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Python Data Analysis Tips - Seaborn how to choose your diverging palette color generator

Updated: Aug 10



free python data analysis tips in seaborn choose color palette diverging palette in seaborn
Seaborn's Choose Color Palette in Heatmap

Seaborn is an incredible power data analysis tool we have access to in Python. By default seaborn comes with some of the nicest plots in Python. Seaborn is the most beautiful analytic tool in Python.


However, we can go beyond the defaults and create some truly artful analytical plots. With Seaborn, we have the ability to tailor the color palette for our analysis.


In situations where we have both positive and negative correlations it's nice to be able to use seaborn's choose diverging palette to allow us to experiment with different combinations of the arguments, we can pass to Seaborn's diverging palette color brewer.



When there are positive and negative correlations we would want use the diverging palette to emphasize both highly positive and highly negative correlations. We might also want features we close to no correlation to show at a lighter color, expanding the light center of our continuous palette. Maybe we'd like the colors to be both shaded darker and of a higher saturation to fit our color palette.


All of these visual formattings do make our Seaborn plots look prettier and more unique. But they also enable the end user to better understand the goal of our analysis. By highlighting the strong positive and negative correlations in different colors and turning down the coloring of correlations under a threshold we as able to highlight what's important and reduce the emphasis on those that aren't important.



Allowing someone who knows nothing about data to understand exactly what they need from our analysis. Being able to communicate your analysis without words and just in highlighting and emphasizing what needs to be understood is what separates amateurs from expert Data Analysts.








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