Plus, it will act as an engine for our dashboard by processing data and passing it to the charts in the summarized form. Its main feature is interactivity and ease of use. This pivot table will handle all the data-related calculations: aggregating, filtering, and sorting data. You can use simply Jupyter Notebook as well Hopefully, the resulting notebook template will help everyone who works with data to answer important domain-specific questions and present data analysis insights in a comprehensible form.Īs a data sample, we’ll use the World Happiness Report from Kaggle to explore tendencies in data, both spatial and temporal. That’s why, without any extensions added, we will establish a working environment for reporting within Jupyter Notebook in the minimum time. I believe data reporting should be comprehensible and take less time than the analysis itself. The guide will take minimum time and steps to complete. In this tutorial, I’d like to show how to empower the exploratory phase of your project with two interactive data visualization tools that are available as JavaScript libraries. Besides, it’s a perfect web-based environment for performing exploratory analysis. Rich interactive computing experience is what I love most about Jupyter Notebook.
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