MS Excel Automation | Excel Data Analysis with Python
MS Excel Automation | Excel Data Analysis with Python
Last updated 1/2024
Duration: 6h49m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 3.85 GB
Genre: eLearning | Language: English
Excel Python Bootcamp | Revolutionize Your Excel Workflow with Python Automation and Data Analysis
What you'll learn
Automate Excel tasks using Python-based libraries like openpyxl.
Create, modify, and format Excel workbooks and sheets using openpyxl.
Insert and manipulate data, comments, and images in Excel using openpyxl.
Generate various types of charts such as column, line, bar,area, bubble, using openpyxl.
Read and write Excel files using openpyxl in read-only or write-only modes.
Apply conditional formatting to cells using built-in or custom rules.
Configure print settings in Excel for better printing results.
Filter and sort data in Excel for better data analysis.
Work with tables and apply data validation in cells.
Use formulas to perform calculations in Excel.
Protect and secure Excel workbooks using openpyxl.
Data Validation with Excel using Openpyxl
Requirements
You should have basic knowledge of MS Excel
You should have basic knowledge python with beginner level experince
You did not need to buy extra software or course
Description
Introduction to MS Excel Automation | Excel Data Analysis with Python
The course "MS Excel Automation | Excel Data Analysis with Python" offers a comprehensive guide to using Python with Microsoft Excel to perform advanced data analysis and automate repetitive tasks.
The course introduces the basic concepts of
Excel automation with Python
libraries like
openpyxl
and demonstrates how to create and manipulate workbooks and sheets.
The students will learn to insert and format data, including merging and unmerging cells, adding comments, and applying conditional formatting. The course also covers various chart types, including column, line, pie, and bubble charts, and how to use formulas and data validation in
Excel
.
Additionally, the course teaches the students how to protect and secure workbooks and apply filters and sorting.
Upon completion of the course, the students will have a solid understanding of how to use
Python with Excel
to automate data analysis tasks and enhance their productivity.
Outlines for this course MS Excel Automation with OpenPyxl
Chapter 01:
Introduction to Excel
Excel Python-based Libraries
Installation openpyxl
Creating a basic file to insert data into Excel using openpyxl
Chapter 02:
Creating Workbook & Sheet
Inserting Data into the cell
Accessing cell(s)
Loading a file
Comments
Saving file
Chapter 03:
Inserting image
Merging and unmerging cell
Formatting text
Alignment
Border
Background color
Chapter 04:
Read-only mode
Write only mode
Openpyxl with Pandas
Openpyxl with Numpy
Chapter 05:
Creating Charts in Excel using OpenPyXl:
Column chart
Bar chart
Line chart
Area chart
Bubble chart
Chapter 06:
Conditional Formatting
Greater than a specific value
Less than a specific value
Equal to a specific value
Contain specific value
Between values
The first 5 records highlights
The last 5 records highlights
Chapter 07:
Sorting
Filtering
Print setting in Excel
Chapter 08:
Table with openpyxl
Table creation
Inserting new row and inserting data
Inserting new column and inserting data
ROW Background Color Change
Column Background Color Change
Chapter 09:
Working with Formulas:
Protecting and Securing Workbooks:
Data Validation in Cell
After this MS Excel Automation with Python, Student able to:
Understand the fundamentals of Excel and its functionalities.
Work with Excel files using Python-based libraries like
openpyxl
.
Install and utilize
openpyxl
for creating, reading, and manipulating Excel files programmatically.
Create workbooks and sheets, insert data into specific cells, access cell values, and modify cell content.
Load existing Excel files, add comments to cells, and manage file-saving operations.
Perform advanced operations such as inserting images, merging and unmerging cells, and formatting text, alignment, borders, and cell background colors.
Handle Excel files in read-only and write-only modes using
openpyxl
.
Integrate
openpyxl
with Pandas and Numpy libraries for data manipulation and analysis within Excel files.
Generate various types of charts (e.g., column, bar, line, area, bubble) in Excel using
openpyxl
.
Apply conditional formatting to highlight cells based on specific conditions.
Implement sorting, filtering, and print settings programmatically in Excel.
Manage tables in Excel, insert data, and customize appearance by changing row and column background colors.
Work with formulas within Excel files using Python and understand workbook security techniques like data validation and protection settings.
Instructor Experiences and Education:
Faisal Zamir
is an experienced programmer and an expert in the field of computer science. He holds a Master's degree in Computer Science and has
over 7 years of experience
working in schools, colleges, and university. Faisal is a highly skilled instructor who is passionate about teaching and mentoring students in the field of computer science.
As a programmer, Faisal has worked on various projects and has experience in multiple programming languages, including PHP, Java, and Python.
He has also worked on projects involving web development, software engineering, and database management. This broad range of experience has allowed Faisal to develop a deep understanding of the fundamentals of programming and the ability to teach complex concepts in an easy-to-understand manner.
As an instructor, Faisal has a proven track record of success. He has taught students of all levels, from beginners to advanced, and has a passion for helping students achieve their goals.
Faisal has a unique teaching style that combines theory with practical examples, which allows students to apply what they have learned in real-world scenarios.
Overall,
Faisal Zamir
is a skilled programmer and a talented instructor who is dedicated to helping students achieve their goals in the field of computer science. With his extensive experience and proven track record of success, students can trust that they are learning from an expert in the field.
What you can do with OpenPyXL Python Library
1. Create new Excel workbooks and worksheets.
2. Read and write data to Excel spreadsheets.
3. Format Excel cells with fonts, colors, borders, and alignment.
4. Merge and unmerge cells in Excel.
5. Create charts, such as column, line, pie, and scatter charts, in Excel.
6. Add images to Excel spreadsheets.
7. Use conditional formatting to highlight cells that meet specific criteria.
8. Sort and filter data in Excel.
9. Create tables in Excel.
10. Validate data entered into Excel cells.
11. Work with Excel formulas, including functions and operators.
12. Protect Excel workbooks with passwords and user permissions.
13. Control print settings in Excel.
30-day money-back guarantee for MS Excel Automation | Excel Data Analysis with Python
A 30-day money-back guarantee is offered for the MS Excel Automation | Excel Data Analysis with Python course.
If for any reason you are not satisfied with the course content or feel that it does not meet your expectations, you can request a refund within 30 days of purchase.
Thank you
Faisal Zamir
Who this course is for:
Business Analysts and Data Analysts who want to automate their Excel tasks and perform data analysis more efficiently using Python.
Students and Professionals who want to learn how to use Python to automate Excel tasks and perform data analysis.
Excel Users who want to enhance their knowledge and skills by learning how to integrate Python with Excel for automation and data analysis.
Financial Analysts who work with large datasets and want to learn how to use Python to analyze and visualize financial data in Excel.
Entrepreneurs and Small Business Owners who want to automate their business processes and analyze their data using Python and Excel.
Researchers who want to use Python to automate data collection, analysis, and visualization in Excel.
Anyone who wants to learn how to use Python to automate Excel tasks and perform data analysis, regardless of their prior experience with Excel or Python.
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