From the course: Data Visualization with Matplotlib and Seaborn

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Setting expectations

Setting expectations - Python Tutorial

From the course: Data Visualization with Matplotlib and Seaborn

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Setting expectations

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- [Instructor] Before we dive into the course, I want to set some expectations to make sure this course is a good fit for you. This course covers the core functionality for Matplotlib and Seaborn. We'll cover chart types, common customization options, and best practices for visualizing and analyzing data. Matplotlib and Seaborn are very big libraries, so we'll give the tools to use the official documentation to apply any customization option not covered in the course. If we tried to cover all the customization options, this course would be 100 hours. We'll focus on creating static visuals and dashboards. Interactive data visualization with Python will be covered in a separate course. Yes, there's another library for that. We'll use Jupyter Notebooks as our primary coding environment. Jupyter Notebooks are free to use in the industry standard for conducting data analysis with Python. We'll also briefly introduce Google Colab as an alternative cloud-based environment as well…

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