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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