loop before it has looped
through all the items
Example:2
fruits = ["apple", "banana", "cherry"]
for x in fruits:
print(x)
if x == "banana":
break
O/p:
Apple
Banana

 Exit the loop when x is "banana", but
this time the break comes before the
print
for x in fruits:
if x == "banana":
break
print(x)
O/p:
Apple
Banana

Example:
x=["apple","boy","cat","dog"]
for a in x:
print(a)
if a=="cat":
break
 O/p:
apple
boy
cat

Continue statement:
 With the continue statement we can stop
the current iteration of the loop, and
continue with the next
Example:
for x in fruits:
if x == "banana":
continue
print(x)
O/p:
Apple
cherry

While in python:
 A while loop statement in Python
programming language repeatedly
executes a target statement as long
as a given condition is true.
Syntax:
while expression:
statement(s)

 Example:
num=0
while num<=9:
print("number is:
",+num)
num=num+1
print("end of loop")
O/p:
('number is: ', 0)
end of loop
('number is: ', 1)
end of loop
('number is: ', 2)
end of loop
('number is: ', 3)
end of loop
('number is: ', 4)
end of loop
('number is: ', 5)
end of loop
('number is: ', 6)
end of loop
('number is: ', 7)
end of loop
('number is: ', 8)
end of loop
('number is: ', 9)
end of loop

What is OOPS in python:
 Object Oriented programming is a programming
style that is associated with the concept of Class,
Objects and various other concepts revolving
around these two, like Inheritance,
Polymorphism, Abstraction, Encapsulation etc.
 OOP is designed in such a way that one should
focus on an object while programming and not
the procedure. An object can be anything that we
see around us. It can be a human (that has some
properties like - name, address, DOB and so on),
a chair (portrayed by size, material, cost etc), a
school (depicted by place, student strength,
results) etc.
 Object oriented programming brings
programming close to real life, as we are always
dealing with an object, performing operations on
it, using it's methods and variables etc.

Concepts of OOP in python:
 Class
 Object
 Inheritance
 Encapsulation
 Abstraction
 Polymorphism

Class:
A Class is a logical grouping of data and
functions. It gives the freedom to
create data structures that contains
arbitrary content and hence easily
accessible.
Object:
A unique instance of a data structure
that's defined by its class. An object
comprises both data members (class
variables and instance variables) and
methods.

Inheritance:
The transfer of the characteristics of a
class to other classes that are derived
from it.
Polymorphism:
The word polymorphism means having
many forms. In programming,
polymorphism means same function
name (but different signatures) being
uses for different types.

 Encapsulation:
Encapsulation is defined as wrapping up
of data and information under a single
unit. In Object Oriented Programming,
Encapsulation is defined as binding
together the data and the functions that
manipulates them.
Abstraction:
Abstraction means displaying only
essential information and hiding the
details. Data abstraction refers to
providing only essential information
about the data to the outside world,
hiding the background details or
implementation.

Class:
Syntax of a class: 1
Class class_name():
statements
Printing the class
Example:
Class Myclass():
a=10
Print(Myclass)
O/p:
10

Syntax of a class:2
class MyClass:
variable1 = something
variable2 = something
def function1(self, parameter1, ...):
self.variable1 = something else
self.variable3 = something function
statements...
def function2(self, parameter1, ...):
self.variable2 = something else
function2 statements...
Note: It's a mandatory parameter for every function
defined in a class. self represents the current active
object of the class, using which the function of the class
is called.

 Inheritance in Python
If we have a class Parent and another class Child and we want the class Child to
inherit the class Parent, then:
Example:
# Parent class
class Parent:
# class variable
a = 10;
b = 100;
# some class methods
def doThis():
Statements
def doThat():
statements
# Child class inheriting Parent class
class Child(Parent):
# child class variable
x = 1000;
y = -1;
# some child class method
def doWhat():
statements
def doNotDoThat():
statements

 Creating an Object:
class MyClass:
x = 5
p1 = MyClass()
print(p1.x)
Here pl is an object

 Identity: Identity refers to some piece of
information that can be used to identify
the object of a class. It can be the name
of the student, the company name of the
car, etc.
 Properties: The attributes of that object
are called properties. Like age, gender,
DOB for a student; or type of engine,
number of gears for a car.
 Behavior: Behavior of any object is
equivalent to the functions that it can
perform. In OOP it is possible to assign
some functions to objects of a class.
Taking the example forward, like a
student can read/write, the car can

 Sample code for creating class & Object:
class Apollo:
# define a variable
destination = "moon"
# defining the member functions
def fly(self):
print ("Spaceship flying...“)
def get_destination(self):
print ("Destination is: " + self.destination)
# 1st object
objFirst = Apollo()
# 2nd object
objSecond = Apollo()
# lets change the destination for objFirst to mars
objFirst.destination = "mars"
# objFirst calling fly function
objFirst.fly()
# objFirst calling get_destination function
objFirst.get_destination()
# objSecond calling fly function
objSecond.fly()
# objSecond calling get_destination function
objSecond.get_destination()

Polymorphism
 Polymorphism, or Poly + Morph,
means "many forms. Precisely,
Polymorphism is the property of any
function or operator that can behave
differently depending upon the input
that they are fed with.
 Polymorphism can be achieved in tow
different forms, they are:
:Over riding & Over loading

 Overloading:
For example, consider a function add(), which
adds all its parameters and returns the result.
In python we will define it as,
Example:
def add(a, b):
print("addition of two numbers is: ", a+b)
add(3,4)
def add(a, b, c):
print("addition of three numbers is: ",
a+b+c)
add(3,4,5)
# to add 4 numbers
def add(a, b, c, d):
print("addition of four numbers is: ",
a+b+c+d)
add(3,4,5,6)

 Method Overriding:
 Python method overriding occurs
simply defining in the child class a
method with the same name of a
method in the parent class. When you
define a method in the object you
make the latter able to satisfy that
method call, so the implementations of
its ancestors do not come in play.

class Parent(object):
def __init__(self):
self.value = 5
def get_value(self):
return self.value
class Child(Parent):
def get_value(self):
return self.value + 1

Polymorphism:
Sample code:
def add(x, y, z = 0):
return x + y+z
print(add(2, 3))
print(add(2, 3, 4))
O/p:
5
9

 Example of polymorphism:
class India():
def capital(self):
print("New Delhi is the capital of India.")
def language(self):
print("Hindi the primary language of India.")
def type(self):
print("India is a developing country.")
class USA():
def capital(self):
print("Washington, D.C. is the capital of USA.")
def language(self):
print("English is the primary language of USA.")
def type(self):
print("USA is a developed country.")
Object_ind = India()
Object_usa = USA()
for country in (object_ind, object_usa):
country.capital()
country.language()
country.type()

Example of Inheritance
class Person(object):
def __init__(self, name):
self.name = name
def getName(self):
return self.name
def isEmployee(self):
return False
class Employee(Person):
def isEmployee(self):
return True
emp = Person("Geek1") print(emp.getName(),
emp.isEmployee())
emp = Employee("Geek2") # An Object of Employee
print(emp.getName(), emp.isEmployee())

Some Examples on Data visualization
using Pandas, Numpy &
matplotlib.pyplot

 NumPy: (Numerical Python)
It is a core library for scientific
computing
in python, It provides a higher
performance multidimensional array
object & tools for working with these
arrrays.
Pandas:
Pandas takes data from .csv, .tsv or
SQL database files & creates a python
object with rows and columns called
data frames that looks very similar to
table in a statistical Software

matplotlib.pyplot:
Matplotlib.pyplot is a library used to
create 2D graphs & plots by using
python scripts. It has a module named
pyplot which makes things easy for
plotting by providing feature to control
line styles font properties formatting
axes etc.,

import numpy
x=numpy.array([5,4,3,4])
y=numpy.array([1,2,3,4])
z=x-y
print(z)
O/p:
4,2,0,0

import pandas
import numpy
import matplotlib.pyplot as dee
myarray=numpy.array([[1,2,3,4,5],[6,7,8,9,
0]])
rowname=["a","b"]
columnname=["m","n","o","p","q"]
x=pandas.DataFrame(myarray,
index=rowname, columns=columnname)
print(x)
O/p:
m n o p q
a 1 2 3 4 5
b 6 7 8 9 0

Python for plotting graphs:
 Example:
import pandas
import numpy
x=numpy.array([1,2,3,4,5])
y=numpy.array([3,4,5,6,7])
dee.scatter(x,y)
dee.xlabel(“x-axis”)
dee.ylabel(“y-axis”)
dee.show()
O/p:

Plotting graphs:
import pandas
import numpy
url="https://archive.ics.uci.edu/ml/machi
ne-learning-databases/iris/iris.data"
name=['sl','sw','pl','pw','class']
data=pandas.read_csv(url,
names=name)
data.plot(kind='box', subplots=True,
layout=(1,4))
dee.show()

Reading a CSV file:
url="https://archive.ics.uci.edu/ml/machine
-learning-databases/iris/iris.data"
name=['sl','sw','pl','pw','class']
data=pandas.read_csv(url, names=name)
print(data

import pandas
from sklearn import model_selection
from sklearn.linear_model import LinearRegression
url =
"https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.data"
names = ['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX',
'PTRATIO', 'B', 'LSTAT', 'MEDV']
dataframe = pandas.read_csv(url, delim_whitespace=True, names=names)
array = dataframe.values
X = array[:,0:13]
Y = array[:,13]
seed = 7
kfold = model_selection.KFold(n_splits=10, random_state=seed)
model = LinearRegression()
scoring = 'neg_mean_squared_error'
results = model_selection.cross_val_score(model, X, Y, cv=kfold,
scoring=scoring)
print(results.mean())

Python introduction towards data science

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