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 stay the same. We can modify the data in a way that the quartiles ...
a histogram with a kernel density estimate (KDE) a boxplot a violin plot We will use this function for inspecting the randomly created samples. def plot_comparison(x, title): fig, ax = plt.subplots(3, 1, sharex=True) sns.distplot(x, ax=ax[0]) ax[0].set_title('Histogram + KDE'...
Each Flowers measurement in the data set has equal values (each 50) as we saw the “shape ()” method. Violin plot The violin plot generally performs like a combination of Boxplot and Kernel Density Estimation (KDE). It shows the distribution of numerical/ quantitative data of the cate...