At a Glance

Uncover the hidden secrets within FIFA World Cup data using the PygWalker Python library, which generates dynamic dashboards and reports within Jupyter Notebook. This innovative tool brings the power of a Tableau-like user interface to your Jupyter Notebook environment. Bid farewell to the constraints of traditional data analysis workflows and embrace the seamless integration of PyGWalker's user interface in your notebooks. PyGWalker appears to offer data scientists a user-friendly interface for tasks such as visualization, data cleaning, annotation, and even natural language queries.

Unlock the full potential of PyGWalker, a Python library for exploratory data analysis with visualization. Connect and easily import your data sets, create stunning interactive visualisations, and gain valuable insights from your data.

With PyGWalker, you can create dynamic dashboards and reports right within your Jupyter Notebook, all while harnessing the user-friendly features reminiscent of Tableau's visual analytics platform and interface. Say hello to an intuitive and efficient workflow as you explore and communicate your data-driven stories with the ease and flexibility that PyGWalker provides.

A look at the project

After completing this guided project, you will be able to:

Create interactive visualisations: Learn how to use PyGWalker's capabilities to create interactive visualisations. Understand different chart types and customisation options, and learn how to create compelling visual representations of your data.
Build dynamic dashboards and reports: Discover how to assemble interactive dashboards and reports within PyGWalker. Learn how to combine multiple visualisations, add interactivity, and effectively present your data-driven insights.
Perform advanced data manipulation and transformation: Explore advanced data manipulation and transformation techniques using PyGWalker. Learn how to handle missing data, perform calculations, and apply complex data transformations within the PyGWalker environment.
Collaborate and share: Understand how to collaborate with others using PyGWalker. Learn how to share notebooks and dashboards, export visualisations, and effectively communicate your findings to stakeholders.

What you'll need

To complete this guided project, you need a basic understanding of machine learning principles and topics . This project uses Python primarily. Although Python skills are recommended prerequisites so that you can understand the code, no prior experience is required because this guided project is designed for beginners.

Offered By: IBMSkillsNetwork

PyGWalker: Unlocking the secrets of FIFA World Cup data

At a Glance

A look at the project

What you'll need

Offered By: IBMSkillsNetwork

PyGWalker: Unlocking the secrets of FIFA World Cup data

At a Glance

A look at the project

What you'll need

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