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Auxiliary functions to clean pandas data frames

Project description

Pywrangle

About

PyWrangle is an open-source Python library for data wrangling. Wikipedia defines data wrangling as follows:

is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics

Functions

PyWrangle currently supports:

  • cleaning strings
  • tracking dataframe changes
  • identifying data entry errors

Documentation & Distribution

Documentation is available here

Distribution is available here

Install

Requirements

  • Python >= 3.8
  • numpy >= 1.14.4
  • pandas >= 1.0.3
  • fuzzywuzzy >= 0.18.0
  • python-levenshtein >= 0.12.0
  • metaphone >= 0.6

Pip Install

To install pywrangle, use pip:

pip install pywrangle

Import

Per convention with Python libraries for data science, import pywrangle as follows:

>>> import pywrangle as pw

Contributing

Like all developers, I love open source. Please reference the contributing guidelines here

History

Version = "0.3.0"

  • Removed identify missing data from library -- too much overlap with the missingno library.
  • Added identify_errors() function. Uses levenshtein's distance & double metaphone string matching algorithms to identify potential data entry errors in string columns.
  • Refactored code into different sub libraries
  • Placed documentation on ReadTheDocs.

version = "0.2.40"

  • refactored code for clarity
  • added display info to print_df_changes

version = "0.2.1"

  • Created init file for function imports
  • Documentation on importing pywrangle
  • Added numpy as required package.
  • Changed package requirements to greater than or equal to.

version = "0.0.1"

  • Init

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