In this article, I showed what are the violin plots, how to interpret them and what their advantages are over the boxplots. One last remark worth making is that the boxplots don’t adapt as long as the quartiles
The distribution plot of class label generally performs as a combination of probability density function and Histogram in a single figure. Here the univariate analysis, how we are going to do the univariate analysis by executing these commands.sns.distplot( iris["SepalLengthCm"], bins=20 ) ...
more on this, in the next section of visualizations where we look at the distribution of ticket fare and survived column. 3c. Fare and Survived # KernelDensity Plot fig = .figure(figsize=(15,8),) ax=snskdeplot(train.loc[(train['Survived] == 0),Fare'] , color='gray',shade...