datalib-ha 0.1.0

A comprehensive data analysis library for Python

DataLib: Python Data Analysis Library

Overview

DataLib is a comprehensive Python library designed to simplify data manipulation, statistical analysis, visualization, and machine learning tasks. It provides an intuitive and powerful set of tools for data scientists, researchers, and analysts.

Features

Data Manipulation

• CSV file loading and saving
• Data filtering
• Missing value handling
• Data normalization

Statistical Analysis

• Descriptive statistics
• Correlation analysis
• T-tests
• Chi-square tests

Data Visualization

• Bar plots
• Histograms
• Scatter plots
• Correlation heatmaps

Advanced Analysis

• Linear and Polynomial Regression
• Classification Algorithms (KNN, Decision Trees)
• Clustering (K-means)
• Dimensionality Reduction (PCA)

Installation

pip install datalib

Quick Examples

Data Manipulation

from datalib.data_manipulation import DataManipulation

# Load CSV
df = DataManipulation.load_csv('data.csv')

# Filter data
filtered_df = DataManipulation.filter_data(df, {'age': lambda x: x > 25})

Statistical Analysis

from datalib.statistics import StatisticalAnalysis

# Calculate descriptive stats
stats = StatisticalAnalysis.descriptive_stats(df['column'])

# Correlation matrix
corr_matrix = StatisticalAnalysis.correlation(df)

Visualization

from datalib.visualization import DataVisualization

# Create bar plot
DataVisualization.bar_plot(df, 'category', 'value')

# Scatter plot
DataVisualization.scatter_plot(df, 'x_column', 'y_column')

Contributing

Contributions are welcome! Please check our GitHub repository for guidelines.

License

This project is licensed under the MIT License.