Python Made Easy: Step by Step Guide to Programming and Data Analysis using Python for Beginners and Intermediate Level

Length: 436 pages
Edition: 1
Language: English
Publisher: Notion Press
Publication Date: 2020-10-07
ISBN-10: 1649837259
ISBN-13: 9781649837257
Sales Rank: #0 (See Top 100 Books)

Python Made Easy: Beginners Guide to Programming and Data Analysis using Python

Get comprehensive learning of Python Programming starting from the very basics and going up to utilizing python libraries for data analysis and Visualization. It provides an ideal and elegant way to start learning Python, both for a newcomer to the programming world and a professional developer expert in other languages.

This book comes loaded with illustrations and real-life examples. It gives you exercises which challenge you to refresh your conceptual clarity and write better codes. It is super easy to follow and will work as a self-paced tutorial to get you started with the latest and best in Python. All the advanced Python features to date are included.

1. Get to know the history, present, and future of Data Science

2. Get introduced to the basics of Computer Programming

3. Explore the exciting world of Python using Anaconda

4. Learn how to install and use Python on your computer

5. Create your Variables, Objects and learn Syntax of operations

6. Explore Python’s built-in object types like Lists, dictionaries, Tuples, Strings and sets

7. Learn to make your codes reusable by using functions

8. Organize your codes, functions and other objects into larger components with Modules

9. Explore Classes – the Object-Oriented Programming tool for elegant codes

10. Write complex codes and learn how to handle Errors and Exceptions

11. Learn about NumPy arrays and operations on them

12. Explore data analysis using pandas on a real-life data set

13. Dive into the exciting world of Visualization with 3 chapters on 14. Visualization and Matplotlib

15. Experience the Power of What you learnt by 3 projects

16. Learn to make your own application complete with GUI by using API

Title
Copyright
Dedication
What to Expect from This Book
Foreword
Acknowledgement
1. Introduction to Data Science and Programming Basics
    1.1 Introduction to Data Science
        1.1.1 Why Data Science?
        1.1.2 Components of Data Science
        1.1.3 History of Data Science
        1.1.4 Ancient History of Data
        1.1.5 Modern History of Data
        1.1.6 Present and Future of Data Science
        1.1.7 What does a Data Scientist do?
        1.1.8 How does he do it?
        1.1.9 Prerequisites for Data Science
        1.1.10 Data Science Jobs Roles
    1.2 Summary of Data Science Introduction
    1.3 Basics of Computer Programming
        1.3.1 What is Programming?
        1.3.2 Computer Algorithm
        1.3.3 Flowchart
        1.3.4 What is a programming language?
        1.3.5 What is Source Code?
        1.3.6 How to Run the Source Code?
        1.3.7 Compiler
        1.3.8 Interpreter
        1.3.9 What is IDE (Integrated Development Environment)
    1.4 Summary:
    1.5 Exercise:
        1.5.1 Answer the following:
        1.5.2 True or False:
        1.5.3 Write your own Codes for this:
        1.5.4 Things to do:
2. Introduction to Python
    2.1 What is Python?
        2.1.1 Why Python?
        2.1.2 Python Origin
        2.1.3 Python vs Other Programming Languages
        2.1.4 Philosophy of Python
    2.2 Advantage of Python over other languages
        2.2.1 Simple
        2.2.2 Easy to learn
        2.2.3 Free and Open Source
        2.2.4 High-Level Language
        2.2.5 Portable
        2.2.6 Interpreted
        2.2.7 Python Interpreter
        2.2.8 Object-Oriented
        2.2.9 Extensible
        2.2.10 Embeddable
        2.2.11 Extensive Libraries
        2.2.12 Python for Beginners!
    2.3 Python Version
        2.3.1 Python 2
        2.3.2 Python 2.7
        2.3.3 Python 3
        2.3.4 Key Differences
    2.4 How to Install and use Python
        2.4.1 Anaconda Python Distribution
        2.4.2 Why Anaconda?
        2.4.3 Installing Anaconda on Windows
        2.4.4 Installing Anaconda on macOS
    2.5 Running Python on Terminal
    2.6 Introduction to Anaconda Apps
    2.7 IPyhton Qt Console
    2.8 Spyder (Scientific Python Development Environment)
        2.8.1 Components
    2.9 Jupyter Notebook
        2.9.1 Introduction
        2.9.2 Main features of the web application
        2.9.3 Notebook documents
        2.9.4 Starting the notebook server
        2.9.5 Creating a new notebook document
        2.9.6 Opening notebooks
        2.9.7 Notebook user interface
        2.9.8 Structure of a notebook document
        2.9.9 Code cells
        2.9.10 Markdown cells
        2.9.11 Raw cells
        2.9.12 Basic workflow
        2.9.13 Keyboard shortcuts
        2.9.14 Plotting
        2.9.15 Browser Compatibility
    2.10 What to use?
    2.11 Summary:
    2.12 Exercise:
        2.12.1 Answer the following:
        2.12.2 True or False:
3. Python Basics
    3.1 Running Python
        3.1.1 Using Spyder IDE
        3.1.2 Using Jupyter Notebook
    3.2 Starting with Hello world!
    3.3 Using Python as a Calculator
        3.3.1 Numbers
        3.3.2 Strings
    3.4 Syntax of Code in Python
        3.4.1 Statement
        3.4.2 Variables and Assignment
        3.4.3 Variable names and keywords
        3.4.4 Expressions
    3.5 First Steps towards Programming
        3.5.1 More about Print()
        3.5.2 A Cool way to print output
        3.5.3 Basic shape by Mighty print()
    3.6 Troubleshooting
        3.6.1 Syntax Errors
        3.6.2 Runtime Errors
        3.6.3 Semantic Errors
        3.6.4 When all else fails...
    3.7 Summary
    3.8 Exercise:
        3.8.1 Answer the following:
        3.8.2 True or False:
        3.8.3 Write your own Codes for this:
        3.8.4 Things to do:
4. Objects and Operators in Python
    4.1 Variables
        4.1.1 Assigning a variable
        4.1.2 Naming a Variable
    4.2 Conceptual Hierarchy
    4.3 Objects
        4.3.1 Classification of Objects
        4.3.2 Advantages of Built-in Objects
        4.3.3 Object's Identity, values, and types
        4.3.4 Mutable and Immutable Objects
    4.4 The standard type hierarchy
    4.5 Operations on objects in python
    4.6 Operators
        4.6.1 Arithmetic Operators
        4.6.2 Assignment Operators
        4.6.3 Comparison Operators
        4.6.4 Logical Operators
        4.6.5 Conditional Operator
    4.7 Indentation
    4.8 Python Comments
    4.9 Order of Evaluation in Python
        4.9.1 Changing the Order of Evaluation
        4.9.2 Associativity
        4.9.3 Area of Rectangle
    4.10 Dynamic Typing
    4.11 Strong Typing
    4.12 Branching
    4.13 Logical and Physical Line
    4.14 Summary
    4.15 Exercise:
        4.15.1 Answer the following:
        4.15.2 True or False:
        4.15.3 Write your own Codes for this:
        4.15.4 Things to do:
5. Control Flow Statements
    5.1 Control Flow Tools
    5.2 if Statements
        5.2.1 if Statement
        5.2.2 if – else Statement
        5.2.3 if – elif – else Statement
    5.3 for Statements (for loop)
        5.3.1 for loop with else
    5.4 The range() Function
    5.5 While Loop
    5.6 break and continue Statements
        5.6.1 break Statement
        5.6.2 Continue statement
    5.7 pass Statements
    5.8 Summary
    5.9 Exercise:
        5.9.1 Answer the following:
        5.9.2 True or False:
        5.9.3 Write your own Codes for this:
6. Functions
    6.1 Defining Functions
    6.2 Types of Function
    6.3 Built-in Functions
        6.3.1 Some Built-in function Definitions
    6.4 User-defined functions
        6.4.1 Why Create Functions?
        6.4.2 Creating and Calling a function
        6.4.3 Setting Parameters and arguments
        6.4.4 Return from a function
    6.5 More on Defining Functions
        6.5.1 Default Parameter Values (or default Argument values)
        6.5.2 Arbitrary Arguments (*args)
        6.5.3 Keyword Arguments
        6.5.4 Arbitrary Keyword Arguments (**kwargs)
    6.6 Generator
        6.6.1 How to define a Generator?
        6.6.2 Example code explained
    6.7 Summary:
    6.8 Exercise:
        6.8.1 Answer the following:
        6.8.2 True or False:
        6.8.3 Write your own Codes for this:
        6.8.4 Things to do:
7. Project 1: Patterns Using Loops and Functions
    7.1 Patterns using * (Asterisk)
        7.1.1 L Pattern of * (Also looks like Right angle triangle)
        7.1.2 Inverted L Pattern of *
        7.1.3 Pyramid pattern with * (Also Equilateral Triangle)
        7.1.4 Inverted L pattern or Inverted Right angle Triangle
        7.1.5 Tilted Pyramid pattern with *
        7.1.6 Practice Patterns for *
    7.2 Number Patterns
        7.2.1 Number Pattern 1 - L shaped pattern of number
        7.2.2 Number Pattern 2 - Half Pyramid of Numbers
        7.2.3 Number Pattern 3 - Inverted half Pyramid
        7.2.4 Number Pattern 4 - Reverse Numbers
        7.2.5 Number Pattern 5 - Square of reverse numbers
        7.2.6 Number Patter 6 - Diamond Pattern with Numbers 1
        7.2.7 Number Patter 7 - Diamond Pattern with Numbers 2
        7.2.8 Number Pattern 8 - Tilted Pyramid
        7.2.9 Practice Patterns for Number Patterns
    7.3 Summary
8. Data Structures and Sequence
    8.1 Strings
        8.1.1 String Operations
        8.1.2 Formatting
        8.1.3 Concatenation and Repetition
        8.1.4 Split and Join
        8.1.5 Indexing
        8.1.6 Slicing
    8.2 Lists
        8.2.1 Indexing and Slicing
        8.2.2 Methods of List Objects
        8.2.3 List Comprehensions
        8.2.4 The del statement
    8.3 Tuples
        8.3.1 Tuple Methods
    8.4 Sets
        8.4.1 Demonstration of set operations
        8.4.2 Set Methods
    8.5 Dictionaries
        8.5.1 Dictionary Methods
    8.6 Looping Techniques on Sequence
    8.7 Summary:
    8.8 Exercise:
        8.8.1 Answer the following:
        8.8.2 True or False:
        8.8.3 Write your own Codes for this:
        8.8.4 Things to do:
9. Input-Output, Files and Exception Handling
    9.1 Input
    9.2 Output
        9.2.1 Fancier Output Formatting
    9.3 Reading and Writing Files
        9.3.1 Methods of File Objects
        9.3.2 Creating a file and Writing in it
        9.3.3 Opening a file and Reading its contents
        9.3.4 Reading Line by Line
        9.3.5 Reading and Writing other than text files
    9.4 Summary
    9.5 Exercise:
        9.5.1 Answer the following:
        9.5.2 True or False:
        9.5.3 Write your own Codes for this:
        9.5.4 Things to do:
10. Project 2: Automating the Task of Multiple Image Processing
    10.1 Changing File type (Extension)
    10.2 Resizing the photos
    10.3 Converting to Black and White
    10.4 Rotating the Images
    10.5 Changing the DPI of the image
    10.6 Summary:
    10.7 Things to do:
11. Classes
    11.1 Classes
    11.2 Class Objects
        11.2.1 Creating class with __init__() method
    11.3 Instance Objects
        11.3.1 Instantiating Objects
        11.3.2 How It Works
        11.3.3 Now let’s combine the class and instance and see some magic
        11.3.4 Let's see what's going on here:
    11.4 Method Objects
    11.5 Inheritance
    11.6 Multiple Inheritance
        11.6.1 Overriding methods
    11.7 Polymorphism
    11.8 Abstraction and Encapsulation
    11.9 How to control access
        11.9.1 Private Variables
    11.10 Summary:
    11.11 Exercise:
        11.11.1 Answer the following:
        11.11.2 True or False:
        11.11.3 Write your own Codes for this:
        11.11.4 Things to do:
12. Error and Exception Handling
    12.1 Errors and Exceptions
        12.1.1 Syntax Errors
        12.1.2 Exceptions
    12.2 Raising Exceptions
        12.2.1 raise Statement
        12.2.2 The AssertionError Exception
    12.3 Handling Exceptions
        12.3.1 try and except statements
        12.3.2 The else clause
    12.4 Defining Clean-up Actions
    12.5 Summary:
    12.6 Exercise:
        12.6.1 Answer the following:
        12.6.2 True or False:
        12.6.3 Write your own Codes for this:
13. Modules and Packages
    13.1 Modules
        13.1.1 Definition of Module:
    13.2 More on Modules
    13.3 Importing Modules
        13.3.1 Importing Modules from other modules
        13.3.2 Importing Names from a module directly
        13.3.3 Importing ALL Names from a module directly
        13.3.4 Importing Module as some other name
    13.4 Standard Modules
    13.5 The dir() Function
    13.6 Packages
        13.6.1 Our sample Package: sound
        13.6.2 Calling a package to use
        13.6.3 Popular Packages in Python
    13.7 Summary:
    13.8 Exercise:
        13.8.1 Answer the following:
        13.8.2 True or False:
        13.8.3 Things to do:
14. Project 3 - Gui Based Currency Converter
    14.1 Introduction to Tkinter
    14.2 Basics of Tkinter
    14.3 Currency Converter GUI window
        14.3.1 using .pack()
        14.3.2 using .grid()
    14.4 Code to convert currency
    14.5 Final App - Currency Converter
    14.6 Summary:
    14.7 Things to Do:
15. Numpy
    15.1 Welcome to NumPy!
    15.2 Installing NumPy
    15.3 How to import NumPy
    15.4 Difference between a Python list and a NumPy array
    15.5 Why NumPy?
    15.6 What is an array?
        15.6.1 NumPy Array (ndarray)
    15.7 How to create a basic array
        15.7.1 Zeros, Ones, and Random Numbers
        15.7.2 Create sequence using range functions
        15.7.3 Specifying your data type
        15.7.4 Printing Arrays
    15.8 Adding, removing, and sorting elements
        15.8.1 Sort
        15.8.2 Adding (concatenation)
        15.8.3 Removing
    15.9 Shape and Size of array
    15.10 Reshape
    15.11 Adding Axis to the array
    15.12 Indexing and slicing
    15.13 Creating Array from existing data
    15.14 Copies and Views
        15.14.1 No Copy at All
        15.14.2 View or Shallow Copy
        15.14.3 Deep Copy
    15.15 How does a NumPy array look like in real life?
        15.15.1 Tables and Spreadsheets
        15.15.2 Audio and Timeseries
        15.15.3 Images
    15.16 Summary
16. Numpy Operations
    16.1 Basic array operations
        16.1.1 Universal Functions
    16.2 Broadcasting
    16.3 More useful array operations
    16.4 Creating matrices
    16.5 unique items and counts
    16.6 Transposing and reshaping a matrix
    16.7 Reverse an array
        16.7.1 Reversing a 1D array
        16.7.2 Reversing a 2D array
    16.8 Reshaping and flattening multidimensional arrays
    18.9 Working with mathematical formulas
    16.10 How to save and load NumPy objects
    16.11 Summary:
17. Pandas Introduction
    17.1 What is Pandas
    17.2 Why Pandas?
    17.3 Pandas install and import
    17.4 Data handled in pandas
    17.5 DataFrame
        17.5.1 Creating a DataFrame
        17.5.2 Index in DataFrame
        17.5.3 Series from DataFrame
    17.6 Columns in DataFrame
        17.6.1 New Column in DataFrame
        17.6.2 Column Deletion in DataFrame
        17.6.3 Changing the value in a Column
    17.7 Rows in DataFrame
        17.7.1 Row Selection
        17.7.2 Row Slice (Multiple Row Selection)
    17.8 Operations on DataFrame
    17.9 Reading data in Pandas from file
        17.9.1 Understanding this dataset
    17.10 Writing Data from pandas to a file
    17.11 First Check on DataFrame
        17.11.1 dtypes
        17.11.2 info()
        17.11.3 head()
        17.11.4 tail()
    17.12 Selecting a part of DataFrame
        17.12.1 Selecting Columns
        17.12.2 Selecting Rows (Filter Rows)
        17.12.3 Selecting both Rows and Columns
    17.13 Summary:
18. Pandas in Action
    18.1 Creating new Columns from old ones
    18.2 Deleting columns from the DataFrame
    18.3 Renaming the columns
    18.4 Summary Statistics
    18.5 Grouped By Category
    18.6 Sort Table Rows
    18.7 Combining data from Multiple Tables
        18.7.1 Concatenating objects
        18.7.2 Joining using common Identifier
    18.8 Summary:
19. Visualization in Python
    19.1 Visualization
        19.1.1 Importance of Data Visualization
        19.1.2 Basic Visualization
        19.1.3 Basic line Plot in Pandas
        19.1.4 Basic Scatter Plot in Pandas
        19.1.5 Other Plot Methods
        19.1.6 Basic Box plot in pandas
        19.1.7 Subplots
        19.1.8 Saving the Plot
    19.2 Data Visualization in Python
        19.2.1 Matplotlib
        19.2.2 Seaborn
        19.2.3 ggplot
        19.2.4 Bokeh
        19.2.5 Folium
        19.2.6 Gleam
    19.3 Summary:
20. Visualization Using Matplotlib.Pyplot
    20.1 Introduction and History
    20.2 How to use Matplotlib?
        20.2.1 The Matplotlib Object Hierarchy
        20.2.2 Types of inputs to plotting functions
    20.3 Parts of a Figure
        20.3.1 Figure
        20.3.2 Axes
        20.3.3 Axis
        20.3.4 Artist
    20.4 Matplotlib Interfaces
        20.4.1 The object-oriented interface
        20.4.2 The pyplot interface
        20.4.3 Which way to go?
    20.5 Repeat Plots using Function
    20.6 Pyplot
    20.7 plot() function
        20.7.1 Plotting labeled data
        20.7.2 Plotting multiple sets of data
        20.7.3 Formatting the style
    20.8 plot(parameters)
        20.8.1 x, y
        20.8.2 Format Strings (fmt)
        20.8.3 data
    20.9 plot() Returns
    20.10 plot(**kwargs)
    20.11 Plotting with categorical variables
    20.12 Controlling line properties
    20.13 Working with multiple figures and axes
    20.14 Inserting Text in/on the plot
    20.15 Using mathematical expressions in text
        20.15.1 Annotating text
    20.16 Logarithmic and other nonlinear axes
    20.17 Summary:
21. Visualization Matplotlib O-O Interface and Sample Plots
    21.1 Object-Oriented API vs. Pyplot
    21.2 Our data
    21.3 First Step
    21.4 Controlling the Styles
    21.5 Customizing the Plot
    21.6 Combining multiple visualizations
    21.7 Text Formatting on Plot
        21.7.1 Basic Text commands
    21.8 Saving the Plot
    21.9 Sample Plots
        21.9.1 Histogram
        21.9.2 Paths
        21.9.3 Three Dimensional Plotting
        21.9.4 Pie Chart
        21.9.5 Subplot Example
    21.10 Summary
Bibliography
Notes
About the Author