Python Training

1 : Python Basics

• Why Python?
• History of python
• Applications of Python
• Features of Python
• Advantages of Python
• Versions of Python
• Installation of Python
• Flavors of Python
• Comparision b/w various programming languages C, Java and Python

2 : Python Operations

• Python Modes of Execution
• Interactive mode of Execution
• Batch mode of Execution
• Python Editors and IDEs
• Python Data Types
• Python Constants
• Python Variables
• Comments in python
• Output Print(),function
• Input() Function :Accepting input
• Type Conversion
• Type(),Id() Functions
• Comments in Python
• Escape Sequences in Python
• Strings in Python
• String indices and slicing
•  

3: Operators in python
• Arithmetic Operators
• Comparision Operators
• Logical Operators
• Assignment Operators
• Short Hand Assignment Operators
• Bitwise Operators
• Membership Operators
• Identity Operators

4: Python IDE’s

• Pycharm IDE Installation
• Working with Pycharm
• Pycharm components
• Installing Anaconda
• What is Conda?
• Anaconda Prompt
• Anaconda Navigator
• Jupyter Notebook
• Jupyter Features
• Spyder IDE
• Spyder Featueres
• Conda and PIP

5: Flow Control statements

• Block/clause
• Indentation in Python
• Conditional Statements
• if stmt
• ;if…else statement
• if…elif…statement

6: Looping Statements

• while loop,
• while … else,
• for loop
• Range() in for loop
• Nested for loop
• Break statememt
• Continue statement
• Pass statement

7: Strings in Python

• Creating Strings
• String indexing
• String slicing
• String Concatenation
• String Comparision
• String splitting and joining
• Finding Sub Strings
• String Case Change
• Split strings
• String methods

8: Collections in Python

• Introduction
• Lists
• Tuples
• Sets
• Dictionaries
• Operations on collections
• Functions for collections
• Methods of collection
• Nested collections
• Differences b/w list tuple and set and Dictionary

9: Python Lists

• List properties
• List Creation
• List indexing and slicing
• List Operations
• Nested Lists
• List modification
• List insertion and deletion
• List Methods

10: Python Tuples

• Tuple properties
• Tuple Creation
• Tuple indexing and slicing
• Tuple Operations
• Nested Tuples
• Tuple Methods
• Differences b/w List and Tuple

11: Python Sets

• Set properties
• Set Creation
• Set Operations
• Set Mathematical Operations
• Set Methods
• Insertion and Deletion operation

12: Python Dictionary

Dictionary properties

Dictionary Creation

Dictionary Operations

Dictionary Methods

Insertion and Deletion of elements

Differences b/w list tuple and set and Dictionary

13. Functions in Python

• Defining a function
• Calling a function
• Properties of Function
• Examples of Functions
• Categories of Functions
• Argument types
• default arguments
• non-default arguments
• keyword arguments
• non keyword arguments
• Variable Length Arguments
• Variables scope
• Call by value and Call by Reference
• Passing collections to function
• Local and Global variables
• Recursive Function
• Boolean Function
• Passing functions to function
• Anonymous or Lamda function
• Filter() and map() functions

14: Modules in Python

• What is a module?
• Different types of module
• Creating user defined module
• Setting path
• The import statement
• Normal Import
• From … Import
• Module Aliases
• Dir function
• Working with Standard modules -Math, Random, Date time and os modules

15: Packages

• Introduction to packages
• Defining packages
• Importing from packages
• –init–.py file
• Defining sub packages
• Importing from sub packages

16: Errors and Exception Handling

• Types of errors
• Compile-Time Errors
• Run-Time Errors
• What is Exception?
• Need of Exception handling
• Predefined Exceptions
• Try,Except, finally blocks
• Nested blocks
• Handling Multiple Exceptions
• User defined Exceptions
• Raise statement

17: File Handling

• Introduction
• Types of Files in Python
• Opening a file
• Closing a file
• Writing data to files
• Tell( ) and seek( ) methods
• Reading a data from files
• Appending data to files
• With open stmt
• Various functions

18: OOPs concepts

• OOPS Features
• Encapsulation
• Abstraction
• Class
• Object
• Static and non static variables
• Defining methods
• Diff b/w functions & methods
• Constructors
• Parameterized Constructors
• Built –in attributes
• Object Reference count
• Destructor
• Garbage Collection
• Inheritance
• Types of Inheritances
• Polymorphism
• Over riding
• Super() statement

19: Regular Expressions

• What is regular expression? Special characters
• Forming regular expression
• Compiling regular expressions
• Grouping
• Match() function
• Search() function
• Matching vs searching
• Splitting a string
• Replacing text
• validations

20: Database Access

• Introduction
• Installing Oracle database
• Creating database users,
• Installing Oracle Python modules
• Establishing connection with oracle
• Closing database connections
• Cursor object
• Executing SQL queries
• Retrieving data from Database.
• Using bind variables executing SQL queries
• Transaction Management
• Handling errors

21: Python Date and Time

• How to Use Date & DateTime Class
• Time and date Objects
• Calendar in Python
• The Time Module
• Python Calendar Module

22: Operating System Module

• Introduction
• getcwd
• listdir
• chdir
• mkdir
• rename file/dir
• remove file/dir
• Os help
• Os operations
• 23: Advanced concepts
• Python Iterator
• Python Generator
• Python closure
• Python Decorators
• Web Scraping
• PIP
• Working with CSV files
• Working with XML files
• Working with JSON files
• Debugging

24: GUI Programming

• Introduction
• Components and events
• Root window
• Fonts and colors
• Buttons ,checkbox
• Label widget
• Message widget
• Text widget
• image

25: Data analytics

• Introduction
• pandas module
• Numpy module
• Matplotlib module
• Working Examples

26: Excel workbook

• Installing and working with Xlsx writer
• Creating Excel Work book
• Inserting into excel sheet
• Insetting data into multiple excel sheets
• Creating headers
• Installing and working with xlrd module
• Reading a specific cell or row or column
• Reading specific rows and columns

I) INTRODUCTION
What is Django?
• Why Django? Key Advantages
• History of Django
• Features of Django
• Characteristics of Django
• Companies Using Django
• Difference b/w MVC and MVT
• Models Views and Templates

II) WEB FRAMEWORKS
What is a Web Framework?
• What is a server?
• HTTP Requests and HTTP Responses
• What is a web framework ?
• What is a web application?
• Steps in Developing web application.

III) DJANGO INSTALLATION
• Django Architecture
• Django Installation
• Virtual Environment
• Working with Pycharm
• Working with ATOM
• Developing First Django Application

IV) DJANGO PROJECT ARCHITECTURE
Exploring manage.py,
• Exploring urls.py
• Exploring settings.py,
• Exploring admin.py,
• Exploring models.py,
• Exploring views.py,
• Application creations and Examples

V) DJANGO APPLICATION CREATION
steps in Application creation
• Working with views
• Working with HTML and CSS
• Working with Bootstrap
• Django Application creation in Atom
• Django Application creation in Pycharm
• project with multiple Applications
• Reusing a Application in different projects
• working with staticfiles

VI) DJANGO VIEWS
Requesting a web page via URL
• Rendering web page via view function
• Render HttpResponse to templates
• Application with multiple views
• Understanding context object and dictionary type
• GET and POST methods

VII) DJANGO TEMPLATES
• Template tags
• Template Filters
• Template API
• Passing Dynamic content to template file
• Passing multiple dict values to template
• Loading static files
• Adding image file to template
• Advanced Templates
• Template library
• custom template filter
• custom templates tags
• Registering the tags

VIII) DJANGO ADMIN
• Activating the Admin interface
• Creating super user for Admin site
• Using the Admin site
• How to use the Admin site

IX) DJANGO MODELS
working with models and databases
• Defining Models
• Model Fields
• Defining forms
• ModelForms
• makemigrations and migrate
• Registering models in settings.py
• Registering models with Admin site
• Connecting with sqlite3
• Connecting with MySQL
• Connecting with Oracle

X) ADVANCED CONCEPTS
Django ORM
• Faker Module
• Class based views
• Form validation
• Rendering forms
• crispy forms
• MultiselectField
• Embeded Video
• Uploading and downloading Files
• Working with Audio and video
• Integrating with legacy databases and applications
• Sessions users Registrations
• Security
• Django Deployment
• Other Contributed Frameworks

Introduction to Datascience

• Machine Learning Introduction
• Datasets
• Supervised /Unsupervised Learning
• Statistical Analysis
• Data Analysis
• Uni-variate/multi-variate analysis
• Corelation Analysis
• Algorithm types
• Applications

Python Matplotlib

• Introduction to matplolib
• Installing matplotlib
• Generating graphs
• Generating Bargraphs
• Histograms
• Scatter plots
• Stack plots
• Pie plots

PANDAS
Pandas – Introduction
Pandas – Environment Setup

• Series
• DataFrame
• Data Type of Columns
• Panel

Pandas — Series

• Series
• Create an Empty Series
• Create a Series f
• from ndarray
• from dict
• Accessing Data from Series with Position
• Retrieve Data Using Label (Index)

Pandas – DataFrame

• DataFrame
• Create DataFrame
• Create an Empty DataFrame
• Create a DataFrame from Lists
• Create a DataFrame from Dict of ndarrays / Lists
• Create a DataFrame from List of Dicts
• Create a DataFrame from Dict of Series
• Column Selection
• Column Addition
• Column Deletion
• Row Selection, Addition, and Deletion
• Pandas – Panel

Panel()

• Create Panel
• Selecting the Data from Panel
  Pandas – Working with Text Data
  Pandas – Indexing and Selecting Data
• loc()
• .iloc()
• Use of Notations

Pandas – Aggregations

• Applying Aggregations on DataFrame

Pandas – Missing Data

• Cleaning / Filling Missing Data
• Replace NaN with a Scalar Value
• Fill NA Forward and Backward
• Drop Missing Values

Replace Missing (or) Generic Values

• Pandas – GroupBy
• Split Data into Groups
• View Groups
• Iterating through Groups
• Select a Group
• Aggregations
• Transformations
• Filtration

Pandas – Merging/Joining

• Merge Using ‘how’ Arguments
• Pandas– Concatenation
• Concatenating Objects
• Pandas – Merging/Joining
  • Merge Using ‘how’ Arguments
  • Pandas– Concatenation

Pandas – Concatenation

• Concatenating Objects
• Time Series

Pandas – Date Functionality

Pandas – Timedelta

Pandas – Categorical Data

• Object Creation

Pandas – Visualization

• Bar Plot
• Histograms
• Box Plots
• Area Plot
• Scatter Plot
• Pie Chart

Pandas – IO Tools

• csv

Pandas – Comparison with SQL

NUMPY − INTRODUCTION

NUMPY − ENVIRONMENT

NUMPY − NDARRAY OBJECT

NUMPY − DATA TYPES

• Data Type Objects (dtype)

NUMPY − ARRAY ATTRIBUTES

• shape
• ndim
• itemsize
• flags

NUMPY − ARRAY CREATION ROUTINES

• empty
• zeros

NUMPY − ARRAY FROM EXISTING DATA

NUMPY − ARRAY FROM NUMERICAL RANGES

• arange
• linspace

NUMPY − INDEXING & SLICING

NUMPY − ADVANCED INDEXING

• Integer Indexing
• Boolean Array Indexing

NUMPY − ITERATING OVER ARRAY

• Iteration
• Order
• Modifying Array Values
• External Loop

NUMPY – ARRAY MANIPULATION

• reshape
• ndarray.flat
• ndarray.flatten
• ravel
• transpose
• ndarray.T
• swapaxes
• rollaxis
• broadcast
• broadcast_to
• expand_dims
• squeeze
• concatenate
• stack
• hstack and numpy.vstack
• split
• hsplit and numpy.vsplit
• resize
• append
• insert
• delete unique

NUMPY – BINARY OPERATORS

• bitwise_and
• bitwise_or
• invert()
• left_shift
• right_shift

NUMPY − STRING FUNCTIONS

NUMPY − MATHEMATICAL FUNCTIONS

• Trigonometric Functions
• Functions for Rounding

NUMPY − ARITHMETIC OPERATIONS

• reciprocal()
• power()
• mod()

NUMPY − STATISTICAL FUNCTIONS

• amin() and numpy.amax()
• ptp()
• percentile()
• median()
• mean()
• average()
• Standard Deviation
• Variance

NUMPY − SORT, SEARCH & COUNTING FUNCTIONS

• sort()
• argsort()
• lexsort()
• argmax() and numpy.argmin()
• nonzero()
• where()
• extract()

NUMPY − BYTE SWAPPING

• ndarray.byteswap()

NUMPY − COPIES & VIEWS