Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms

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Helen Wall

2:02:36

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01 - Introduction

01 - Introducing the power of Python in Excel.mp4

00:36

02 - What you should know.mp4

00:11

03 - Enabling Python in Excel.mp4

01:19

02 - 1. Introducing Excel and Python

01 - Breaking down Excel and Python processes.mp4

01:48

02 - Leveraging Power Query.mp4

06:32

03 - Using the PY Excel function.mp4

03:44

04 - Using the XL Excel function and Python variables.mp4

04:23

05 - Determining calculation order.mp4

04:31

06 - Importing Python libraries into Excel.mp4

03:20

07 - Managing errors.mp4

04:14

08 - Working with Python objects.mp4

07:03

09 - Transforming DataFrame objects.mp4

07:41

10 - Challenge Creating table objects in Excel.mp4

02:15

11 - Solution Creating table objects in Excel.mp4

03:09

03 - 2. Applying Algorithms

01 - Introducing AI and machine learning algorithms.mp4

02:32

02 - Determining trends for linear regression with Excel functions.mp4

05:04

03 - Leveraging Excel Solver for logistic regression.mp4

02:49

04 - Determining trends for logistic regression with Python code.mp4

04:17

05 - Grouping data with hierarchical clustering.mp4

05:05

06 - Grouping data with the K-Means algorithm.mp4

02:51

07 - Determining anomalies with anomaly detection algorithms.mp4

06:43

08 - Challenge Running algorithms with Python in Excel.mp4

01:05

09 - Solution Running algorithms with Python in Excel.mp4

05:10

04 - 3. Creating Visuals

01 - Visualizing data.mp4

01:35

02 - Leveraging Excel line charts.mp4

03:58

03 - Leveraging Excel scatter plots.mp4

05:21

04 - Configuring Python in Excel with dynamic parameters.mp4

04:32

05 - Creating Python visuals.mp4

02:13

06 - Visualizing hierarchical clustering with dendrograms.mp4

06:43

07 - Breaking down time series models into components.mp4

05:29

08 - Challenge Comparing time series components to anomalies.mp4

00:50

09 - Solution Comparing time series components to anomalies.mp4

04:56

05 - Conclusion

01 - Continuing on with Python in Excel.mp4

00:37

Description

Excel is a powerful tool for data and business analysis, and Python is one of the world’s most popular and dynamic programming languages. Python in Excel works as a sandbox environment. It enables developers and business users to test small parts of code by creating visuals and running algorithms on existing data. In this course, data analytics and business analysis expert Helen Wall focuses on how Python can expand the existing capabilities of Excel. Explore the process and framework of setting up Python to create DataFrame objects and other outputs in Excel. Dive into ways you can use these outputs and objects in custom data visualizations and algorithms that Excel does not have natively, but which Python can create with code. This course highlights ways you can harness the strengths of both Excel and Python in one interface.

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Python

Helen Wall

Instructor's Courses

Follow me to see my latest published content on data science, analytics, and visualization! Aficionado of Power BI, AWS, Tableau, and Excel (including Power Query), and currently diving deep into the world of Python, R, and AI (including machine learning). Designer and developer of business intelligence dashboards and visualizations supporting many business functions and industries.

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