Stacked Bar Plot

plot_stacked_bar_repel() creates stacked bar plots with intelligent label placement for visualizing cell type composition.

Preparing data

Create a synthetic observation DataFrame:

import pandas as pd
import numpy as np

np.random.seed(42)
n = 1000
obs_df = pd.DataFrame({
    'cell_type': np.random.choice(
        ['B cell', 'T cell', 'Monocyte', 'NK', 'DC'],
        size=n, p=[0.3, 0.3, 0.2, 0.1, 0.1]
    ),
    'sample': np.random.choice(
        ['Sample_1', 'Sample_2', 'Sample_3', 'Sample_4'],
        size=n
    ),
})

Relative composition

Show proportions per cell type:

from sjanpy.pl import plot_stacked_bar_repel

plot_stacked_bar_repel(
    obs_df,
    group_col='sample',
    type_col='cell_type',
    mode='relative',
    label_content='percentage',
)

Small slices are automatically labeled with leader lines using adjustText to avoid overlap.

Absolute counts

Switch to raw counts with optional log scale:

plot_stacked_bar_repel(
    obs_df,
    group_col='sample',
    type_col='cell_type',
    mode='absolute',
    log_scale=True,
    label_content='count',
)

Label options

The label_content parameter controls what appears on each bar segment:

'percentage': show percentage (default)
'count': show raw count
'both': show count and percentage

Adjust min_label_threshold to control when labels switch from inline to leader-line style (default: 0.03 = 3%).

Saving

plot_stacked_bar_repel(
    obs_df,
    group_col='sample',
    type_col='cell_type',
    save_path='barplot.pdf',
)