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I can create beatiful scatter plot with seaborns regplot, obtain the right level of transparency through the scatter_kws as in
sns.regplot(x='logAssets', y='logLTIFR', lowess=True, data=df, scatter_kws={'alpha':0.15}, line_kws={'color': 'red'}) and obtain this:
Is there an option in a seaborn pairplot to tweak transparency?
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To control the transparency of plots, we can use the alpha argument within the plot function. By default, its value is 1. The value of this parameter ranges from 0 to 1, with the plot getting more transparent and invisible as the value reaches 0.
seaborn.pairplot() To plot multiple pairwise bivariate distributions in a dataset, you can use the pairplot() function. This shows the relationship for (n, 2) combination of variable in a DataFrame as a matrix of plots and the diagonal plots are the univariate plots.
Ok I was very close to the solution. Seaborn pairplots have plot_kws that takes as arguments a dictionary of the kind of modifications you would do in a regplot. The following line is exactly what I needed:
g = sns.pairplot(df, kind='reg', plot_kws={'line_kws':{'color':'red'}, 'scatter_kws': {'alpha': 0.1}}) And this is the outcome:
If you don't do the regression but just the scatter plot (kind='scatter'), within plot keywords you don't have to do the division between line and scatter keywords:
g = sns.pairplot(df, kind='scatter', plot_kws={'alpha':0.1}) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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