pandas-pretty-display 0.3.5

A package to make pandas DataFrames display beautifully in Jupyter notebooks

Pandas Pretty Display

A simple Python package to make your pandas DataFrames look beautiful in Jupyter notebooks with alternating colors and improved formatting. Now with support for styled markdown headers!

Installation

You can install the package via pip:

pip install pandas-pretty-display

Usage

DataFrame Styling

from pandas_pretty_display import style_dataframe
import pandas as pd

# Create or load your DataFrame
df = pd.DataFrame(...)

# Apply the styling
style_dataframe()

# Display your DataFrame - it will now have the pretty styling
display(df)

Markdown Header Styling

from pandas_pretty_display import style_notebook

# Apply all styling at once (DataFrame + header styling)
style_notebook()

# Now you can use regular markdown headers in markdown cells:
# # Level 1 Header
# ## Level 2 Header
# ### Level 3 Header

All markdown headers in your notebook will automatically be styled with red borders, gold backgrounds, and dark blue text.

Individual Styling Functions

You can also apply just the header styling without the DataFrame styling:

from pandas_pretty_display import style_headers

# Apply only header styling
style_headers()

For backward compatibility, the package still includes functions to create headers directly in code cells:

from pandas_pretty_display import header1, header2, header3

# Create headers in code cells
header1("This is a Level 1 Header")
header2("This is a Level 2 Header")
header3("This is a Level 3 Header")

Features

DataFrame Styling

• Alternating gold and light blue row colors
• Black text in table cells
• Red text in table headers
• Black borders around cells
• 18px font size
• Full-width container
• Scrollable output up to 1000px height

Header Styling

• Level 1, 2, and 3 headers with consistent styling
• Red border (thickness varies by level)
• Gold background (#ffcc00)
• Dark blue text (#000080)
• Responsive sizing based on header level
• Rounded corners for modern appearance

Requirements

• Python >= 3.6
• pandas >= 1.0.0
• IPython >= 7.0.0

License

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