edabyalex 0.1.2

A Python package for streamlined Exploratory Data Analysis (EDA) and Extraction Transform Load (ETL)

EDAbyAlex

A Python package for streamlined Exploratory Data Analysis (EDA) with support for various file formats.

Features

• Flexible Data Loading

  • Support for both CSV and Excel (.xlsx) files
  • Single file loading with automatic sheet detection
  • Multiple file loading with pattern matching
  • Smart Excel sheet handling

• Comprehensive EDA Tools

  • Quick data preview (first 10 rows)
  • Statistical description of numerical columns
  • Dataset information and structure
  • Column listings
  • Unique value analysis
  • Missing value detection

Installation

pip install edabyalex

Quick Start

from extractor import extractor

# Initialize and load a CSV file
eda = extractor(path="data.csv")
eda.load()
eda.eda()  # Run complete analysis

Detailed Usage

Initialization

from extractor import extractor

# For CSV files
eda = extractor(
    path="path/to/file.csv",  # Required: File path
    file_type=None,           # Optional: Defaults to CSV
    file_query=None           # Optional: For multiple file loading
)

# For Excel files
eda = extractor(
    path="path/to/file.xlsx",
    file_type=".xlsx",
    sheet_name="Sheet1"       # Optional: Sheet name
)

Loading Data

Single File Loading

# Load CSV
eda = extractor(path="data.csv")
df = eda.load()

# Load Excel with specific sheet
eda = extractor(path="data.xlsx", file_type=".xlsx")
df = eda.load(sheet_name="Sheet1")

Multiple File Loading

# Load multiple CSV files
eda = extractor(path="./data/", file_query="2024")
df = eda.load_multiple_csv()

# Load multiple Excel files
eda = extractor(path="./data/", file_query="2024")
df = eda.load_multiple_xlsx()

Exploratory Data Analysis

# Run complete EDA
eda.eda()  # Shows:
           # - Data preview (first 10 rows)
           # - Statistical description
           # - Dataset information
           # - Column list
           # - Unique values
           # - Missing values

# View columns
eda.columns()

# Analyze unique values
eda.print_unique()  # All columns
eda.unique_values(col_name="category")  # Specific column

Data Export

# Export to CSV
eda.export(file_type="csv", file_name="output_data")

# Export to Excel
eda.export(file_type=".xlsx", file_name="output_data")

Error Handling

The package includes comprehensive error handling for common scenarios:

• File not found
• Invalid sheet names in Excel files
• Missing columns
• Operations on unloaded data

Example:

try:
    eda = extractor(path="data.xlsx", file_type=".xlsx")
    df = eda.load(sheet_name="NonexistentSheet")
except TypeError as e:
    print(f"Sheet error: {e}")

Requirements

• pandas >= 1.0.0
• numpy >= 1.18.0
• openpyxl >= 3.0.0 (for Excel support)

Version History

0.1.2 (updating documentation)

• Updated README.md

0.1.1 (export feature)

• Added export functionality
• Improved package build configuration
• Enhanced error handling
• Updated documentation

0.1.0 (Initial Release)

• Basic EDA functionality
• Support for CSV and Excel files
• Data loading and preview features
• Unique value analysis
• Missing value detection

License

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

Author

Alex Yang

Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.