Skip to main content

A data tools library for loading, preprocessing, exploratory analysis, and visualization.

Project description

TaboTools

TaboTools is a Python library designed to streamline data processing workflows, including file loading, data preprocessing, exploratory analysis, and visualization. This package provides a set of tools to simplify the tasks of cleaning, analyzing, and visualizing your data.

Features

  • File Loading: Automatically loads data from various file formats.
  • Data Preprocessing: Checks data types, detects full and implicit duplicates, and processes date columns.
  • Exploratory Data Analysis: Provides quick statistical insights and analysis of different feature types.
  • Data Visualization: Generates customizable visualizations to aid in data understanding.

Installation

You can install TaboTools directly from PyPI:

pip install tabotools

Usage

Below is an example of how to use the DataProcessor class provided by TaboTools. In this example, we initialize the processor with an abstract file path and specify which columns should be parsed as dates.

from tabotools import DataProcessor

# Initialize the DataProcessor with a generic data file and a list of date columns.
data_processor = DataProcessor(
    file_path='data/sample_data.csv',
    parse_dates=['created_at', 'updated_at', 'published_at']
)

# Run data preprocessing: this method checks data types and identifies duplicate records.
data_processor.data_preprocessor()

# Perform exploratory data analysis by specifying the target feature.
data_processor.eda(target_value='sale_price')

# Display dataset information including:
# - File path and source
# - DataFrame name or identifier
# - Lists of categorical, numerical, and time columns
# - The designated target feature
data_processor.info()

Dependencies

TaboTools requires the following libraries:

  • Python
  • pandas
  • matplotlib
  • seaborn
  • IPython

Contributing

Contributions to TaboTools are welcome! If you have any suggestions, bug fixes, or improvements, please open an issue or submit a pull request.

License

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

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

tabotools-0.1.4.tar.gz (10.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tabotools-0.1.4-py3-none-any.whl (11.3 kB view details)

Uploaded Python 3

File details

Details for the file tabotools-0.1.4.tar.gz.

File metadata

  • Download URL: tabotools-0.1.4.tar.gz
  • Upload date:
  • Size: 10.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for tabotools-0.1.4.tar.gz
Algorithm Hash digest
SHA256 0aef67160381e1d61a64f36f2f99b3f02f5b36ccf5724ce3c7308f9729613a7f
MD5 87528c1512e57cecb9e68f9b7bff790e
BLAKE2b-256 5a7d213d1e1ee36fa200ca3b0600fb1b9b3853248f6abad91df202a0c1facad8

See more details on using hashes here.

File details

Details for the file tabotools-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: tabotools-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 11.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for tabotools-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 27b7d2ac2943136abebf6a1c3f5ec2187f61bc4be09309f66504294f06ac31a0
MD5 0933565b081e843b94eff5ea976f62c5
BLAKE2b-256 df93a45968611928f6c86bd519dd0f553385b660feb44043c8ceab6dfdfb4ef3

See more details on using hashes here.

Supported by

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