Metadata-Version: 1.0
Name: ctnamecleaner
Version: 0.7
Summary: Replace village and commonly-misspelled Connecticut town names with real town names.
Home-page: https://github.com/jakekara/ctnamecleaner-py
Author: Jake Kara
Author-email: jake@jakekara.com
License: GPL
Description: # CT Name Cleaner
        
        Resolve village and coloquial Connecticut town names, as well as common
        misspellings of Connecticut town names to their official town names.
        
        This is based on an R package of the same name by my colleague Andrew Ba Tran.
        
        This installs a command line script, ctclean,  as well as a library 
        
        by Jake Kara, jake@jakekara.com
        
        ### Installation
        
            pip install ctnamecleaner
        
        ### Command line util
        
        Usage:
        
        	$ ctclean New\ Preston
        	WASHINGTON
        	$ ctclean "New Preston"
        	WASHINGTON
        
        When nothing is found, return None:
        
        	$ ctclean NotGonnaFindItsVille
        	None
        
        Set a custom value to return on error with the --error or -e flag:
        
            $ ctclean NotGonnaFindItsVille --error "Ruh Roh"
            Ruh Roh
        
        ### Use with Pandas dataframes
        
        See the demo/ folder in this repo for an example of translating an entire
        column with the Lookup.clean_dataframe() method. It uses pandas'
        DataFrame.join() method, so it's faster than using the Lookup.cean() method
        and applying it with a lambda function yourself.
        
        ### Extending with other data
        
        Not in CT? Want to map other things, like population? Just make a spreadsheet
        and put it anywhere, online or locally, that Pandas .read_csv() can open.
        
        You can specify a spreadsheet (local or remote) to use as the lookup table
        when you instantiate a Lookup object. You have to specify a path to the sheet
        as well as the name of the raw name column and the clean name column.
        
             >>> l = lookup.Lookup(csv_url="http://path/to/your/sheet",
        			   raw_name_col="something",
        			   clean_name_col="something_else")
Platform: UNKNOWN
