Course Content

Identifying Fake News

Introduction True News and Fake News Data Preprocessing Clean and Convert Initial Model Fit Decision Tree Comparison Fake News Tool (Bonus)

Data Preprocessing

As a mandatory step in our analysis, we must preprocess our data. Data preprocessing is the process of cleaning, transforming, and organizing the data to make it more suitable for analysis and modeling. This typically involves several steps, such as the following:

removing missing or duplicate values;
correcting inconsistencies;
transforming the data into a format that is easier to manage.

Task

Remove unnecessary columns (for our further analysis): 'title', 'subject', and 'date'.
Use the appropriate method to remove duplicates.
Use the appropriate methods to shuffle the DataFrame and reset its index.
Use the appropriate method to check for missing values (NaN values).

Mark tasks as Completed

Everything was clear?

Section 1. Chapter 3

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