Metadata-Version: 2.1
Name: crystal-ball
Version: 0.1.1
Summary: Useful crystal-ball-related stuff.
Home-page: http://pypi.python.org/pypi/crystal-ball/
Author: Winn Y Cui
Author-email: winn.yc@berkeley.edu
License: LICENSE.txt
Description: # Crystal-Ball Documentation
        
        If you have hundreds of csvs you need to quickly digest and understand, you can use crystal-ball to help with the onboarding and data exploration phase of your project. You will be able to immediately dive into an expansive data set without getting lost.
        
        ## Crystal-Ball Features:
        - find specific columns and tables you may be interested in, but may have otherwise not known where to look.
        - walk through connections between different csvs, 
        - compare and establish foreign key and primary key relationships by using simple boxplots
        - dynamically create a master table of useful information while simultaneously recording your step-by-step process for future reference.
        
        ## Methods
        
        ###  cb.contains(keywords, all_colnames) -> list
        
        **_Purpose:_**
        - Determine whether a keyword (substring) exists in a given list of column names (strings). 
        - Note: This search is case sensitive!
        
        **_Parameters:_**
        - **keywords** (list of strings)
          - A key word
        - **all_colnames** (list of strings)
          - List of column names of a table, or for many tables. 
          - If no argument is provided, this function will use the column names generated when the run method was called.
          
        **_Returns:_**
        - **list** (a list of bools): 
          - For each index corresponding to a keyword, True if substring exists in list of strings, otherwise False.
        
        **_Examples:_**
        ```python
        colnames = ['id', 'name', 'title']
        cb.contains(['name'], colnames) # returns [True]
        cb.contains(['Name'], colnames) # returns [False]
        cb.contains(['name', 'Name'], colnames) # returns [True, False]
        ```
        
        ###  cb.featureSearch(keywords, all_colnames) -> list
        
        **_Purpose:_**
        - Find features (column names) that contain the substrings specified in keywords. 
        - Note: This search is case sensitive!
        
        **_Parameters:_**
        - **keywords** (list of strings)
            - List of key words that the user is interested in
        - **colnames** (list of strings)
            - List of column names of a table, or for many tables. 
            - If no argument is provided, this function will use the column names generated when the run method was called.
        
        **_Returns:_**
        - **list** (list of features): 
            - List will contain all features (column names) that contains one/all substrings found in keywords.
            - List will be sorted in alphabetical order.
        
        **_Examples:_**
        ```python
        colnames = ['id', 'name', 'nameType', 'subSpeciesName', 'title']
        cb.featureSearch(['name'], colnames) # returns ['name', 'nameType']
        cb.featureSearch(['Name'], colnames) # returns ['subSpeciesName']
        cb.featureSearch(['name', 'Name'], colnames) # returns ['name', 'nameType', 'subSpeciesName']
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
