Skip to main content

A package for data analysis including data description, data preprocessing, data visualization, and modeling

Project description

Pejmanai Data Analysis Package

Package Banner

Overview

  • pejmanai_data_analysis is a Python package for comprehensive data analysis, including read data in csv format, data preprocessing, data visualization, and machine learning modeling for both regression and classification problems. It provides tools to streamline the process of understanding and modeling datasets with ease.

Features

  • Data Reading: Load datasets from CSV files with error handling.
  • Data Description: View basic statistics, data information, and missing values.
  • Data Preprocessing: Handle missing values and encode categorical variables.
  • Data Visualization: Generate scatter plots, histograms, KDE plots, and heatmaps.
  • Regression Models: Evaluate multiple regression models including Linear Regression, Ridge Regression, Decision Trees, Random Forests, and K-Nearest Neighbors.
  • Classification Models: Compare various classification models such as Decision Trees, Random Forests, Support Vector Machines, K-Nearest Neighbors, and MLP Classifiers.

Installation

  • You can install the package using pip: pip install pejmanai_data_analysis

Usage

  • Data Reading
  • from pejmanai_data_analysis.app import read_csv
  • df = read_csv('path/to/your/data.csv')
  • print(df)
  • Data Description
  • from pejmanai_data_analysis.app import data_description
  • data_description('path/to/your/data.csv')
  • Data Preprocessing
  • from pejmanai_data_analysis.app import data_preprocessing
  • df_preprocessed = data_preprocessing('path/to/your/data.csv')
  • print(df_preprocessed)
  • Data Visualization
  • from pejmanai_data_analysis.app import data_visualization
  • data_visualization('path/to/your/data.csv', 'x_column', 'y_column')
  • Data Prediction (Regression)
  • from pejmanai_data_analysis.app import data_prediction
  • data_prediction('path/to/your/data.csv', 'target_column')
  • Data Classification
  • from pejmanai_data_analysis.app import data_classification
  • data_classification('path/to/your/data.csv', 'target_column')

License

  • This project is licensed under the MIT License

Contact

For any questions or feedback, please reach out to Pejman Ebrahimi.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pejmanai_data_analysis-0.1.2.tar.gz (4.6 kB view details)

Uploaded Source

Built Distribution

pejmanai_data_analysis-0.1.2-py3-none-any.whl (5.0 kB view details)

Uploaded Python 3

File details

Details for the file pejmanai_data_analysis-0.1.2.tar.gz.

File metadata

File hashes

Hashes for pejmanai_data_analysis-0.1.2.tar.gz
Algorithm Hash digest
SHA256 3a284a99d49193af5328f81a8e1682df41a3c0ead3e1ba3c427533b9bf75340d
MD5 ceee8737a892c55bc7a80cd6a97c8373
BLAKE2b-256 a2466c75299c59891290d6a8396217976a5b2e5b04886986d26daeb9d49e5ade

See more details on using hashes here.

File details

Details for the file pejmanai_data_analysis-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for pejmanai_data_analysis-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 5d2ce2cb01a2586431823e211817dbe810919a4f86e4537b87db9cf451753307
MD5 1f1492d7ab725f153948da8e6daf8a5b
BLAKE2b-256 0c5088df1d8ee593debff6c45853101907e81f650c9e03897a41cb64a699ba0e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page