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/Data_set.csv")
print(df)
df.head(10)
df.info()
df.isnull()
df.isnull().sum()
df['show_name']=df['show_name'].fillna(df['aired_on'].mode()[0])
df['aired_on']=df['aired_on'].fillna(df['aired_on'].mode()[0])
df['original_network']=df['original_network'].fillna(df['aired_on'].mode()[0])
df.head()
df['rating']=df['rating'].fillna(df['rating'].mean())
df['current_overall_rank']=df['current_overall_rank'].fillna(df['current_overall_rank'].mean())
df.head()
df['watchers']=df['watchers'].fillna(df['watchers'].median())
df.head()
df.info()
df.isnull().sum()