Python for Data Analysis: Step-By-Step with Projects - Renaming Columns

The video tutorial focuses on standardizing column names in a pandas dataframe. It covers the use of string methods like lower, upper, and title to ensure consistent capitalization. The tutorial also explains how to rename columns using the rename method, both with a dictionary and by applying functions. Advanced techniques using the mapper and axis parameters are discussed. Finally, the video highlights the importance of saving the modified dataframe for future use.

Why is it important to standardize column names in a dataframe?

• To improve the speed of data processing

• To reduce the size of the dataframe

• To ensure consistent access to columns

• To make the data look more professional

Which string method would you use to convert all column names to lowercase?

• upper()

• title()

• lower()

• capitalize()

What must you do after using a string method to change column names?

• Delete the original dataframe

• Save the dataframe to a file

• Reassign the dataframe to apply changes

• Print the dataframe

How can you rename a specific column using the rename method?

• By using a list of new names

• By changing the index labels

• By providing a dictionary mapping old names to new names

• By using a string method

What does the rename method return when used on a dataframe?

• A copy of the dataframe with changes

• A list of column names

• An error if the column does not exist

• A modified dataframe

Which parameter is used with the rename method to apply a function to column names?

• axis

• mapper

• index

• columns

How can you change all index labels to uppercase using the rename method?

• Set the index parameter to STR.upper

• Use the columns parameter with STR.upper

• Set the axis parameter to 1

• Use the mapper parameter with STR.lower