★ Chapter 1: Getting Started with the Python Programming Language
1.1 Before you begin
____Limitations of Excel and VBA
____Features of Python
1.2 Getting Started with Python
____Installing the Python development environment
____Running Python
____Write Python code in an integrated development environment
1.3 Using Jupyter Notebook
____Running Jupyter Notebook and Creating a Notebook
____Jupyter Notebook Key Features Overview
____Write code in Jupyter Notebook
____Writing documents in Jupyter Notebook
____What else can you do?
1.4 Summary

★ Chapter 2: Python Basic Grammar
2.1 Variables and data types
____variable
____number(int, float)
____string (str)
____bool
____list
____tuple
____set
____dictionary
2.2 Control statements
____conditional statement
____loop
2.3 Data Output
____Default Output
____Specify output format
2.4 Summary

★ Chapter 3: Functions, Classes, and Modules
3.1 Function
Definition and calling of ____function
____Built-in functions
3.2 Class
____Classes and Objects
Inheritance of ____class
3.3 Module
Create and import a ____module
____Built-in module
____package
3.4 Summary

★ Chapter 4: Reading and Writing Files and String Processing
4.1 Reading and Writing Files
Basic structure for reading and writing ____files
Read ____file
Read and process the ____ file line by line
Write ____file
Reading and writing files with the ____with statement
4.2 String Handling
Splitting a string: split()
____Remove unnecessary strings: strip()
____Concatenating strings: join()
____Finding strings: find(), count(), startswith(), endswith()
____Replace a string: replace()
____Change case: lower(), upper()
4.3 Summary

★ Chapter 5: Libraries for Data Processing and Analysis
5.1 NumPy: Efficient Array Data Operations
____Creating array data
____Array data operations
Select ____array data
5.2 Pandas, powerful for tabular data processing
____Data Structure and Creation
Reading and writing data files in ____ table format
____table data operations
Select ____table data
____Table Data Integration
5.3 Summary

★ Chapter 6: Library for handling Excel files
6.1 Creating Excel files with XlsxWriter
____XlsxWriter Basic Usage
Writing data of various data types with ____XlsxWriter
Formatting cells with ____XlsxWriter
Inserting pictures and text boxes with ____XlsxWriter
6.2 xlwings for interacting with Excel using Python
Basic usage of ____xlwings
Writing and reading various data types with ____xlwings
Outputting Excel files with ____xlwings
6.3 Summary

★ Chapter 7: Handling Excel Files and Data
7.1 Processing Excel files using Python
7.2 Integrating Excel files
Excel data structure for efficient data processing
____Combine multiple Excel files into one
7.3 Filtering and Calculating Excel Data
____Data Filtering
____Data calculation
____Apply to multiple Excel files
7.4 Processing Useful Excel Functions with Python
____Find and retrieve data from a specified range
Enter results based on ____conditions
Apply different formats based on ____conditions
7.5 Excel Data Cleaning
____Check and process missing data
____Data extraction and organization
7.6 Summarizing and Aggregating Excel Data
____Creating a Pivot Table Basics
____Advanced Pivot Table Creation
7.7 Retrieving data from a web page
Basics of importing ____table data
____ table data import in-depth
7.8 Summary

★ Chapter 8: Excel Data Visualization
8.1 Excel Chart
____Basic structure of code that creates Excel charts
____bar chart
____line chart
____area chart
____Pie chart
____Scatter chart
8.2 Excel Sparklines
____Types of sparklines and examples of their use
____Basic structure of code that generates sparklines
8.3 Drawing Graphs with Pandas
Basic structure for ____graphs
____line graph (line chart)
____bar graph (bar chart)
____Scatterplot (Scatter Chart)
____Pie graph (circular chart)
____Area graph (area chart)
____histogram
____Box graph (box and whisker chart)
____Save the graph and add it to an Excel file
8.4 Summary

★ Chapter 9: Statistical Data Analysis Using Excel and Python
9.1 Basics of Statistical Data Analysis
____Understanding Basic Statistics
____Get basic statistics
9.2 Advanced statistical data analysis
____Correlation Analysis
____Regression analysis
9.3 Summary

- Installing a Python development environment using Anaconda and using Jupyter Notebook
- Python basic grammar, string data processing (split, delete, concatenate, find, replace)
- Array and table data processing using NumPy and Pandas (operations, aggregation, data selection and deletion, integration)
- Format and write Excel files with XlsxWriter, insert pictures and text boxes into Excel files
- Read and write Excel files with document security applied using xlwings, print them, or output them as PDF files.
- Handling Excel files (reading, writing, integrating, calculating, aggregating, checking for and handling missing data, pivot tables)
- Drawing Excel charts and sparklines using the xlsxwriter engine in Pandas
- Data visualization with Pandas and Matplotlib (line/bar/pie/area/box graphs, scatter plots, histograms)
- Statistical data analysis using Excel and Python (basic statistical analysis, correlation analysis, regression analysis)