Module 1
Python Installation
Anaconda Prompt
Python REPL: An Interactive Python Session
Package Managers: Conda and pip
Conda Environments
Jupyter Notebooks
Running Jupyter Notebooks
Notebook Cells
Edit vs. Command Mode
Run Order Matters
Shutting Down Jupyter Notebooks
Visual Studio Code
Installation and Configuration
Running a Python Script
Module 2
Data Types
Objects
Numeric Types
Booleans
Strings
Indexing and Slicing
Indexing
Slicing
Data Structures
Lists
Dictionaries
Tuples
Sets
Control Flow
Code Blocks and the pass Statement
The if Statement and Conditional Expressions
The for and while Loops
Module Title : Python for excel
Duration : 5 days
Course Outline :: Python for excel ::
List, Dictionary, and Set Comprehensions
Functions
Modules and the import Statement
The datetime Class
Looping in Python
Module 3 NumPy
Getting Started with NumPy
NumPy Array
Vectorization and Broadcasting
Universal Functions (ufunc)
Creating and Manipulating Arrays
Getting and Setting Array Elements
Useful Array Constructors
View vs. Copy
Module 4 Data Analysis with pandas
Data Frame and Series
Index
Columns
Data Manipulation
Selecting Data
Setting Data
Missing Data
Duplicate Data
Arithmetic Operations
Working with Text Columns
Applying a Function
View vs. Copy
Combining DataFrames
Concatenating
Joining and Merging
Descriptive Statistics and Data Aggregation
Descriptive Statistics
Grouping
Pivoting and Melting
Plotting
Course Outline :: Python for excel ::
Matplotlib
Plotly
Importing and Exporting Data Frames
Exporting CSV Files
Importing CSV Files
DatetimeIndex
Creating a DatetimeIndex
Filtering a DatetimeIndex
Working with Time Zones
Common Time Series Manipulations
Shifting and Percentage Changes
Rebasing and Correlation
Resampling
Rolling Windows
Limitations with pandas
Conclusion
Module 5 Excel File Manipulation with pandas
Case Study: Excel Reporting
Reading and Writing Excel Files with pandas
The read_excel Function and ExcelFile Class
The to_excel Method and ExcelWriter Class
Limitations When Using pandas with Excel Files
The Reader and Writer Packages
When to Use Which Package
The excel.py Module
OpenPyXL
XlsxWriter pyxlsb xlrd, xlwt, and xlutils
Advanced Reader and Writer Topics
Working with Big Excel Files
Formatting DataFrames in Excel
Case Study (Revisited): Excel Reporting
Module 6. Excel Automation
Course Outline :: Python for excel ::
Getting Started with xlwings
Using Excel as Data Viewer
The Excel Object Model
Running VBA Code
Converters, Options, and Collections
Working with DataFrames
Converters and Options
Charts, Pictures, and Defined Names
Case Study (Re-Revisited): Excel Reporting
Advanced xlwings Topics
Module 7. Python-Powered Excel Tools
Using Excel as Frontend with xlwings
Excel Add-in
Quickstart Command
Run Main
RunPython Function
Deployment
Python Dependency
Standalone Workbooks: Getting Rid of the xlwings Add-in
Configuration Hierarchy
Settings
Conclusion
Module 8 The Python Package Tracker
What We Will Build
Core Functionality
Web APIs
Databases
Exceptions
Application Structure
Frontend
Backend
Debugging
Conclusion
Module 9 User-Defined Functions (UDFs)
Getting Started with UDFs
UDF Quickstart
Course Outline :: Python for excel ::
Case Study: Google Trends
Introduction to Google Trends
Working with DataFrames and Dynamic Arrays
Fetching Data from Google Trends
Plotting with UDFs
Debugging UDFs
Advanced UDF Topics
Basic Performance Optimization
Caching
The Sub Decorator
Course agenda
Time Day 1 Day 2 Day 3 Day 4 Day 5
9:00am -
10:30am
Module 1 Module 2 (cont.) Module 4 Module 5 Module 7
10:30am -
10:45am
Morning Break Morning Break Morning Break Morning Break Morning Break
10:45am -
12:30pm
Module 1 (cont.) Module 3 Module 4 (cont.) Module 5 (cont.) Module 7 (cont.)
12:30pm -
1:30pm
Lunch Break Lunch Break Lunch Break Lunch Break Lunch Break
1:30pm -
3:30pm
Module 1( cont.) Module 3 (cont.) Module 4 (cont.) Module 6 Module 7 (cont.)
3:30pm -
3:45pm
Afternoon Break Afternoon Break Afternoon Break Afternoon Break Afternoon Break
3:45pm -
5:00pm
Programme scope, delivery arrangements and suitability are confirmed during enquiry.