general_horizontal_bar_plot

Horizontal bar plot comparing metrics for each category, with optional group-based coloring and legends.

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📥 Arguments

Name	Type	Required	Description
df	pd.DataFrame	✅	DataFrame with category_column and metric columns.
category_column	str	✅	Column used for y-axis labels.
category_group_key	str	❌	Column used for group labels (used for colour and legend).
group_color_map	Dict[str, str]	❌	Mapping of group label → colour.
figsize	tuple	❌	Figure size. Default: (12, 7).
xlabel	str	❌	Label for x-axis.
ylabel	str	❌	Label for y-axis.
title	str	❌	Title of the plot.
legend_loc	str	❌	Legend location. Default: ‘upper right’.
bar_height	float	❌	Height of the bars. Default: 0.35.
color_map	Dict[str, str]	❌	Mapping of metrics to colours.
style_map	Dict[str, str]	❌	Mapping of metrics to hatch styles.
put_legend	bool	❌	Whether to display a legend. Default: True.
fontsize	float	❌	Base font size for axis labels, tick labels, title, legend, and annotations. Default: 12.
save	str	❌	Filename base to save PNG and PDF.
ax	matplotlib.axes.Axes	❌	Optional matplotlib Axes object.

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📦 Example Output

Click to show example code

import pandas as pd
import matplotlib.pyplot as plt
from swizz import plot

# 1) Prepare the data as a DataFrame
df = pd.DataFrame({
    "Category": ["64", "128", "256", "512", "1024", "2048", "0.95", "0.99", "0.995"],
    "rate": [0.7835051, 0.8800000, 0.9368421,
             0.8913044, 0.8800000, 0.8736842,
             0.8297873, 0.8800000, 0.7234042],
    "Group": ["Hidden size", "Hidden size", "Hidden size", "Batch size", "Batch size", "Batch size", "Discount factor", "Discount factor", "Discount factor"],
})

# 3) Assign one color per group
group_color_map = {
    "Discount factor": "#41047F",
    "Batch size":      "#7464AE",
    "Hidden size":     "#A3A1CB",
}

# 4) Plot using the new function
fig, ax = plot(
    "general_horizontal_bar_plot",
    df=df,
    category_column="Category",
    category_group_key="Group",
    group_color_map=group_color_map,
    xlabel="Lone-wolf capture rate",
    ylabel="",
    title="",
    bar_height=0.4,
    style_map={"rate": ""},
    put_legend=True,
    save="general_barh_plot",
    legend_loc="upper left",
)

plt.show()