Metadata-Version: 2.1
Name: quickdataanalysis
Version: 0.0.2
Summary: Kick start your data analysis with these functions
Home-page: https://github.com/Santhoshkumard11/quickdataanalysis
Author: Santhoshkumard11
Maintainer: Santhoshkumard11
License: MIT
Description: # quick data analysis
        
        [![PyPi](https://img.shields.io/badge/pypi%20package-0.0.1-blue)](https://pypi.org/project/quickdataanalysis/)
        [![](https://img.shields.io/github/license/Santhoshkumard11/quickdataanalysis.svg?colorB=00fff0)](https://github.com/Santhoshkumard11/quickdataanalysis/blob/master/LICENSE.md)
        [![Release](https://img.shields.io/badge/Next%20Release-Oct%2020-green)](https://pypi.org/project/quickdataanalysis/)
        ![Issues](https://img.shields.io/github/issues/Santhoshkumard11/quickdataanalysis)
        
        This packages allows you to kick start your data analysis and make faster insights of the data.
        
        # Requirements
        * Pandas >=1.0.1
        
        ## Documentation
        
        ## 1) Creating Dummies for columns
        
        The create_dummies method will return dummies for the columns. For example you want to dummies for Gender column put the column name in a list and you will get the dataframe with the dummies.
        
               >>> df =  create_dummies(df_train,["sex"])
               >>> df
               male female
               0      1
               1      0
               1      0
               1      0
        
        ## 2) Counting the column values
        
        The count_values method will return the number of values in the columns. For example you want to count the number of females.
        
            >>> count_values(df_train["female"],1,False)
              312
        
        ## ToDo
        
         - [ ] Add more method
        
        
        
        All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome :)
        
        Happy Coding!!
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries
Description-Content-Type: text/markdown
