Metadata-Version: 2.1
Name: preJProcess
Version: 0.0.2
Summary: Pre processing the Data Frame
Home-page: https://github.com/jeetbhatt-sys/DataPreProcess
Author: Jeet Bhatt
Author-email: jeetbhatt.va@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE

#preProcess
This is one basic project , which pre processes the data frame , removing null values and standard scaling.

#installation

pip install preJProcess


#usage 


from sklearn.preprocessing import StandardScaler

class preProcess():
    def __init__(self,df):
        self.df = df
        
    def preProcessData(self):
        print("Null values present in your data : ", self.df.isna().sum())
        print("Preprocessing the data, removing Null Values....")
        columns = self.df.columns
        scalar = StandardScaler()
        for col in columns:
            print("Processing : " , col)
            self.df[col].fillna(self.df['TOEFL Score'].mean(),inplace=True)
        scalar.fit_transform(self.df)
        return self.df
    


