bar plot

abutils provides functionality for creating bar plots of categorical data. The bar plot function is flexible and can handle both raw counts and frequency distributions, with options for highlighting specific categories, customizing colors, and adding legends.

plotting function	description
abutils.plots.bar()	creates bar plots for categorical data with optional grouping

examples

basic bar plot

Bar plots can be created using either raw values or named columns in a DataFrame. If only x-values are provided, the function counts occurrences automatically.

import abutils

# create a simple bar plot from a list of categories
categories = ['A', 'B', 'A', 'C', 'B', 'A', 'D', 'A', 'B', 'C']
ax = abutils.plots.bar(x=categories, figsize=[8, 5])

stacked bar plot with hue

Adding a hue parameter creates a stacked bar plot where each segment represents a hue category.

import abutils
import pandas as pd

# create a DataFrame with categories and subcategories
data = pd.DataFrame({
    'gene': ['IGHV1-2', 'IGHV1-2', 'IGHV1-18', 'IGHV3-23', 'IGHV3-23', 'IGHV4-34'],
    'isotype': ['IgG', 'IgM', 'IgG', 'IgA', 'IgG', 'IgM']
})

# create a stacked bar plot
ax = abutils.plots.bar(
    x='gene',
    hue='isotype',
    data=data,
    palette={'IgG': 'darkred', 'IgM': 'navy', 'IgA': 'forestgreen'},
    figsize=[10, 5]
)

normalized frequency bar plot

Bar plots can show normalized frequencies instead of raw counts, and can be displayed horizontally.

import abutils
import pandas as pd

# create a DataFrame with counts
data = pd.DataFrame({
    'category': ['A', 'B', 'C', 'D', 'E'],
    'count': [23, 45, 12, 67, 8]
})

# create a horizontal bar plot with normalized frequencies
ax = abutils.plots.bar(
    x='category',
    y='count',
    data=data,
    normalize=True,
    orientation='horizontal',
    color='steelblue',
    xlabel='Frequency (%)',
    ylabel='Category',
    figsize=[6, 8]
)

highlighting specific categories

You can highlight specific categories to draw attention to them.

import abutils
import pandas as pd

# create a DataFrame with categories and values
data = pd.DataFrame({
    'gene': ['IGHV1-2', 'IGHV1-18', 'IGHV3-23', 'IGHV3-30', 'IGHV4-34', 'IGHV5-51'],
    'frequency': [0.15, 0.08, 0.25, 0.12, 0.30, 0.10]
})

# create a bar plot with highlighted categories
ax = abutils.plots.bar(
    x='gene',
    y='frequency',
    data=data,
    highlight=['IGHV3-23', 'IGHV4-34'],
    highlight_color='darkred',
    alt_color='lightgray',
    ylabel='Frequency',
    figsize=[10, 5]
)

api

abutils.plots.bar()