Kernel Density Estimation
Explore how to use Kernel Density Estimation in Python Altair to model data distributions. Learn to apply the transform_density() method for creating smooth visualizations, enhancing insights into data patterns.
We'll cover the following...
We'll cover the following...
Kernel density estimation (KDE) is a statistical method used to estimate the probability density function of a random variable based on a set of observed data points. In simpler terms, KDE creates a smooth curve approximating the distribution of a dataset, which can help us better understand ...