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Automate Excel using Python – Xlwings | Series 2

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Automate Excel using Python – Xlwings | Series 2, available at $19.99, with 55 lectures, and has 46 subscribers.

You will learn about Writing macros (in python) for their Excel sheets Automate Excel without any VBA code (installed by default) Build your own Formulas by coding User-defined Functions (UDFs) in Python Practical hands-on experience with Industry level datasets Automate, streamline and completely revolutionize your Excel workflow with Python macros Master unique concepts, tools and case studies, which you won't find ANY other course, guaranteed Get LIFETIME access to course materials and a 1-on-1 expert support Continuous course updation when python packages updated with new features This course is ideal for individuals who are Beginner developers who want to make their career on Data Science or People working as an Analyst, using Excel mostly It is particularly useful for Beginner developers who want to make their career on Data Science or People working as an Analyst, using Excel mostly.

Enroll now: Automate Excel using Python – Xlwings | Series 2

Summary

Title: Automate Excel using Python – Xlwings | Series 2

Price: $19.99

Number of Lectures: 55

Number of Published Lectures: 55

Number of Curriculum Items: 55

Number of Published Curriculum Objects: 55

Original Price: $34.99

Quality Status: approved

Status: Live

What You Will Learn

  • Writing macros (in python) for their Excel sheets
  • Automate Excel without any VBA code (installed by default)
  • Build your own Formulas by coding User-defined Functions (UDFs) in Python
  • Practical hands-on experience with Industry level datasets
  • Automate, streamline and completely revolutionize your Excel workflow with Python macros
  • Master unique concepts, tools and case studies, which you won't find ANY other course, guaranteed
  • Get LIFETIME access to course materials and a 1-on-1 expert support
  • Continuous course updation when python packages updated with new features

Who Should Attend

  • Beginner developers who want to make their career on Data Science
  • People working as an Analyst, using Excel mostly

Target Audiences

  • Beginner developers who want to make their career on Data Science
  • People working as an Analyst, using Excel mostly

This course teaches how to automate Industry-level datasets maintained in Excel sheets using Python programming language.

MS Excel is a very helpful tool for record-keeping. But the language that comes by default for macro is VBA, which is dated. And in the field of Data Analysis, Python has a lot of interesting packages which makes a job easy. Package like xlwings links any Excel with Python macros. Packages like Pandas, takes data into tabular format i.e. dataframe and also has customized filtering of rows or columns for complex data analysis. Packages like Matplotlib, Plotly enables to create different plots – line plot, Scatter plot, Heat map for finding the correlation b/w different parameters. You would learn the most modern interactive chart with required customization.

In the Series, 3 Case studies has been picked from Industry process line. And correspondingly, Python macros are created to:

  1. reduce time in analysis

  2. enable customization using python packages

  3. reduce macros code lines in VBA codebase.

  4. create customized User-defined modules by python functions.

The “Data Science” field is mainly composed of 3 stages:
a. Data Acquisition: The method of fetching data from the storage like Excel here.

b. Data Wrangling: The method of filtering, extracting the required data from the raw dataset.

c. Data Visualization: The method of visualizing the data in the best possible form of chart. Here, we target at showing the most modern interactive chart.

Course Curriculum

Chapter 1: Introduction

Lecture 1: About Instructor

Lecture 2: Academy's Courses (All)

Lecture 3: Course Outline

Lecture 4: Communication: Doubts, Request feature

Chapter 2: Chapter 0: Installation

Lecture 1: Anaconda

Lecture 2: Package Installation

Lecture 3: Sublime Text 3

Lecture 4: Xlwings Installation pt 1

Lecture 5: Xlwings Installation pt 2

Chapter 3: AutoPlot part 1

Lecture 1: Demo

Lecture 2: Explain data and its types

Lecture 3: Code Hierarchy | Outline

Lecture 4: Code Hierarchy | Import packages

Lecture 5: Code Hierarchy | Date formatter utility function

Lecture 6: Code Hierarchy | Plotly chart 1 utility function part 1

Lecture 7: Code Hierarchy | Plotly chart 1 utility function part 2

Lecture 8: Code Hierarchy | Plotly chart 2 utility function

Lecture 9: Code Hierarchy | Plotly chart 3 utility function

Lecture 10: Define Init function

Lecture 11: Define Dataframe for dtype_1 | part 1

Lecture 12: Define Dataframe for dtype_1 | part 2

Lecture 13: Define plot variables for dtype_1

Lecture 14: Call Plot Function for dtype_1

Lecture 15: Define Dataframe for dtype_2

Lecture 16: Define plot variables for dtype_2

Lecture 17: Call Plot Function for dtype_2

Lecture 18: Execute

Lecture 19: Use of Plotly charts | Line Plot

Lecture 20: Bonus: Define button_run() in excel

Chapter 4: AutoPlot part 2

Lecture 1: Demo

Lecture 2: Explain data and its types

Lecture 3: Code Hierarchy | Outline

Lecture 4: Code Hierarchy | Import packages

Lecture 5: Code Hierarchy | Date formatter utility function

Lecture 6: Code Hierarchy | Plotly chart 1 utility function

Lecture 7: Code Hierarchy | Plotly chart 2 utility function

Lecture 8: Code Hierarchy | Plotly chart 3 utility function

Lecture 9: Define Init function

Lecture 10: Define Dataframe for chart 1

Lecture 11: Define plot variables for chart 1

Lecture 12: Call Plot Function for chart 1

Lecture 13: Define Dataframe for chart 2

Lecture 14: Define plot variables for chart 2

Lecture 15: Call Plot Function for chart 2

Lecture 16: Define Dataframe for chart 3

Lecture 17: Define plot variables for chart 3

Lecture 18: Call Plot Function for chart 3

Lecture 19: Execute

Lecture 20: Use of Plotly charts | Scatter Plot

Chapter 5: Automatic generation of Rent Agreement

Lecture 1: Demo

Lecture 2: Explain Project

Lecture 3: Code Hierarchy | Outline | Import packages | Input vars| Directory

Lecture 4: Code Hierarchy | Main func part 1

Lecture 5: Code Hierarchy | Main func part 2

Lecture 6: Execute

Instructors

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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