Similar to a density plot, it visualizes how numerical data is distributed.
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| import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("iris")
sns.set(rc={"figure.figsize": (12, 8)})
sns.histplot(data=df["sepal_length"], binwidth=0.5)
plt.show()
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- Density Plot — Visualize distribution with a smooth curve
- Box Plot — Compare median, quartiles, and outliers
- ECDF — Check the proportion below a threshold via cumulative ratio