Getting Started#

Installation#

Recommended

Use a virtual environment to prevent conflicts with existing package versions. Frameon requires specific versions of dependencies that may affect other packages.

Basic Installation#

Using pip:

pip install frameon

Using poetry:

poetry add frameon

Installation with Virtual Environment#

Python’s built-in venv:

# Create and activate environment
python -m venv frameon_env
source frameon_env/bin/activate

pip install frameon

Poetry (manages virtual env automatically):

# In your project directory
poetry init  # For new projects
poetry add frameon

Access Patterns#

DataFrame Operations

df.explore.method()    # Dataset exploration
df.preproc.method()    # Table transformations
df.analyze.method()    # Analytical methods
df.viz.method()        # Visualizations
df.stats.method()      # Statistical analysis

Series Operations

df['col'].explore.method()    # Column analysis
df['col'].preproc.method()    # Value transformations

Basic Usage#

  1. Import and wrap your DataFrame:

    import pandas as pd
from frameon import FrameOn as fo

# Create or load your DataFrame
df = pd.read_csv('your_data.csv')

# Add Frameon functionality
df = fo(df)

  2. Explore your data:

    • For DataFrame-level operations:

      df.explore.info()
df.viz.bar()

    • For column-specific operations:

      df['price'].explore.info()
df['date'].preproc.to_categorical()

Pandas Compatibility#

All standard operations remain available:

df.groupby('category').mean()
df.query('price > 100')

Next Steps#