nafeezkamal123 / ex-01-data-cleaning

Ex-01_DS_Data_Cleansing

AIM

To read the given data and perform data cleaning and save the cleaned data to a file.

Explanation

Data cleaning is the process of preparing data for analysis by removing or modifying data that is incorrect ,incompleted , irrelevant , duplicated or improperly formatted. Data cleaning is not simply about erasing data ,but rather finding a way to maximize datasets accuracy without necessarily deleting the information.

ALGORITHM

STEP 1

Read the given Data

STEP 2

Get the information about the data

STEP 3

Remove the null values from the data

STEP 4

Save the Clean data to the file

CODE

import pandas as pd
df=pd.read_csv("/content/Loan_data.csv")
print(df)
df.head(10)
df.info()
df.isnull()
df.isnull().sum()
df['Loan_ID']=df['Loan_ID'].fillna(df['Dependents'].mode()[0])
df['Dependents']=df['Dependents'].fillna(df['Dependents'].mode()[0])
df['Education']=df['Education'].fillna(df['Dependents'].mode()[0])
df.head()
df['ApplicantIncome']=df['ApplicantIncome'].fillna(df['ApplicantIncome'].mean())
df['Loan_Amount_Term']=df['Loan_Amount_Term'].fillna(df['Loan_Amount_Term'].mean())
df.head()
df['Credit_History']=df['Credit_History'].fillna(df['Credit_History'].median())
df.head()
df.info()
df.isnull().sum()

OUPUT

DATA:

NON NULL BEFORE:

MODE:

MEAN:

MEDIAN:

NON NULL AFTER:

RESULT

Thus, the given data is read, cleansed and the cleansed data is saved into the file.