Box Plots & Outlier Detection

Why Box Plots?

Histograms hide exact percentiles. Box plots show the 5-number summary visually:

1. Minimum (Q1 - 1.5 * IQR)
2. Q1 (25th percentile)
3. Median (50th percentile)
4. Q3 (75th percentile)
5. Maximum (Q3 + 1.5 * IQR)

Outliers

Any points outside the "whiskers" (min/max) are plotted as individual dots. These are statistical outliers.

Violin Plots

A combination of a box plot and a KDE (density) plot. It shows the shape of the distribution in addition to the summary statistics.

import seaborn as sns
sns.boxplot(x='category', y='value', data=df)
sns.violinplot(x='category', y='value', data=df)

Data Science Use: Box plots are step 1 in anomaly detection (fraud, server crashes, sensor errors).