MS Excel Automation | Excel Data Analysis with Python
MS Excel Automation | Excel Data Analysis with Python, available at $59.99, has an average rating of 4.46, with 63 lectures, 1 quizzes, based on 67 reviews, and has 14397 subscribers.
You will learn about 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 This course is ideal for individuals who are Business Analysts and Data Analysts who want to automate their Excel tasks and perform data analysis more efficiently using Python. or Students and Professionals who want to learn how to use Python to automate Excel tasks and perform data analysis. or Excel Users who want to enhance their knowledge and skills by learning how to integrate Python with Excel for automation and data analysis. or Financial Analysts who work with large datasets and want to learn how to use Python to analyze and visualize financial data in Excel. or Entrepreneurs and Small Business Owners who want to automate their business processes and analyze their data using Python and Excel. or Researchers who want to use Python to automate data collection, analysis, and visualization in Excel. or 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. It is particularly useful for Business Analysts and Data Analysts who want to automate their Excel tasks and perform data analysis more efficiently using Python. or Students and Professionals who want to learn how to use Python to automate Excel tasks and perform data analysis. or Excel Users who want to enhance their knowledge and skills by learning how to integrate Python with Excel for automation and data analysis. or Financial Analysts who work with large datasets and want to learn how to use Python to analyze and visualize financial data in Excel. or Entrepreneurs and Small Business Owners who want to automate their business processes and analyze their data using Python and Excel. or Researchers who want to use Python to automate data collection, analysis, and visualization in Excel. or 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.
Enroll now: MS Excel Automation | Excel Data Analysis with Python
Summary
Title: MS Excel Automation | Excel Data Analysis with Python
Price: $59.99
Average Rating: 4.46
Number of Lectures: 63
Number of Quizzes: 1
Number of Published Lectures: 63
Number of Published Quizzes: 1
Number of Curriculum Items: 66
Number of Published Curriculum Objects: 66
Number of Practice Tests: 1
Number of Published Practice Tests: 1
Original Price: $22.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- 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.
Target Audiences
- 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.
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 openpyxland 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:
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Understand the fundamentals of Excel and its functionalities.
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Work with Excel files using Python-based libraries like openpyxl.
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Install and utilize openpyxl for creating, reading, and manipulating Excel files programmatically.
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Create workbooks and sheets, insert data into specific cells, access cell values, and modify cell content.
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Load existing Excel files, add comments to cells, and manage file-saving operations.
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Perform advanced operations such as inserting images, merging and unmerging cells, and formatting text, alignment, borders, and cell background colors.
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Handle Excel files in read-only and write-only modes using openpyxl.
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Integrate openpyxl with Pandas and Numpy libraries for data manipulation and analysis within Excel files.
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Generate various types of charts (e.g., column, bar, line, area, bubble) in Excel using openpyxl.
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Apply conditional formatting to highlight cells based on specific conditions.
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Implement sorting, filtering, and print settings programmatically in Excel.
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Manage tables in Excel, insert data, and customize appearance by changing row and column background colors.
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Work with formulas within Excel files using Python and understand workbook security techniques like data validation and protection settings.
Instructor Experiences and Education:
Faisal Zamiris 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
Course Curriculum
Chapter 1: Python with Excel Chapter 01
Lecture 1: 01 Chapter 01 Excel with Python
Lecture 2: 02 Introduction to Excel
Lecture 3: 03 Libraries used for Excel with Python
Lecture 4: 04 Installation for OpenPyXl for Excel with Python
Lecture 5: 05 Example 01
Lecture 6: 06 Example 02
Chapter 2: Python with Excel Chapter 02
Lecture 1: 01 Chapter 02 Excel with Python
Lecture 2: 02 Creating a Workbook
Lecture 3: 03 Creating a worksheet
Lecture 4: 04 Inserting data into cell Ex1
Lecture 5: 05 Inserting data into cell Ex2 and Ex3
Lecture 6: 06 Accessing cell data Ex1
Lecture 7: 07 Accessing cell data Ex2
Lecture 8: 08 Accessing cell data Ex3
Lecture 9: 09 Accessing cell data Ex4
Lecture 10: 10 Accessing cell data Ex5
Lecture 11: 11 Loading a File
Lecture 12: 12 Comments in Excel with openpyxl
Lecture 13: 13 Saving a file in openpyxl
Chapter 3: Python with Excel Chapter 03
Lecture 1: 01 Chapter 03 Excel with Python
Lecture 2: 02 Inserting Images in Excel
Lecture 3: 03 Merging and Unmerging in Excel
Lecture 4: 04 Formatting Text in Excel with Python
Lecture 5: 05 Alignment in Excel with Python
Lecture 6: 06 Border in Excel with Python
Lecture 7: 07 Background color in Excel with Python
Chapter 4: Python with Excel Chapter 04
Lecture 1: 01 Outline Chapter 04 Openpyxl Excel
Lecture 2: 02 Read Only Mode with Openpyxl
Lecture 3: 03 Write Only Mode with Openpyxl
Lecture 4: 04 Openpyxl with Pandas Example
Lecture 5: 05 Openpyxl with Numpy Example
Chapter 5: Python with Excel Chapter 05
Lecture 1: 01 Outline Chapter 05 Openpyxl Excel
Lecture 2: 02 Creating Column chart in Excel with Python
Lecture 3: 03 Bar Chart in Excel with Python
Lecture 4: 04 Create Line Chart in Excel with Python
Lecture 5: 05 Area Chart in Excel with Python
Lecture 6: 06 Bubble Chart in Excel with Python
Chapter 6: Python with Excel Chapter 06
Lecture 1: 01 Excel with OpenPyXl Chapter 06 Outline
Lecture 2: 02 Conditional Formatting with Greater Value highlight
Lecture 3: 03 Conditional Formatting with Less Value highlight
Lecture 4: 04 Conditional Formatting with Equal Value highlight
Lecture 5: 05 Conditional Formatting with Between Value highlight
Lecture 6: 06 Conditional Formatting with First records highlight
Lecture 7: 07 Conditional Formatting with Last records highlight
Lecture 8: 08 Tasks 1 and Solution
Lecture 9: 09 Tasks 2 and Solution
Lecture 10: 10 Tasks 3 and Solution
Chapter 7: Python with Excel Chapter 07
Lecture 1: 01 Excel with OpenPyXl Chapter 07 Outline
Lecture 2: 02 Sorting in Excel with Openpyxl
Lecture 3: 03 Filter in Excel with OpenPyXl
Lecture 4: 04 Print Setting with Openpyxl
Chapter 8: Python with Excel Chapter 08
Lecture 1: 01 Excel with OpenPyXl Chapter 08 Outline
Lecture 2: 02 Table Creating in openpyxl
Lecture 3: 03 Inserting row and data in table
Lecture 4: 04 Inserting Column with Openpyxl
Lecture 5: 05 ROW background color with openpyxl
Lecture 6: 06 Column background color with openpyxl
Chapter 9: Python with Excel Chapter 09
Lecture 1: 01 Excel with OpenPyXl Chapter 09 Outline
Lecture 2: 02 How to set Furmula in Excel with Openpyxl
Lecture 3: 03 Excel Forumulas with Openpyxl
Lecture 4: 04 More Excel formulas with Openpyxl
Lecture 5: 05 Protect Workbook and Sheet with Openpyxl
Lecture 6: 06 Data Validation with Openpyxl
Chapter 10: Updated Section
Chapter 11: Practice Test
Instructors
-
Faisal Zamir
Programmer -
Jafri Code
Programming and Web Instructor -
Pro Python Support
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 2 votes
- 3 stars: 9 votes
- 4 stars: 23 votes
- 5 stars: 30 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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