seaborn

**Seaborn: Statistical Data Visualization** **Overview** Seaborn is a Python visualization library based on **matplotlib**. It provides a high-level interface for drawing attractive and informative statistical graphics. **Why use Seaborn?** - **Better Defaults**: Matplotlib's default plots look "scientific" (ugly). Seaborn's defaults look modern and clean. - **Less Code**: It handles complex aggregations automatically. **Key Plots** **1. Distplot / Histplot** Visualize the distribution of a variable. `sns.histplot(data=df, x="flipper_length_mm")` **2. Pairplot** Plot pairwise relationships in a dataset (Scatter Matrix). `sns.pairplot(penguins, hue="species")` *This single line generates a grid of all variables vs all variables, colored by species.* **3. Heatmap** Great for Correlation Matrices. `sns.heatmap(df.corr(), annot=True)` **4. Box / Violin Plot** Visualize statistical distributions across categories. `sns.violinplot(x="day", y="total_bill", data=tips)` **Integration** Seaborn integrates tightly with **Pandas** DataFrames. You pass the dataframe directly, and use column names as arguments.