How palliplease/edaxe works
EDAxe is a Python library for exploratory data analysis and dataframe preprocessing. The main workflow is a user-supplied dataframe passed to generate_summary, which computes dataset and column metrics, optionally displays visualizations, returns summary data, and can save the column table as CSV. Preprocessing operations are separate user-invoked tools; the sampled source does not show them wired into the summary workflow. The README describes the capabilities, while preprocessing excerpts are partial, so uncertain internal links are omitted.
Main entry points: summary.py Generate summary · preprocessing.py Filter rows
Components 13
Data analysis
- Generate summary
EDAxe/summary.py
Data preprocessing
- Filter rows
EDAxe/preprocessing.py - Filter columns
EDAxe/preprocessing.py - Impute missing values
EDAxe/preprocessing.py - Encode categories
EDAxe/preprocessing.py - Scale features
EDAxe/preprocessing.py
Results and display
- Summary data
- EDA visualizations
EDAxe/summary.py - CSV summary
Other components
- Data analyst
- Input dataframe
- Plotly
- Seaborn and Matplotlib
Connections 18
- Data analyst → Input dataframe: provides
- Data analyst → Generate summary: invokes
- Input dataframe → Generate summary: analyzes
- Generate summary → Summary data: returns
- Generate summary → EDA visualizations: displays
- Generate summary → CSV summary: writes when requested
- Generate summary → Plotly: renders pie chart
- Generate summary → Seaborn and Matplotlib: plots metrics
- Data analyst → Filter rows: invokes
- Data analyst → Filter columns: invokes
- Data analyst → Impute missing values: invokes
- Data analyst → Encode categories: invokes
- Data analyst → Scale features: invokes
- Input dataframe → Filter rows: filters
- Input dataframe → Filter columns: filters
- Input dataframe → Impute missing values: fills missing values
- Input dataframe → Encode categories: encodes
- Input dataframe → Scale features: scales