pandas-tibble 0.2.0

R-style tibble() display for pandas DataFrames using Rich

pandas-tibble

Display pandas DataFrames with R-style tibble formatting in the terminal.

What it does

• Prints DataFrames with column type annotations (<chr>, <int>, <dbl>, <date>, <datetime>)
• Shows dimensions at the top
• Distinguishes between date and datetime types
• Provides glimpse() for quick column overview

Installation

pip install pandas-tibble

For development:

git clone https://github.com/caspercrause/pandas-tibble.git
cd pandas-tibble
poetry install

Requirements

• Python >= 3.10.0
• pandas >= 2.0.0
• rich >= 13.0.0

Usage

tibble()

Display DataFrame with type annotations:

import pandas as pd
from pandas_tibble import tibble
from datetime import date

df = pd.DataFrame({
    'start_date': [date(2024, 1, i) for i in range(1, 6)],
    'name': ['Alice', 'Bob', 'Charlie', 'Diana', 'Eve'],
    'value': [100, 200, 300, 400, 500]
})

tibble(df)

Output:

# A DataFrame: 5 × 3

start_date  name     value
<date>      <chr>    <int>
━━━━━━━━━━━━━━━━━━━━━━━━━━━
2024-01-01  Alice    100
2024-01-02  Bob      200
2024-01-03  Charlie  300
2024-01-04  Diana    400
2024-01-05  Eve      500

Options:

tibble(df, max_rows=20)         # Show more rows
tibble(df, show_index=True)     # Include index column

glimpse()

Quick column overview:

glimpse(df)

Output:

Rows: 5
Columns: 3

start_date  <date>  2024-01-01, 2024-01-02, 2024-01-03...
name        <chr>   Alice, Bob, Charlie...
value       <int>   100, 200, 300...

Type mapping

pandas dtype	Display	Format
object (string)	<chr>	as-is
int64	<int>	as-is
float64	<dbl>	2 decimals
bool	<lgl>	True/False
datetime64[ns]	<datetime>	YYYY-MM-DD HH:MM:SS
object (date)	<date>	YYYY-MM-DD
category	<fctr>	as-is
timedelta64[ns]	<timedelta>	as-is

Missing values display as NA.

What it doesn't do

• Does not create a Tibble class (works with standard pandas DataFrames)
• Does not modify DataFrame behavior
• Does not replicate R tibble's subsetting rules
• Does not support tibble construction syntax

This is a display library, not a DataFrame replacement.

License

MIT

Author

Casper Crause