Density Plot
A density plot is a data visualization technique that estimates the probability density function of a continuous variable, typically using kernel density estimation (KDE). It displays the distribution of data points as a smooth curve, highlighting peaks, valleys, and overall shape without the binning artifacts of histograms. This makes it useful for visualizing the underlying distribution of data, especially for large datasets or when comparing multiple distributions.
Developers should learn density plots when working with data analysis, machine learning, or statistical modeling to explore and communicate data distributions effectively. They are particularly valuable for identifying patterns like multimodality, skewness, or outliers in continuous data, such as in exploratory data analysis (EDA) for datasets like user engagement metrics or sensor readings. Use cases include comparing feature distributions across classes in classification tasks or visualizing the spread of model residuals.