From the course: Python Data Visualization: Create Impactful Visuals, Animations, and Dashboards by Pearson

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Python data visualization: Summary

Python data visualization: Summary - Python Tutorial

From the course: Python Data Visualization: Create Impactful Visuals, Animations, and Dashboards by Pearson

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Python data visualization: Summary

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Thank you for joining us in our exploration of Python data visualization. Over the course of the last few hours, we covered a huge amount of ground and the entire lifecycle of a visualization, from how best to design and create a visualization, how to leverage human perception, how to clean our data using pandas, and how to generate both static and interactive visualizations. In the case of static visualizations, we explored in detail the Matplotlib package and the Seaborn statistical visualization package as well. While on the interactive end, we looked in detail at how best to leverage the functionality made available to us by Bokeh and Plotly, two of the most popular JavaScript-based, interactive visualization packages for Python. Thank you again. I hope you enjoyed this course and you now have a new set of tools in your toolkit that you can leverage in your day-to-day work. I look forward to seeing what visualizations you're going to create, and please feel free to reach out to me…

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