From the course: Data Analysis with Python and Pandas

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Key takeaways

Key takeaways

From the course: Data Analysis with Python and Pandas

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Key takeaways

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- [Instructor] Okay, so by this point we're able to create several common chart types in Python, and we're also able to format them to a reasonable extent. As I mentioned in the last lesson, there is still a lot more to learn in this field if you really want to be able to fully fine-tune your visuals. But hopefully you feel comfortable using them for exploring your data within your Jupyter Notebooks. Sometimes I will still take a Pandas DataFrame and move it into a tool like Excel or Tableau, where the visualization options are very easy to customize, with a lot less manual specification than we see in a library like Matplotlib. The fact of the matter is, is that a library like Matplotlib has a very, very steep learning curve compared to tools like Power BI, Tableau, or Excel. But that learning curve also comes at the benefit of extreme customization. But for what we've learned here, we're just able to create reasonably complex charts with decent formatting. The plot method is what…

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