barinbar 0.1.0

Generate a cool bar in bar chart

barinbar

A Python package for creating bar-in-bar charts using Matplotlib.

Inspiration

This package was created in response to discussions and implementations of bar-in-bar charts across different platforms:

• Original LinkedIn Post by Colin Tomb: Link
• Tableau Implementation (Kevin Flerlage, Sebastine Amede, Darragh Murray, Brittany Rosenau): Blog Post
• R Implementation (Brian Julius): Post
• Deneb Implementation (Daniel Marsh-Patrick): Blog Post

This package aims to provide a straightforward Python (Matplotlib) alternative.

Installation

pip install barinbar

(Note: This assumes the package is published on PyPI.)

Development Setup (using Poetry)

If you want to contribute or run the code locally:

1. Install Poetry: Follow the instructions on the official Poetry website.
2. Clone the repository:

   git clone <your-repo-url>
   cd barinbar
   

3. Install dependencies: This command creates a virtual environment and installs all dependencies (including development tools).

   poetry install --all-extras
   

4. Activate the virtual environment:

   poetry shell
   

5. Now you can run scripts or linters, e.g., python barinbar/plot.py (adjust path if needed).

Requirements

• Python >= 3.10
• matplotlib
• pandas

Usage

The main function is plot_bar_in_bar. It requires a pandas DataFrame structured with columns for the main category, sub-category, segment value, and total category value.

import pandas as pd
from barinbar.plot import plot_bar_in_bar, BarinbarStyle
from matplotlib.cm import get_cmap

# 1. Prepare your data
data = {
    "Region": ["West"]*3 + ["East"]*3 + ["Central"]*3 + ["South"]*3,
    "Segment": ["Consumer", "Corporate", "Home Office"] * 4,
    "Revenue": [364, 232, 143, 357, 204, 131, 254, 158, 91, 196, 122, 74],
}
revenues = pd.DataFrame(data)

# Calculate totals per main category
region_totals = revenues.groupby("Region")["Revenue"].sum().reset_index()
region_totals = region_totals.rename(columns={"Revenue": "TotalRevenue"})

# Merge totals back into the main DataFrame
revenues = pd.merge(revenues, region_totals, on="Region")

# Define category orders (optional but recommended for consistent plotting)
region_order = ["West", "East", "Central", "South"]
segment_order = ["Consumer", "Corporate", "Home Office"]
revenues["Region"] = pd.Categorical(revenues["Region"], categories=region_order, ordered=True)
revenues["Segment"] = pd.Categorical(revenues["Segment"], categories=segment_order, ordered=True)
revenues = revenues.sort_values(by=["Region", "Segment"])

# 2. Define Styling (Optional)
# Use default colors or specify your own
default_color_palette = get_cmap("Dark2")
custom_colors = {
    "Consumer": default_color_palette(0),
    "Corporate": default_color_palette(1),
    "Home Office": default_color_palette(2),
}
my_style = BarinbarStyle(
    fontname='serif', # Example: Use a serif font
    colors=custom_colors,
    figsize=(12, 7) # Example: Adjust figure size
)

# 3. Plot the chart
plot_bar_in_bar(
    df=revenues,
    category_col="Region",
    subcategory_col="Segment",
    value_col="Revenue",
    total_col="TotalRevenue",
    title="Revenue by Region and Segment",
    style=my_style, # Pass the style object
)

This will generate and display the bar-in-bar chart.

Customization

You can customize the appearance of the chart by creating an instance of the BarinbarStyle dataclass and modifying its attributes (e.g., figsize, colors, fontname, fontsize, background_color). Pass this style object to the plot_bar_in_bar function.

from barinbar.plot import BarinbarStyle

custom_style = BarinbarStyle(
    background_color="#F0F0F0",
    figsize=(10, 6),
    fontsize=18,
    small_fontsize=11,
    fontname="Arial",
    colors={"Consumer": "blue", "Corporate": "green", "Home Office": "red"}
)

# ... then pass `style=custom_style` to the plot function

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

• Daniel Vecera - [e-mail]