Seaborn Heatmap - How to Visualise Correlations and Data With Heatmaps in Python
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- Опубликовано: 22 авг 2024
- Heatmaps are a great way to visualise tabular data. They allow us to identify trends, spot outliers and understand the range of our data. In this week's video, we are going to see how to visualise data using a Seaborn Heatmap.
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Very informative video ...just a suggestion , Subtitles should be made available as your accent is pretty strong for non english speakers to understand
Great job! Very simple, quick and effective explanation
A masterpiece video! makes it easy to grasp the concept
Great job! Thank you so much Sir for making such awesome video
Thanks!
@@AndyMcDonald42 🙏🙏🙏
An excellent and straightforward explanation😁
Thanks! 😃
Heatmaps for correlations: starts at 3:39
Brilliant video - so clear and easy to follow. Thank you :)
Thank you was very helpful🙏🏼
Thanks for this knowledge
Thanks for the explanation
Is there somewhere I could download the .csv so I can work alongside the video with you? Thanks.
Great one, how do you get the p values out?
Hello ! Is it possible to use this for corrected cover area (CCA) for overlap in an umbrella review?
Where can I get the Data Xeek well file because I keep getting errors
Good One sir..
Thanks 🙂
Hello there, my graduation project is about predicting sonic and density log using ANN and i don't know what to start with can you help me please
It depends on what the purpose of the prediction is. Are you trying to predict because the curves are damaged or missing.
I’m putting out a video next week that looks at Random Forest for regression which may be of interest.
I would recommend checking out my medium page which has articles covering how to QC well data prior to ML.
medium.com/@andymcdonaldgeo
Good luck with your project.
@@AndyMcDonald42 actually I'm trying to generate a synthetic log I mean for a well that is not having logging due to cost saving using logging data of the nearby wells
I can send you the paper of the work through email