Python In Practice - 15 Projects to Master Python - Data Cleaning

The video tutorial covers handling CSV files using pandas in Python. It explains how to import CSV files, rename columns, skip rows, and handle NaN values. The tutorial also demonstrates how to drop specific rows and columns, providing a comprehensive guide to data cleaning and manipulation using pandas.

What is the primary library used for data manipulation in the tutorial?

• Matplotlib

• Pandas

• SciPy

• NumPy

Which parameter is used to rename columns while importing a CSV file?

• columns

• names

• index_col

• header

What is the purpose of the 'skiprows' parameter?

• To rename columns

• To change data types

• To skip rows

• To skip columns

What does NaN stand for in data analysis?

• Not a Number

• Not a Name

• No Available Number

• Null and None

Which method is used to detect NaN values in a DataFrame?

• dropna

• isnull

• replace

• fillna

How can you fill NaN values with the preceding value in a column?

• bfill

• pad

• fillna

• dropna

Which method is used to remove rows with NaN values?

• isnull

• replace

• fillna

• dropna

What function is used to delete specific rows from a DataFrame?

• remove

• delete

• drop

• erase

How can you delete specific columns from a DataFrame?

• remove(columns=...)

• drop(columns=...)

• delete(columns=...)

• erase(columns=...)

What is the effect of using the 'drop' method on a DataFrame?

• It renames columns

• It adds new rows

• It changes data types

• It removes specified rows or columns