Package: dupandas
# **dupandas:** data deduplication of text records in a pandas dataframe[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](http://www.repostatus.org/badges/latest/wip.svg)](https://github.com/shivam5992/dupandas) [![Twitter Follow](https://img.shields.io/twitter/follow/shields_io.svg?style=social&label=Follow&maxAge=2592000)](https://twitter.com/shivamshaz)dupandas is a python package to perform data deduplication on columns of a pandas dataframe using flexible text matching. It is compatible with both versions of python (2.x and 3.x). dupandas can find duplicate any kinds of text records in the pandas data. It comprises of sophisticated Matchers that can handle spelling differences and phonetics. It also comprises of several Cleaners, which can be used to clean up the noise present in the text data such as punctuations, digits, casing etc.For fast computations, dupandas uses lucene based text indexing. In the input_config, if "indexing" = True, then it indexes the dataset in RAMDirectory which is used to identify and search similar strings. Check out the instructions of installing PyLucene below.The beautiful part of dupandas is that it's Matchers, Cleaners and Indexing functions can be used as standalone packages while working with text data.## InstallationFollowing python modules are required to use dupandas: **pandas, fuzzy, python-levenshtein** . These modules can be installed using pip command:```pythonpip install dupandas pandas fuzzy python-levenshtein```**OR** if dependencies are already installed:```pip install dupandas```**OPTIONAL** For faster implementation dupandas with indexing feature is recommended. dupandas uses PuLucene for data indexing purposes.**PyLucene Installation:** Please note that for lucene indexing, java needs to be installed. Java 8 is recommended. Refer to [this](https://www.digitalocean.com/community/tutorials/how-to-install-java-on-ubuntu-with-apt-get) link```sudo apt-get updatesudo apt-get install pyluceneAfter Installation, edit ~/.bashrc file, and add the following line at the endexport LD_LIBRARY_PATH=/usr/lib/jvm/java_folder_name/jre/lib/amd64/serverexample: export LD_LIBRARY_PATH=/usr/lib/jvm/java-8-oracle/jre/lib/amd64/server```**Note:** The use of indexing can reduce the overall time of computation and execution to one third of original.## Usage : dupandasdupandas using default Matchers and Cleaners, Default Matcher and Cleaners are Exact Match and No Cleaning respectively.``` pythonfrom dupandas import Dedupedupe = Dedupe()input_config = {'input_data' : pandas_dataframe,'column' : 'column_name_to_deduplicate','_id' : 'unique_id_column_of_dataset',}results = dupe.dedupe(input_config)```dupandas using custom Cleaner and Matcher configs```  pythonfrom dupandas import Dedupeclean_config = { 'lower' : True, 'punctuation' : True, 'whitespace' : True, 'digit' : True }match_config = { 'exact' : False, 'levenshtein' : True, 'soundex' : False, 'nysiis' : False}dupe = Dedupe(clean_config = clean_config, match_config = match_config)input_config = {'input_data' : pandas_dataframe,'column' : 'column_name_to_deduplicate','_id' : 'unique_id_column_of_dataset',}results = dupe.dedupe(input_config)```Other options in input_config```pythoninput_config = {'input_data' : pandas_dataframe,'column' : 'column_name_to_deduplicate','_id' : 'unique_id_column_of_dataset','score_column' : 'name_of_the_column_for_confidence_score','threshold' : 0.75, # float value of threshold'unique_pairs' : True, # boolean to get unique (A=B) or duplicate (A=B and B=A) results'indexing' : False # Boolean to set lucene indexing = True / False, Default: False}```## Usage : standalone Cleaner class```pythonfrom dupandas import Cleanerclean_config = { 'lower' : True, 'punctuation' : True, 'whitespace' : True, 'digit' : True }clean = Cleaner(clean_config)clean.clean_text("new Delhi 3#! 34 ")```## Usage: standalone Matcher class```pythonfrom dupandas import Matchermatch_config = { 'exact' : False, 'levenshtein' : True, 'soundex' : False, 'nysiis' : False}match = Matcher(match_config)match.match_elements("new delhi", "newdeli")```## IssuesThanks for checking this work, Yes ofcourse there is a scope of improvement, Feel free to submit issues and enhancement requests.## Contributing#### ToDos1. [ ]  V2: Add Support for multi column match2. [ ]  V2: Add More Matchers, Cleaners3. [ ]  V2: Remove Library Dependencies4. [ ]  V2: Handle Longer Texts, Optimize Speed, Lucene Time Optimize, fix input bugs#### Steps1. **Fork** the repo on GitHub2. **Clone** the project to your own machine3. **Commit** changes to your own branch4. **Push** your work back up to your fork5. Submit a **Pull request**