Python for Data Analysis: A Beginners Guide to Master the Fundamentals of Data Science and Data Analysis by Using Pandas, Numpy and Ipython

Table of contents :
Introduction
What You Should Keep in Mind
All Tech Work Has A Creative Element
Some Things Will Be Harder at First
You Don’t Know Everything
You Won’t Work Alone
Some Rules
To Python Beginners
Chapter 1: What is Data Science/Analysis?
Data Science vs. Data Analysis
An Example
Data Life Cycle
Data Collection
Data Cleaning
Data Wrangling
Analysis
Application
Why Python?
Chapter 2: Setting Up Your Environment
Anaconda
Windows Anaconda Installation
macOS Anaconda Installation
Using the Installer
Using the Command-line
Linux Anaconda Installation
Chapter 3: iPython & Jupyter
iPython
iPython Installation & Getting Started
iPython Special Features
Getting Information About the Object
Magic Functions
List of Magic Functions
Running and Editing a Python Script
Running System Commands
Jupyter
What Does it Do?
A Quick Overview
Understanding Modality
Jupyter Cell Magic Functions
IPyWidgets
Interactives
Types of Widgets
Numeric Widgets
Boolean Widgets
Selection Widgets
Chapter 4: Pandas
Setting Up Your Environment
Pandas Data Structures
DataFrames & Series
Labelling Indexes In A Series
Converting Tuples & Dictionaries Into A Series
Accessing Data In A DataFrame
Deleting Columns
How to Read and Write Data in Pandas
Learning More About the Data
Writing A DataFrame to A File
Selecting Data
Creating Plots
Creating New Columns
Adding and Removing Columns
Doing Statistics
Combining Tables
Dealing With Textual Data
Find length
Resources
Table A : Reading and Writing data table
Table B:2019 Weekly Data
Table C: The second set of 2019 data for DataFrame combining exercises and others
Chapter 5: NumPy
Installation
The Importance of NumPy Arrays
What is a NumPy Array?
Creating Arrays
Learning About An Array
Basic Array Operations
Accessing Elements, Slicing and Iterating Arrays
Manipulating Shapes
Stacking Arrays
Splitting An Array
Final Words & FAQ
When Do I Know I Have Enough Projects in My Portfolio?
What Type of PC Do I Need for Data Science?
What Are Some of the Skills I Will Need?
Is There a Future in Data Science/Analytics?
What Will it Take for Me to Become a Data Analyst?
Other Books from the Author
References