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Plot With pandas: Python Data Visualization Basics (Summary)
In this course, you’ve learned how to start visualizing your dataset using Python and the pandas library. You’ve seen how some basic plots can give you insight into your data and guide your analysis.
In this course, you learned how to:
- Get an overview of your dataset’s distribution with a histogram
- Discover correlation with a scatter plot
- Analyze categories with bar plots and their ratios with pie plots
- Determine which plot is most suited to your current task
Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.
00:00 Summary. Well done! You’ve made it to the end of this course. In it, you’ve learned how to start visualizing your dataset using Python and the pandas library.
00:12 You’ve seen how some basic plots can give you an insight into your data and guide your analysis. In this course, you learned how to get an overview of your dataset’s distribution with a histogram, discover correlation with a scatter plot, analyze categories with bar plots and their ratios with pie plots, and determine which plot is most suited for your current task.
00:36
Using .plot() and a small DataFrame, you’ve discovered quite a few possibilities for providing a picture of your data. You’re now ready to build on this knowledge and experience and discover even more sophisticated visualizations. We hope you’ve enjoyed this course, and don’t forget to check out the related courses to deepen your understanding of statistics, data science libraries, and Python. We hope we’ll see you again soon at realpython.com.
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