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Pre processing the Data Frame

Project description

#Preprocessing

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

#Main Features

Removes Null values from DataFrame and do standard Scaling of data

#Installation

pip install preJProcess

#Usage

e.g, p = preProcess(df) df ==> dataFrame p.preProcessData() p.scaling()

#Sample Code 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[col].mean(),inplace=True)
    return self.df
.....

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