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:

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 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.

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