Box Plots¶

Box plots are ideal for statistical summaries, outlier detection, and comparing distributions across groups. Rekha’s box plots show quartiles, medians, and outliers with clean, informative visualizations.

Basic Usage¶

import rekha as rk
import pandas as pd
import numpy as np

# Simple box plot
data = np.random.normal(50, 15, 1000)
df = pd.DataFrame({'values': data})

fig = rk.box(df, y='values', title='Value Distribution')
fig.show()

Examples Gallery¶

Basic Box Plot¶

Single variable distribution summary:

import rekha as rk
from examples.utils import get_iris

df = get_iris()

fig = rk.box(
    data=df,
    y='sepal_length',
    title='Sepal Length Distribution'
)

Full example

Grouped Box Plot¶

Compare distributions across categories:

fig = rk.box(
    data=df,
    x='species',
    y='petal_length',
    title='Petal Length by Species',
    labels={'species': 'Species', 'petal_length': 'Petal Length (cm)'}
)

Full example

Parameters¶

See the API Reference for complete parameter documentation.

What Box Plots Show¶

Box: Interquartile range (25th to 75th percentile)
Line in box: Median (50th percentile)
Whiskers: Extend to 1.5 × IQR from box edges
Points: Outliers beyond whiskers