Get Started with Python in Excel

Get Started with Python in Excel

Use Python to process and analyze data without leaving your spreadsheet.

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About this course

Python in Excel seamlessly integrates the power of Python analytics into the Excel environment, enabling you to harness Python code to manipulate and analyze data within Excel. In this course, you will learn how to integrate Python, one of the most versatile and in-demand programming languages, with Microsoft Excel, the industry-standard spreadsheet tool. Discover how to leverage Python's powerful libraries and scripting capabilities to supercharge your data manipulation, visualization, and analysis tasks within Excel. Whether you're a data analyst, financial professional, or business enthusiast, this course empowers you to harness the power of Python in Excel for more efficient and impactful data analysis.

By the end of this hands-on course, you’ll understand:

  • How to embed Python code in your Excel sheet
  • What Python packages are and how they work in Excel
  • Data manipulation, analysis and visualization techniques with Python
  • Current limitations of the Beta version of Python in Excel
  • How to import data

And you’ll be able to:

  • Leverage pandas, a popular Python package for data manipulation
  • Utilize Python functionality to clean and transform messy data
  • Gain insight into the most recent Python in Excel capabilities to explore how they can be leveraged for generating visualizations and conducting analyses within an Excel workbook

This training is for you because…

  • You’re someone who enjoys studying data
  • You work with data in any form, but mostly tabular.
  • You want to become a skilled data analyst using Python.

Prerequisites  

Recommended preparation

The following will be helpful to review prior to the course, but are not required:

About the instructor

Albert DeFusco is a data scientist working to improve the tools used by data scientists and does some development, analytics, DevOps, and predictive modeling and MLOps. He specializes in scientific and high performance computing and has taught Data Science topics such as machine learning and big data processing. Prior to joining Anaconda, he completed his Ph.D. in theoretical chemistry at the University of Pittsburgh in 2008 on quantum mechanic interactions between water molecules. Afterwards, Albert was a Research Professor in the Center for Simulation and Modeling at the University of Pittsburgh where he oversaw the administration of the high-performance computing cluster and assisted researchers in its utilization.

Questions? Issues? Contact [email protected].

Curriculum00:58:27

  • Overview
  • Course Overview 00:00:57
  • Python in Excel
  • Python in Excel 00:03:37
  • Using the PY Function in Excel 00:05:51
  • Anaconda Distribution and Python Packages 00:01:39
  • Data Processing with pandas 00:01:21
  • Python in Excel Best Practices 00:03:28
  • Clean and Join Data 00:08:00
  • Clean and Join Data Continued 00:06:50
  • Data Processing 00:09:47
  • pandas and Data Cleaning 00:09:06
  • Visualization with Python 00:01:13
  • Statistical Analysis 00:06:06
  • Conclusion
  • Conclusion 00:00:32
  • End of Course Survey

About this course

Python in Excel seamlessly integrates the power of Python analytics into the Excel environment, enabling you to harness Python code to manipulate and analyze data within Excel. In this course, you will learn how to integrate Python, one of the most versatile and in-demand programming languages, with Microsoft Excel, the industry-standard spreadsheet tool. Discover how to leverage Python's powerful libraries and scripting capabilities to supercharge your data manipulation, visualization, and analysis tasks within Excel. Whether you're a data analyst, financial professional, or business enthusiast, this course empowers you to harness the power of Python in Excel for more efficient and impactful data analysis.

By the end of this hands-on course, you’ll understand:

  • How to embed Python code in your Excel sheet
  • What Python packages are and how they work in Excel
  • Data manipulation, analysis and visualization techniques with Python
  • Current limitations of the Beta version of Python in Excel
  • How to import data

And you’ll be able to:

  • Leverage pandas, a popular Python package for data manipulation
  • Utilize Python functionality to clean and transform messy data
  • Gain insight into the most recent Python in Excel capabilities to explore how they can be leveraged for generating visualizations and conducting analyses within an Excel workbook

This training is for you because…

  • You’re someone who enjoys studying data
  • You work with data in any form, but mostly tabular.
  • You want to become a skilled data analyst using Python.

Prerequisites  

Recommended preparation

The following will be helpful to review prior to the course, but are not required:

About the instructor

Albert DeFusco is a data scientist working to improve the tools used by data scientists and does some development, analytics, DevOps, and predictive modeling and MLOps. He specializes in scientific and high performance computing and has taught Data Science topics such as machine learning and big data processing. Prior to joining Anaconda, he completed his Ph.D. in theoretical chemistry at the University of Pittsburgh in 2008 on quantum mechanic interactions between water molecules. Afterwards, Albert was a Research Professor in the Center for Simulation and Modeling at the University of Pittsburgh where he oversaw the administration of the high-performance computing cluster and assisted researchers in its utilization.

Questions? Issues? Contact [email protected].

Curriculum00:58:27

  • Overview
  • Course Overview 00:00:57
  • Python in Excel
  • Python in Excel 00:03:37
  • Using the PY Function in Excel 00:05:51
  • Anaconda Distribution and Python Packages 00:01:39
  • Data Processing with pandas 00:01:21
  • Python in Excel Best Practices 00:03:28
  • Clean and Join Data 00:08:00
  • Clean and Join Data Continued 00:06:50
  • Data Processing 00:09:47
  • pandas and Data Cleaning 00:09:06
  • Visualization with Python 00:01:13
  • Statistical Analysis 00:06:06
  • Conclusion
  • Conclusion 00:00:32
  • End of Course Survey