What is the simplest way to address the missing value problem in data science applications? O a. Replace all the missing values in each column by some fixed value O b. Delete all the columns from the Data Frame in which even a single missing value exists O . Delete all the rows from the Data Frame in which even a single missing value exists O d. Replace the missing values in each column by the mean of each column

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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What is the simplest way to address the missing value problem in data science applications?
O a. Replace all the missing values in each column by some fixed value
O b. Delete all the columns from the Data Frame in which even a single missing value exists
O . Delete all the rows from the Data Frame in which even a single missing value exists
O d. Replace the missing values in each column by the mean of each column
Transcribed Image Text:What is the simplest way to address the missing value problem in data science applications? O a. Replace all the missing values in each column by some fixed value O b. Delete all the columns from the Data Frame in which even a single missing value exists O . Delete all the rows from the Data Frame in which even a single missing value exists O d. Replace the missing values in each column by the mean of each column
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