Seaborn with example
📊 Seaborn in Python
Seaborn is a statistical data visualization library built on top of Matplotlib. It provides high-level interface for creating attractive and informative charts.
1. Installation
2. Importing Seaborn
3. Load Example Dataset
Seaborn comes with built-in datasets:
| total_bill | tip | sex | smoker | day | time | size |
|---|---|---|---|---|---|---|
| 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
4. Simple Scatter Plot
-
hue→ color by category -
data→ dataset -
x,y→ columns
5. Line Plot
6. Histogram / Distribution Plot
-
kde=True→ plots Kernel Density Estimate (smooth curve)
7. Box Plot
Shows distribution and outliers.
8. Bar Plot
Displays aggregate statistics.
9. Pair Plot
Visualizes relationships between all numerical columns.
10. Heatmap
Useful for correlation matrices.
🧠 Summary Table
| Plot Type | Function | Notes |
|---|---|---|
| Scatter Plot | scatterplot() |
Relationship between two variables |
| Line Plot | lineplot() |
Trends over numeric x-axis |
| Histogram | histplot() |
Distribution of numeric data |
| Box Plot | boxplot() |
Distribution and outliers |
| Bar Plot | barplot() |
Mean values for categories |
| Pair Plot | pairplot() |
Scatter & distribution matrix |
| Heatmap | heatmap() |
Correlation or 2D data matrix |
